Lipid nanoparticle library towards development next generation genomic medicines

Ionizable amino lipids are a major constituent of the lipid nanoparticles for delivering nucleic acid therapeutics (e.g., DLin-MC3-DMA in ONPATTRO , ALC-0315 in Comirnaty , SM-102 in Spikevax ). Scarcity of lipids that are suitable for cell therapy, vaccination, and gene therapies continue to be a problem in advancing many potential diagnostic/therapeutic/vaccine candidates to the clinic. Herein, we describe the development of novel ionizable lipids to be used as functional excipients for designing vehicles for nucleic acid therapeutics/vaccines in vivo or ex vivo use in cell therapy applications. We first studied the transfection efficiency (TE) of LNP-based mRNA formulations of these ionizable lipid candidates in primary human T cells and established a workflow for engineering of primary immune T cells. We then adapted this workflow towards bioengineering of CAR constructs to T cells towards non-viral CAR T therapy. Lipids were also tested in rodents for vaccine applications using self-amplifying RNA (saRNA) encoding various antigens. We have then evaluated various ionizable lipid candidates and their biodistribution along with the mRNA/DNA translation exploration using various LNP compositions. Further, using ionizable lipids from the library, we have shown gene editing of various targets in rodents. We believe that these studies will pave the path to the advancement in nucleic acid based therapeutics and vaccines, or cell gene therapy agents for early diagnosis and detection of cancer, and for targeted genomic medicines towards cancer treatment and diagnosis.

Detection and quantification of sars-cov-2 wastewater treatment plants from different cities in chile, towards to a permanent sentinel surveillance.

Background: The quantification of SARS-CoV-2 in wastewater is a tool that allows determining the trend of viral circulation in a particular geographical area. Aim(s): To quantify the SARS-CoV-2 virus in 15 wastewater treatment plants in different Chilean cities to establish a comparison with the variables of: I) Active cases per 100,000 inhabitants;ii) daily positivity (novel cases);and iii) phases of the lockdown strategy. Method(s): SARS-CoV-2 was concentrated from wastewater samples. To obtain the number of virus genomes per liter, absolute quantification was performed using qRT-PCR. Result(s): Between January and June 2021, 253 samples were processed, all of which were positive for the presence of the virus. Likewise, it will be determined that the rate of active cases per 100,000 inhabitants is the variable that best fits the trends obtained with the quantification of the viral load in wastewater. Conclusion(s): The quantification of SARS- CoV-2 in wastewater as a continuous strategy is an efficient tool to determine the trend of the viral circulation in a delimited geographical area and, combined with genomic surveillance, it can constitute an ideal sentinel surveillance alert on future outbreaks.Copyright © 2022, Sociedad Chilena de Infectologia. All rights reserved.

Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network.

Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network's technical capacity. QCA full panel results showed a lower hit rate for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain.

SARS-CoV-2 Co-Infections and Recombinations Identified by Long-Read Single-Molecule Real-Time Sequencing.

Co-infection with at least 2 strains of virus is the prerequisite for recombination, one of the means of genetic diversification. Little is known about the prevalence of these events in SARS-CoV-2, partly because it is difficult to detect them. We used long-read PacBio single-molecule real-time (SMRT) sequencing technology to sequence whole genomes and targeted regions for haplotyping. We identified 17 co-infections with SARS-CoV-2 strains belonging to different clades in 6829 samples sequenced between January and October, 2022 (prevalence 0.25%). There were 3 Delta/Omicron co-infections and 14 Omicron/Omicron co-infections (4 cases of 21K/21L, 1 case of 21L/22A, 2 cases of 21L/22B, 4 cases of 22A/22B, 2 cases of 22B/22C and 1 case of 22B/22E). Four of these patients (24%) also harbored recombinant minor haplotypes, including one with a recombinant virus that was selected in the viral quasispecies over the course of his chronic infection. While co-infections remain rare among SARS-CoV-2-infected individuals, long-read SMRT sequencing is a useful tool for detecting them as well as recombinant events, providing the basis for assessing their clinical impact, and a precise indicator of epidemic evolution. IMPORTANCE SARS-CoV-2 variants have been responsible for the successive waves of infection over the 3 years of pandemic. While co-infection followed by recombination is one driver of virus evolution, there have been few reports of co-infections, mainly between Delta and Omicron variants or between the first 2 Omicron variants 21K_BA.1 and 21L_BA.2. The 17 co-infections we detected during 2022 included cases with the recent clades of Omicron 22A, 22B, 22C, and 22E; 24% harbored recombinant variants. This study shows that long-read SMRT sequencing is well suited to SARS-CoV-2 genomic surveillance.

