This retrospective observational study compared severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA load in nasopharyngeal specimens (NPs) from patients with breakthrough coronavirus ...disease 2019 (COVID‐19) caused by the Omicron BA.1 or BA.2 sublineages. The convenience sample was composed of 277 outpatients (176 female/112 male; median age, 48 years; range, 12–97) with breakthrough COVID‐19 (n = 130 due to BA.1 and n = 147 due to BA.2). All participants had completed a full vaccination schedule and 56% had received a booster vaccine dose at the time of COVID‐19 breakthrough microbiological diagnosis. NPs were collected within 7 days (median 2 days) after symptom onset. The TaqPath COVID‐19 Combo Kit (Thermo Fisher Scientific) was used to estimate viral loads in NPs. Overall, viral RNA loads in NPs were comparable (p = 0.31) for BA.1 (median, 7.1 log10 copies/ml; range, 2.7–10.6) and BA.2 (median, 7.5 log10 copies/ml; range, 2.7–10.6), yet peak viral load appeared to be reached sooner for BA.2 than for BA.1 (Day 1 vs. Days 3–5; p = 0.002). Time elapsed since last vaccine dose had no significant impact on SARS‐CoV‐2 RNA loads in the upper respiratory tract (URT) for either BA.1 or BA.2. The data presented do not support that the transmissibility advantage of BA.2 over BA.1 is related to generation of higher viral loads in the URT early after infection.
Recombination is a pervasive process generating diversity in most viruses. It joins variants that arise independently within the same molecule, creating new opportunities for viruses to overcome ...selective pressures and to adapt to new environments and hosts. Consequently, the analysis of viral recombination attracts the interest of clinicians, epidemiologists, molecular biologists and evolutionary biologists. In this review we present an overview of three major areas related to viral recombination: (i) the molecular mechanisms that underlie recombination in model viruses, including DNA-viruses (Herpesvirus) and RNA-viruses (Human Influenza Virus and Human Immunodeficiency Virus), (ii) the analytical procedures to detect recombination in viral sequences and to determine the recombination breakpoints, along with the conceptual and methodological tools currently used and a brief overview of the impact of new sequencing technologies on the detection of recombination, and (iii) the major areas in the evolutionary analysis of viral populations on which recombination has an impact. These include the evaluation of selective pressures acting on viral populations, the application of evolutionary reconstructions in the characterization of centralized genes for vaccine design, and the evaluation of linkage disequilibrium and population structure.
Bacteriophages play key roles in bacterial ecology and evolution and are potential antimicrobials. However, the determinants of phage-host specificity remain elusive. Here, we isolate 46 phages to ...challenge 138 representative clinical isolates of Klebsiella pneumoniae, a widespread opportunistic pathogen. Spot tests show a narrow host range for most phages, with <2% of 6,319 phage-host combinations tested yielding detectable interactions. Bacterial capsule diversity is the main factor restricting phage host range. Consequently, phage-encoded depolymerases are key determinants of host tropism, and depolymerase sequence types are associated with the ability to infect specific capsular types across phage families. However, all phages with a broader host range found do not encode canonical depolymerases, suggesting alternative modes of entry. These findings expand our knowledge of the complex interactions between bacteria and their viruses and point out the feasibility of predicting the first steps of phage infection using bacterial and phage genome sequences.
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•Klebsiella capsular diversity restricts the host range of most Klebsiella phages•Phage-encoded depolymerase domains can predict capsular tropism•Capsular tropism predictability is limited by post-adsorptive resistance mechanisms•Phages lacking capsule dependency and depolymerases exhibit broader host ranges
Beamud et al. analyze the host tropism of bacteriophages infecting Klebsiella pneumoniae, a nosocomial pathogen of global concern. They identify phage sequence domains that predict capsular tropism, the main determinant of infectivity. This work demonstrates how phenotypic and genomic data can be combined to better understand virus-host interactions.
