Search

Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.

The dynamics of SARS-CoV-2 transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the USA became increasingly significant. Notably, Galicia’s major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Background: In June, 2021, WHO published the most complete catalogue to date of resistance-conferring mutations in Mycobacterium tuberculosis. Here, we aimed to assess the performance of genome-based antimicrobial resistance prediction using the catalogue and its potential for improving diagnostics in a real low-burden setting. Methods: In this retrospective population-based genomic study M tuberculosis isolates were collected from 25 clinical laboratories in the low-burden setting of the Valencia Region, Spain. Culture-positive tuberculosis cases reported by regional public health authorities between Jan 1, 2014, and Dec 31, 2016, were included. The drug resistance profiles of these isolates were predicted by the genomic identification, via whole-genome sequencing (WGS), of the high-confidence resistance-causing variants included in the catalogue and compared with the phenotype. We determined the minimum inhibitory concentration (MIC) of the isolates with discordant resistance profiles using the resazurin microtitre assay. Findings: WGS was performed on 785 M tuberculosis complex culture-positive isolates, and the WGS resistance prediction sensitivities were: 85·4% (95% CI 70·8–94·4) for isoniazid, 73·3% (44·9–92·2) for rifampicin, 50·0% (21·1–78·9) for ethambutol, and 57·1% (34·0–78·2) for pyrazinamide; all specificities were more than 99·6%. Sensitivity values were lower than previously reported, but the overall pan-susceptibility accuracy was 96·4%. Genotypic analysis revealed that four phenotypically susceptible isolates carried mutations (rpoB Leu430Pro and rpoB Ile491Phe for rifampicin and fabG1 Leu203Leu for isoniazid) known to give borderline resistance in standard phenotypic tests. Additionally, we identified three putative resistance-associated mutations (inhA Ser94Ala, katG Leu48Pro, and katG Gly273Arg for isoniazid) in samples with substantially higher MICs than those of susceptible isolates. Combining both genomic and phenotypic data, in accordance wit

The origins of treponemal diseases have long remained unknown, especially considering the sudden onset of the first syphilis epidemic in the late 15th century in Europe and its hypothesized arrival from the Americas with Columbus’ expeditions. Recently, ancient DNA evidence has revealed various treponemal infections circulating in early modern Europe and colonial-era Mexico. However, there has been to our knowledge no genomic evidence of treponematosis recovered from either the Americas or the Old World that can be reliably dated to the time before the first trans-Atlantic contacts. Here, we present treponemal genomes from nearly 2,000-year-old human remains from Brazil. We reconstruct four ancient genomes of a prehistoric treponemal pathogen, most closely related to the bejel-causing agent Treponema pallidum endemicum. Contradicting the modern day geographical niche of bejel in the arid regions of the world, the results call into question the previous palaeopathological characterization of treponeme subspecies and showcase their adaptive potential. A high-coverage genome is used to improve molecular clock date estimations, placing the divergence of modern T. pallidum subspecies firmly in pre-Columbian times. Overall, our study demonstrates the opportunities within archaeogenetics to uncover key events in pathogen evolution and emergence, paving the way to new hypotheses on the origin and spread of treponematoses.

This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution. This work was supported by the Spanish Ministry of Science, Innovation, and Universities [RTI2018-098530-B-I00 and BFU2017-89594-R]. C-F.C. was supported by the Spanish Ministry of Science, Innovation, and Universities [BES-2015-074204]., Lactococcus garvieae is a well-known pathogen of fish, but is rarely involved in infections in humans and other mammals. In humans, the main clinical manifestation of L. garvieae infections is endocarditis usually related to the ingestion of contaminated food, such as undercooked fish and shellfish. This study presents the first complete genomic sequence of a clinical L. garvieae strain isolated from a patient with endocarditis and its comparative analysis with other genomes. This human isolate contains a circular chromosome of 2 099 060 bp and one plasmid of 50 557 bp. In comparison with other fully sequenced L. garvieae strains, the chromosomal DNA of L. garvieae Lg-Granada carries a low proportion of insertion sequence elements and a higher number of putative prophages. Our results show that, in general, L. garvieae is a highly recombinogenic species with an open pangenome in which almost 30 % of its genome has undergone horizontal transfers. Within the genus Lactococcus, L. lactis is the main donor of genetic components to L. garvieae but, taking Lg-Granada as a representative, this bacterium tends to import more genes from Bacilli taxa than from other Lactococcus species., Ministerio de Ciencia, Innovación y Universidades, Depto. de Sanidad Animal, Centro de Vigilancia Sanitaria Veterinaria (VISAVET), Fac. de Veterinaria, TRUE, pub

Viral mutations within patients nurture the adaptive potential of SARS-CoV-2 during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein we describe VIPERA (Viral Intra-Patient Evolution Reporting and Analysis), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. It has been validated using positive and negative control datasets and successfully applied to a novel case, contributing to easy and automatic analysis of intra-patient SARS-CoV-2 sequences.