Emergence, spread and characterisation of the SARS-CoV-2 variant B.1.640 circulating in France, October 2021 to February 2022.

BackgroundSuccessive epidemic waves of COVID-19 illustrated the potential of SARS-CoV-2 variants to reshape the pandemic. Detecting and characterising emerging variants is essential to evaluate their public health impact and guide implementation of adapted control measures.AimTo describe the detection of emerging variant, B.1.640, in France through genomic surveillance and present investigations performed to inform public health decisions.MethodsIdentification and monitoring of SARS-CoV-2 variant B.1.640 was achieved through the French genomic surveillance system, producing 1,009 sequences. Additional investigation of 272 B.1.640-infected cases was performed between October 2021 and January 2022 using a standardised questionnaire and comparing with Omicron variant-infected cases.ResultsB.1.640 was identified in early October 2021 in a school cluster in Bretagne, later spreading throughout France. B.1.640 was detected at low levels at the end of SARS-CoV-2 Delta variant's dominance and progressively disappeared after the emergence of the Omicron (BA.1) variant. A high proportion of investigated B.1.640 cases were children aged under 14 (14%) and people over 60 (27%) years, because of large clusters in these age groups. B.1.640 cases reported previous SARS-CoV-2 infection (4%), anosmia (32%) and ageusia (34%), consistent with data on pre-Omicron SARS-CoV-2 variants. Eight percent of investigated B.1.640 cases were hospitalised, with an overrepresentation of individuals aged over 60 years and with risk factors.ConclusionEven though B.1.640 did not outcompete the Delta variant, its importation and continuous low-level spread raised concerns regarding its public health impact. The investigations informed public health decisions during the time that B.1.640 was circulating.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India.

BACKGROUND: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

Model design for nonparametric phylodynamic inference and applications to pathogen surveillance.

Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky. We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking.

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Application of CRISPR-Based Human and Bacterial Ribosomal RNA Depletion for SARS-CoV-2 Shotgun Metagenomic Sequencing.

OBJECTIVES: The aim of this study is to evaluate the effectiveness of a CRISPR-based human and bacterial ribosomal RNA (rRNA) depletion kit (JUMPCODE Genomics) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shotgun metagenomic sequencing in weakly positive respiratory samples. METHODS: Shotgun metagenomics was performed on 40 respiratory specimens collected from solid organ transplant patients and deceased intensive care unit patients at UCLA Medical Center in late 2020 to early 2021. Human and bacterial rRNA depletion was performed on remnant library pools prior to sequencing by Illumina MiSeq. Data quality was analyzed using Geneious Prime, whereas the identification of SARS-CoV-2 variants and lineages was determined by Pangolin. RESULTS: The average genome coverage of the rRNA-depleted respiratory specimens increased from 72.55% to 93.71% in overall samples and from 29.3% to 83.3% in 15 samples that failed to achieve sufficient genome coverage using the standard method. Moreover, rRNA depletion enhanced genome coverage to over 85% in 11 (73.3%) of 15 low viral load samples with cycle threshold values up to 35, resulting in the identification of genotypes. CONCLUSION: The CRISPR-based human and bacterial rRNA depletion enhanced the sensitivity of SARS-CoV-2 shotgun metagenomic sequencing, especially in low viral load samples.

Comparison of the Ct-values for genomic and subgenomic SARS-CoV-2 RNA reveals limited predictive value for the presence of replication competent virus.