Mapping of high-throughput sequencing (HTS) reads to a single arbitrary reference genome is a frequently used approach in microbial genomics. However, the choice of a reference may represent a source ...of errors that may affect subsequent analyses such as the detection of single nucleotide polymorphisms (SNPs) and phylogenetic inference. In this work, we evaluated the effect of reference choice on short-read sequence data from five clinically and epidemiologically relevant bacteria (Klebsiella pneumoniae, Legionella pneumophila, Neisseria gonorrhoeae, Pseudomonas aeruginosa and Serratia marcescens). Publicly available whole-genome assemblies encompassing the genomic diversity of these species were selected as reference sequences, and read alignment statistics, SNP calling, recombination rates, dN/dS ratios, and phylogenetic trees were evaluated depending on the mapping reference. The choice of different reference genomes proved to have an impact on almost all the parameters considered in the five species. In addition, these biases had potential epidemiological implications such as including/excluding isolates of particular clades and the estimation of genetic distances. These findings suggest that the single reference approach might introduce systematic errors during mapping that affect subsequent analyses, particularly for data sets with isolates from genetically diverse backgrounds. In any case, exploring the effects of different references on the final conclusions is highly recommended.
We investigated whether peripheral blood levels of SARS‐CoV‐2 Spike (S) receptor binding domain antibodies (anti‐RBD), neutralizing antibodies (NtAb) targeting Omicron S, and S‐reactive‐interferon ...(IFN)‐γ‐producing CD4+ and CD8+ T cells measured after a homologous booster dose (3D) with the Comirnaty® vaccine was associated with the likelihood of subsequent breakthrough infections due to the Omicron variant. An observational study including 146 nursing home residents (median age, 80 years; range, 66–99; 109 female) evaluated for an immunological response after 3D (at a median of 16 days). Anti‐RBD total antibodies were measured by chemiluminescent immunoassay. NtAb were quantified by an Omicron S pseudotyped virus neutralization assay. SARS‐CoV‐2‐S specific‐IFNγ‐producing CD4+ and CD8+ T cells were enumerated by whole‐blood flow cytometry for intracellular cytokine staining. In total, 33/146 participants contracted breakthrough Omicron infection (symptomatic in 30/33) within 4 months after 3D. Anti‐RBD antibody levels were comparable in infected and uninfected participants (21 123 vs. 24 723 BAU/ml; p = 0.34). Likewise, NtAb titers (reciprocal IC50 titer, 157 vs. 95; p = 0.32) and frequency of virus‐reactive CD4+ (p = 0.82) and CD8+ (p = 0.91) T cells were similar across participants in both groups. anti‐RBD antibody levels and NtAb titers estimated at around the time of infection were also comparable (3445 vs. 4345 BAU/ml; p = 0.59 and 188.5 vs. 88.9; p = 0.70, respectively). Having detectable NtAb against Omicron or SARS‐CoV‐2‐S‐reactive‐IFNγ‐producing CD4+ or CD8+ T cells after 3D was not correlated with increased protection from breakthrough infection (OR, 1.50; p = 0.54; OR, 0.0; p = 0.99 and OR 3.70; p = 0.23, respectively). None of the immune parameters evaluated herein, including NtAb titers against the Omicron variant, may reliably predict at the individual level the risk of contracting COVID‐19 due to the Omicron variant in nursing home residents.