We recently commented on the study by Teyssou and colleagues1 showing substantial differences across SARS-CoV-2 variants of concern RNA loads in the upper respiratory tract (URT). Regarding the Delta variant, we reported a trend towards higher viral loads in non-vaccinated individuals with COVID-19 compared to those vaccinated with a variety of COVID-19 vaccines.2 A number of studies concur on that although SARS-CoV-2 RNA loads in the upper respiratory tract of individuals with Delta variant breakthrough infection are comparable to those found in unvaccinated infected individuals, viral RNA clearance seemingly proceeds at a faster rate in the former subjects.3, 4, 5, 6 Nevertheless, analyzes in these studies were not stratified by either time elapsed since full COVID-19 vaccination3, 4, 5 or clinical status (asymptomatic vs. symptomatic) at the time of RT-PCR diagnosis.3, 4, 5, 6 Here, we add nuances to the aforementioned assumption by showing that among patients with breakthrough COVID-19, both the magnitude and dynamics of Delta variant RNA load in URT are markedly affected by time elapsed since full COVID-19 vaccination.

Highlights • Overall, higher SARS-CoV-2 RNA loads are seen for the delta variant compared to the alpha variant within 2 days after symptoms onset. • SARS-CoV-2 RNA loads were higher for the delta than the alpha variant, in both asymptomatic adults and children. • For COVID-19 patients, SARS-CoV-2 delta RNA loads were higher in non-vaccinated individuals compared with vaccinated participants. • Asymptomatic vaccinated and unvaccinated individuals displayed similar SARS-CoV-2 delta RNA loads.

The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24–26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.

[Background] Viral mutations within patients nurture the adaptive potential of SARS-CoV-2 during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intrapatient SARS-CoV-2 serial samples. Herein we describe VIPERA, a new software that integrates the evaluation of the intrapatient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection., [Methods] VIPERA is a pipeline implemented in Snakemake that analyzes a set of SARS-CoV-2 samples serially-collected from the same patient and produces a HTML report with three sections. Firstly, a summary of the samples is reported including lineage designation. Secondly, to ascertain if all samples were collected from the same infection, lineage admixture analyses, phylogenetic analyses and diversity analyses are produced and reported. For the phylogenetic analyses and the diversity analyses, a set of context samples is automatically fetched from GISAID. Thirdly, evolutionary analyses such as dN/dS analysis or the characterization of the nucleotide variants that appear in the studied samples are also carried out and reported. To validate the power to detect serially-sampled infections using VIPERA, we have used it with two validation datasets. The positive control dataset includes 30 sequences collected in Yale from the same patient (Chaguza C et al.,Cell Rep Med, 2023). The negative control dataset includes a mixture of 12 samples collected from one patient in Barcelona in 2020 with 3 other samples from another patient but collected in the same location and dates. Finally, we use VIPERA to carry out the whole intrapatient-evolution analysis with the 12 samples from the same patient that take part in the negative control., [Results] The positive and negative control datasets showed very different lineage composition, with more homogeneous lineage composition in the positive control. Phylogenetic three showed samples from positive control were monophyletic, while sequences from negative control were paraphyletic. Finally, the nucleotide diversity was significantly reduced in the studied sequences compared to the context ones in the positive control, as we expect for sequences derived from the same infection. On the contrary, the nucleotide diversity was not significantly reduced in the studied sequences compared to the context ones in the negative control. Our validation demonstrated that VIPERA has the power to detect serially-sampled infections. Additionally, we analyzed a case study using VIPERA. First we confirmed all sequences derived from a serially-sampled infection because lineage admixture was homogeneous, sequences were monophyletic and the nucleotide diversity was significantly lower than in the context sequences. Intrapatient-evolution analyses reported by VIPERA identified the appearance of mutations that are concerning due to their associated immune scape phenotype. We also detect positive selection along the infection using the dN/dS analysis., [Conclusions] VIPERA provides an aggregate of analysis for detecting whether there is a serially-sampled infection or not, including novel approaches such as genetic diversity and genetic distance at the population level approaches. It also provides a description of the within-host evolution observed in the studied samples.