SARS-CoV-2 is the causative agent of the acute respiratory disease COVID-19. In addition to the full length positive-sensed, single-stranded genomic RNA (gRNA), viral subgenomic RNAs (sgRNAs) that are required for expression of the 3' region of the genome are synthesized in virus-infected cells. However, whether these sgRNA-species might be used as a measure of active virus replication and to predict infectivity is still under debate. The commonly used methods to monitor and quantitate SARS-CoV-2 infections are based on RT-qPCR analysis and the detection of gRNA. The infectivity of a sample obtained from nasopharyngeal or throat swabs is associated with the viral load and inversely correlates with Ct-values, however, a cut-off value predicting the infectivity highly depends on the performance of the assay. Furthermore, gRNA derived Ct-values result from nucleic acid detection and do not necessarily correspond to active replicating virus. We established a multiplex RT-qPCR assay on the cobas 6800 omni utility channel concomitantly detecting SARS-CoV-2 gRNAOrf1a/b, sgRNAE,7a,N, and human RNaseP-mRNA used as human input control. We compared the target specific Ct-values with the viral culture frequency and performed ROC curve analysis to determine the assay sensitivity and specificity. We found no advantage in the prediction of viral culture when using sgRNA detection compared to gRNA only, since Ct-values for gRNA and sgRNA were highly correlated and gRNA offered a slightly more reliable predictive value. Single Ct-values alone only provide a very limited prediction for the presence of replication competent virus. Hence, careful consideration of the medical history including symptom onset has to be considered for risk stratification.

Optimal capacity sharing for global genomic surveillance.

Recent technological advances and substantial cost reductions have made the genomic surveillance of pathogens during pandemics feasible. Our paper focuses on full genome sequencing as a tool that can serve two goals: the estimation of variant prevalences, and the identification of new variants. Assuming that capacity constraints limit the number of samples that can be sequenced, we solve for the optimal distribution of these capacities among countries. Our results show that if the principal goal of sequencing is prevalence estimation, then the optimal capacity distribution is less than proportional to the weights (e.g., sizes) of countries. If, however, the main aim of sequencing is the detection of new variants, capacities should be allocated to countries or regions that have the most infections. Applying our results to the sequencing of SARS-CoV-2 in 2021, we provide a comparison between the observed and a suggested optimal capacity distribution worldwide and in the EU. We believe that following such quantifiable guidance will increase the efficiency of genomic surveillance for pandemics.

SARS-CoV-2 Delta variant genomic variation associated with breakthrough infection in Northern California: A retrospective cohort study.

BACKGROUND: The association between SARS-CoV-2 genomic variation and breakthrough infection is not well-defined among persons with Delta variant SARS-CoV-2 infection. METHODS: In a retrospective cohort we assessed whether individual non-lineage defining mutations and overall genomic variation (including low frequency alleles) were associated with breakthrough infection defined as SARS-CoV-2 infection after COVID-19 primary vaccine series. We identified all non-synonymous single nucleotide polymorphisms, insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. Using Poisson regression, we assessed the association with breakthrough infection for each individual mutation and a viral genomic risk score. RESULTS: Thirty-six mutations met our inclusion criteria. Among 12,744 persons infected with Delta variant SARS-CoV-2, 5,949 (47%) were vaccinated and 6,795 (53%) were unvaccinated. Viruses with a viral genomic risk score in the highest quintile were 9% more likely to be associated with breakthrough infection than viruses in the lowest quintile, but including the risk score improved overall predictive model performance (measured by c-statistic) by only +0.0006. CONCLUSIONS: Genomic variation within SARS-CoV-2 Delta variant was weakly associated with breakthrough infection, however several potential non-lineage defining mutations were identified that might contribute to immune evasion by SARS-CoV-2.

The importance of equally accessible genomic surveillance in the age of pandemics.

Genomic epidemiology is now a core component in investigating the spread of a disease during an outbreak and for future preparedness to tackle emerging zoonoses. During the last decades, several viral diseases arose and emphasized the importance of molecular epidemiology in tracking the dispersal route, supporting proper mitigation measures, and appropriate vaccine development. In this perspective article, we summarized what has been done so far in the genomic epidemiology field and what should be considered in the future. We traced back the methods and protocols employed over time for zoonotic disease response. Either to small outbreaks such as the severe acute respiratory syndrome (SARS) outbreak identified first in 2002 in Guangdong, China, or to a global pandemic like the one that we are experiencing now since 2019 when the severe acute respiratory syndrome 2 (SARS-CoV-2) virus emerged in Wuhan, China, following several pneumonia cases, and subsequently spread worldwide. We explored both the benefits and shortages encountered when relying on genomic epidemiology, and we clearly present the disadvantages of inequity in accessing these tools around the world, especially in countries with less developed economies. For effectively addressing future pandemics, it is crucial to work for better sequencing equity around the globe.