The COVID-19 pandemic was officially declared on March 11th, 2020. Since the very beginning, the spread of the virus has been tracked nearly in real-time by worldwide genome sequencing efforts. As of ...March 2021, more than 830,000 SARS-CoV-2 genomes have been uploaded in GISAID and this wealth of data allowed researchers to study the evolution of SARS-CoV-2 during this first pandemic year. In parallel, nomenclatures systems, often with poor consistency among each other, have been developed to designate emerging viral lineages. Despite general fears that the virus might mutate to become more virulent or transmissible, SARS-CoV-2 genetic diversity has remained relatively low during the first ~ 8 months of sustained human-to-human transmission. At the end of 2020/beginning of 2021, though, some alarming events started to raise concerns of possible changes in the evolutionary trajectory of the virus. Specifically, three new viral variants associated with extensive transmission have been described as variants of concern (VOC). These variants were first reported in the UK (B.1.1.7), South Africa (B.1.351) and Brazil (P.1). Their designation as VOCs was determined by an increase of local cases and by the high number of amino acid substitutions harboured by these lineages. This latter feature is reminiscent of viral sequences isolated from immunocompromised patients with long-term infection, suggesting a possible causal link. Here we review the events that led to the identification of these lineages, as well as emerging data concerning their possible implications for viral phenotypes, reinfection risk, vaccine efficiency and epidemic potential. Most of the available evidence is, to date, provisional, but still represents a starting point to uncover the potential threat posed by the VOCs. We also stress that genomic surveillance must be strengthened, especially in the wake of the vaccination campaigns.
•After months of human-to-human transmission divergent SARS-CoV-2 lineages have emerged.•The nomenclature is debated, but PANGO lineage names are: B.1.1.7, B.1.351 and P.1.•These lineages display a number of amino acid changes, especially in the S protein.•B.1.1.7, B.1.351 and P.1 may be more transmissible, their effect on disease severity is uncertain.•Some mutations in B.1.351 and P.1 may affect antibody binding or vaccine efficiency.
The objective of this study was to analyze multifunctional autoprocessing repeats-in-toxin (MARTX) toxin domain organization within the aquatic species Vibrio vulnificus as well as to study the ...evolution of the rtxA1 gene. The species is subdivided into three biotypes that differ in host range and geographical distribution. We have found three different types (I, II, and III) of V. vulnificus MARTX (MARTXVv) toxins with common domains (an autocatalytic cysteine protease domain CPD, an α/β-hydrolase domain, and a domain resembling that of the LifA protein of Escherichia coli O127:H6 E2348/69 Efa/LifA) and specific domains (a Rho-GTPase inactivation domain RID, a domain of unknown function DUF,a domain resembling that of the rtxA protein of Photorhabdus asymbiotica rtxAPA, and an actin cross-linking domain ACD). Biotype 1 isolates harbor MARTXVv toxin types I and II, biotype 2 isolates carry MARTXVv toxin type III, and biotype 3 isolates have MARTXVv toxin type II. The analyzed biotype 2 isolates harbor two identical copies of rtxA1, one chromosomal and the other plasmidic. The evolutionary history of the gene demonstrates that MARTXVv toxins are mosaics, comprising pieces with different evolutionary histories, some of which have been acquired by intra- or interspecific horizontal gene transfer. Finally, we have found evidence that the evolutionary history of the rtxA1 gene for biotype 2 differs totally from the gene history of biotypes 1 and 3.
Background. It has been accepted that the infection by Mycobacterium tuberculosis (M. tuberculosis) can be more heterogeneous than considered. The emergence of clonal variants caused by ...microevolution events leading to population heterogeneity is a phenomenon largely unexplored. Until now, we could only superficially analyze this phenomenon by standard fingerprinting (RFLP and VNTR). Methods. In this study we applied whole genome sequencing for a more in-depth analysis of the scale of microevolution both at the intrapatient and interpatient scenarios. Results. We found that the amount of variation accumulated within a patient can be as high as that observed between patients along a chain of transmission. Intrapatient diversity was found both at the extrapulmonary and respiratory sites, meaning that this variability can be transmitted and impact on the inference of transmission events. One of the events studied allowed us to track for a single strain the complete process of (i) interpatient microevolution, (ii) intrapatient respiratory variation, and (iii) isolation of different variants at different infected sites of this patient. Conclusions. Our study adds new data to the understanding of variability in M. tuberculosis in a wide clinical scenario and alerts about the difficulties of establishing thresholds to differentiate relatedness in M. tuberculosis with epidemiological purposes.
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