Development of PCR diagnostic method for Trichomonas foetus infection based on 18S rRNA.

To establish a PCR detection method for Trichomonas foetus, the primers were designed and synthesized according to the 18S rRNA gene sequence of T. foetus published by GenBank. The positive recombinant plasmid pUCm-T-TF18S of T. foetus was used as the template, and the genomic DNA of Giardia felis, Coccidia +e-lis, feline parvovirus and cDNA of feline coronavirus were used as the control for PCR detection to analyze the specificity of this method. The positive T. foetus recombinant plasmid was serial to 8 different concentrations with a gap of 10 folds, and PCR was performed to analyze the sensitivity of this method. The pUCm-T-TF18S plasmids stored at -20 " for 3, 6, 9 and 12 months were detected by PCR to analyze the stability of the method. Twenty cat fecal samples were tested using this established PCR assay and compared with those of microscopic examination. The results showed that the recombinant plasmid pUCm-T- TF18S gave specific bands after PCR amplification. The sequencing results showed that the length of the product sequence was 1 264 bp, and the BLAST sequence comparison analysis showed 99.53% sequence identity, which is consistent with that of T. foetus from cats (GenBank registration number M81842.1). The PCR method for detection of T. foetus had no cross-reactivities with C. felis, G. felis, feline coronavirus and feline parvovirus;the minimum detectable template concentration is 4.52 X 105 copies/xl;The target band of T. foetus DNA can still be detected after being stored in the refrigerator at -20 " for 12 months. This method detected 16 positive samples of T. foetus nucleic acid from 20 cat fecal samples, which is more accurate and sensitive than the results from traditional microscopy (13 samples). It is suggested that the PCR method for the detection of T. foetus is highly specific, sensitive and stable, and can be used for clinical detection and epidemiological investigation of T. foetus.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.

Phylodynamics of SARS-CoV-2 in France, Europe, and the world in 2020.

Although France was one of the most affected European countries by the COVID-19 pandemic in 2020, the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) movement within France, but also involving France in Europe and in the world, remain only partially characterized in this timeframe. Here, we analyzed GISAID deposited sequences from January 1 to December 31, 2020 (n = 638,706 sequences at the time of writing). To tackle the challenging number of sequences without the bias of analyzing a single subsample of sequences, we produced 100 subsamples of sequences and related phylogenetic trees from the whole dataset for different geographic scales (worldwide, European countries, and French administrative regions) and time periods (from January 1 to July 25, 2020, and from July 26 to December 31, 2020). We applied a maximum likelihood discrete trait phylogeographic method to date exchange events (i.e., a transition from one location to another one), to estimate the geographic spread of SARS-CoV-2 transmissions and lineages into, from and within France, Europe, and the world. The results unraveled two different patterns of exchange events between the first and second half of 2020. Throughout the year, Europe was systematically associated with most of the intercontinental exchanges. SARS-CoV-2 was mainly introduced into France from North America and Europe (mostly by Italy, Spain, the United Kingdom, Belgium, and Germany) during the first European epidemic wave. During the second wave, exchange events were limited to neighboring countries without strong intercontinental movement, but Russia widely exported the virus into Europe during the summer of 2020. France mostly exported B.1 and B.1.160 lineages, respectively, during the first and second European epidemic waves. At the level of French administrative regions, the Paris area was the main exporter during the first wave. But, for the second epidemic wave, it equally contributed to virus spread with Lyon area, the second most populated urban area after Paris in France. The main circulating lineages were similarly distributed among the French regions. To conclude, by enabling the inclusion of tens of thousands of viral sequences, this original phylodynamic method enabled us to robustly describe SARS-CoV-2 geographic spread through France, Europe, and worldwide in 2020.

Evaluation of Rapid Antigen Test as a Marker of SARS-CoV-2 Infectivity.

Background Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 continues to spread globally. Reverse transcriptase polymerase chain reaction (RT-PCR), which is considered the gold standard for diagnosis, does not always indicate contagiousness. This study was planned to evaluate the performance of the rapid antigen test (RAT) with the duration of symptoms and the usefulness of these tests in determining the infectivity of patients by performing sub-genomic RT-PCR. Methodology This prospective, observational study was designed to compare the diagnostic value of the COVID-19 RAT (SD Biosensor, Korea) with COVID-19 RT-PCR (Thermo Fisher, USA) by serial testing of patients. To evaluate the infectivity of the virus, sub-genomic RT-PCR was performed on previous RAT and RT-PCR-positive samples. Results Of 200 patients, 102 were positive on both RT-PCR and RAT, with 87 patients serially followed and tested. The sensitivity and specificity of RAT were 92.73% and 93.33%, respectively, in symptomatic patients. The mean duration of RAT positivity was 9.1 days, and the mean duration of RT-PCR positivity was 12.6 days. Sub-genomic RT-PCR test was performed on samples that were reported to be positive by RAT, and 73/87 (83.9%) patients were found to be positive. RAT was positive in symptomatic patients whose duration of illness was less than 10 days or those with a cycle threshold value below 32. Conclusions Thus, RAT can be used as the marker of infectivity of SARS-CoV-2 in symptomatic patients, especially in healthcare workers.

Evaluation of low-cost SARS-CoV-2 RNA purification methods for viral quantification by RT-qPCR and next-generation sequencing analysis: Implications for wider wastewater-based epidemiology adoption.

Based Epidemiology (WBE) consists of quantifying biomarkers in sewerage systems to derive real-time information on the health and/or lifestyle of the contributing population. WBE usefulness was vastly demonstrated in the context of the COVID-19 pandemic. Many methods for SARS-CoV-2 RNA determination in wastewater were devised, which vary in cost, infrastructure requirements and sensitivity. For most developing countries, implementing WBE for viral outbreaks, such as that of SARS-CoV-2, proved challenging due to budget, reagent availability and infrastructure constraints. In this study, we assessed low-cost methods for SARS-CoV-2 RNA quantification by RT-qPCR, and performed variant identification by NGS in wastewater samples. Results showed that the effect of adjusting pH to 4 and/or adding MgCl2 (25 mM) was negligible when using the adsorption-elution method, as well as basal physicochemical parameters in the sample. In addition, results supported the standardized use of linear rather than plasmid DNA for a more accurate viral RT-qPCR estimation. The modified TRIzol-based purification method in this study yielded comparable RT-qPCR estimation to a column-based approach, but provided better NGS results, suggesting that column-based purification for viral analysis should be revised. Overall, this work provides evaluation of a robust, sensitive and cost-effective method for SARS-CoV-2 RNA analysis that could be implemented for other viruses, for a wider WEB adoption.

Molecular Characterization of the Convergent Carbapenem-Resistant and Hypervirulent Klebsiella pneumoniae Strain K1-ST23, Collected in Chile during the COVID-19 Pandemic.

The aim of this study was to investigate the genomic features of a carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKp) isolate (K-2157) collected in Chile. Antibiotic susceptibility was determined using the disk diffusion and broth microdilution methods. Whole-genome sequencing (WGS) and hybrid assembly were performed, using data generated on the Illumina and Nanopore platforms. The mucoid phenotype was analyzed using both the string test and sedimentation profile. The genomic features of K-2157 (e.g., sequence type, K locus, and mobile genetic elements) were retrieved using different bioinformatic tools. Strain K-2157 exhibited resistance to carbapenems and was identified as a high-risk virulent clone belonging to capsular serotype K1 and sequence type 23 (ST23). Strikingly, K-2157 displayed a resistome composed of ß-lactam resistance genes (blaSHV-190, blaTEM-1, blaOXA-9, and blaKPC-2), the fosfomycin resistance gene fosA, and the fluoroquinolones resistance genes oqxA and oqxB. Moreover, several genes involved in siderophore biosynthesis (ybt, iro, and iuc), bacteriocins (clb), and capsule hyperproduction (plasmid-borne rmpA [prmpA] and prmpA2) were found, which is congruent with the positive string test displayed by K-2157. In addition, K-2157 harbored two plasmids: one of 113,644 bp (KPC+) and another of 230,602 bp, containing virulence genes, in addition to an integrative and conjugative element (ICE) embedded on its chromosome, revealing that the presence of these mobile genetic elements mediates the convergence between virulence and antibiotic resistance. Our report is the first genomic characterization of a hypervirulent and highly resistant K. pneumoniae isolate in Chile, which was collected during the coronavirus disease 2019 (COVID-19) pandemic. Due to their global dissemination and public health impact, genomic surveillance of the spread of convergent high-risk K1-ST23 K. pneumoniae clones should be highly prioritized. IMPORTANCE Klebsiella pneumoniae is a resistant pathogen involved primarily in hospital-acquired infections. This pathogen is characterized by its notorious resistance to last-line antibiotics, such as carbapenems. Moreover, hypervirulent K. pneumoniae (hvKp) isolates, first identified in Southeast Asia, have emerged globally and are able to cause infections in healthy people. Alarmingly, isolates displaying a convergence phenotype of carbapenem resistance and hypervirulence have been detected in several countries, representing a serious threat to public health. In this work, we analyzed the genomic characteristics of a carbapenem-resistant hvKp isolate recovered in 2022 from a patient with COVID-19 in Chile, representing the first analysis of this type in the country. Our results will provide a baseline for the study of these isolates in Chile, which will support the adoption of local measures aimed at controlling their dissemination.

Classical and Next-Generation Vaccine Platforms to SARS-CoV-2: Biotechnological Strategies and Genomic Variants.

Several coronaviruses (CoVs) have been identified as human pathogens, including the α-CoVs strains HCoV-229E and HCoV-NL63 and the ß-CoVs strains HCoV-HKU1 and HCoV-OC43. SARS-CoV, MERS-CoV, and SARS-CoV-2 are also classified as ß-coronavirus. New SARS-CoV-2 spike genomic variants are responsible for human-to-human and interspecies transmissibility, consequences of adaptations of strains from animals to humans. The receptor-binding domain (RBD) of SARS-CoV-2 binds to receptor ACE2 in humans and animal species with high affinity, suggesting there have been adaptive genomic variants. New genomic variants including the incorporation, replacement, or deletion of the amino acids at a variety of positions in the S protein have been documented and are associated with the emergence of new strains adapted to different hosts. Interactions between mutated residues and RBD have been demonstrated by structural modelling of variants including D614G, B.1.1.7, B1.351, P.1, P2; other genomic variants allow escape from antibodies generated by vaccines. Epidemiological and molecular tools are being used for real-time tracking of pathogen evolution and particularly new SARS-CoV-2 variants. COVID-19 vaccines obtained from classical and next-generation vaccine production platforms have entered clinicals trials. Biotechnology strategies of the first generation (attenuated and inactivated virus-CoronaVac, CoVaxin; BBIBP-CorV), second generation (replicating-incompetent vector vaccines-ChAdOx-1; Ad5-nCoV; Sputnik V; JNJ-78436735 vaccine-replicating-competent vector, protein subunits, virus-like particles-NVX-CoV2373 vaccine), and third generation (nucleic-acid vaccines-INO-4800 (DNA); mRNA-1273 and BNT 162b (RNA vaccines) have been used. Additionally, dendritic cells (LV-SMENP-DC) and artificial antigen-presenting (aAPC) cells modified with lentiviral vector have also been developed to inhibit viral activity. Recombinant vaccines against COVID-19 are continuously being applied, and new clinical trials have been tested by interchangeability studies of viral vaccines developed by classical and next-generation platforms.

Entropy Based Clustering of Viral Sequences

Clustering viral sequences allows us to characterize the composition and structure of intrahost and interhost viral populations, which play a crucial role in disease progression and epidemic spread. In this paper we propose and validate a new entropy based method for clustering aligned viral sequences considered as categorical data. The method finds a homogeneous clustering by minimizing information entropy rather than distance between sequences in the same cluster. We have applied our entropy based clustering method to SARS-CoV-2 viral sequencing data. We report the information content extracted from the sequences by entropy based clustering. Our method converges to similar minimum-entropy clusterings across different runs and limited permutations of data. We also show that a parallelized version of our tool is scalable to very large SARS-CoV-2 datasets.