Genomic surveillance as a scalable framework for precision phage therapy against antibiotic-resistant pathogens.

Phage therapy is gaining increasing interest in the fight against critically antibiotic-resistant nosocomial pathogens. However, the narrow host range of bacteriophages hampers the development of broadly effective phage therapeutics and demands precision approaches. Here, we combine large-scale phylogeographic analysis with high-throughput phage typing to guide the development of precision phage cocktails targeting carbapenem-resistant Acinetobacter baumannii, a top-priority pathogen. Our analysis reveals that a few strain types dominate infections in each world region, with their geographical distribution remaining stable within 6 years. As we demonstrate in Eastern Europe, this spatiotemporal distribution enables preemptive preparation of region-specific phage collections that target most local infections. Finally, we showcase the efficacy of phage cocktails against prevalent strain types using in vitro and animal infection models. Ultimately, genomic surveillance identifies patients benefiting from the same phages across geographical scales, thus providing a scalable framework for precision phage therapy.

Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2,500 COVID-19 cases associated with this variant have been detected in the United States (US) since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid- to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification.

The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task. We propose a method of estimating fitness gains directly from nucleotide information generated by genomic surveillance, without a priori assigning isolates to lineages from phylogenies, based solely on the abundance of single nucleotide polymorphisms (SNPs). The method is based on mapping changes in the genetic population structure over time. Changes in the abundance of SNPs associated with periods of increasing fitness allow for the unbiased discovery of new variants, thereby obviating a deliberate lineage assignment and phylogenetic inference. We conclude that the method provides a fast and reliable way to estimate fitness advantages of variants without the need for a priori assigning isolates to lineages.

Hound: a novel tool for automated mapping of genotype to phenotype in bacterial genomes assembled de novo.

Increasing evidence suggests that microbial species have a strong within species genetic heterogeneity. This can be problematic for the analysis of prokaryote genomes, which commonly relies on a reference genome to guide the assembly process. Differences between reference and sample genomes will therefore introduce errors in final assembly, jeopardizing the detection from structural variations to point mutations-critical for genomic surveillance of antibiotic resistance. Here we present Hound, a pipeline that integrates publicly available tools to assemble prokaryote genomes de novo, detect user-given genes by similarity to report mutations found in the coding sequence, promoter, as well as relative gene copy number within the assembly. Importantly, Hound can use the query sequence as a guide to merge contigs, and reconstruct genes that were fragmented by the assembler. To showcase Hound, we screened through 5032 bacterial whole-genome sequences isolated from farmed animals and human infections, using the amino acid sequence encoded by blaTEM-1, to detect and predict resistance to amoxicillin/clavulanate which is driven by over-expression of this gene. We believe this tool can facilitate the analysis of prokaryote species that currently lack a reference genome, and can be scaled either up to build automated systems for genomic surveillance or down to integrate into antibiotic susceptibility point-of-care diagnostics.

Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders.

The COVID-19 pandemic is marked by the successive emergence of new SARS-CoV-2 variants, lineages, and sublineages that outcompete earlier strains, largely due to factors like increased transmissibility and immune escape. We propose DeepAutoCoV, an unsupervised deep learning anomaly detection system, to predict future dominant lineages (FDLs). We define FDLs as viral (sub)lineages that will constitute >10% of all the viral sequences added to the GISAID, a public database supporting viral genetic sequence sharing, in a given week. DeepAutoCoV is trained and validated by assembling global and country-specific data sets from over 16 million Spike protein sequences sampled over a period of ~4 years. DeepAutoCoV successfully flags FDLs at very low frequencies (0.01%-3%), with median lead times of 4-17 weeks, and predicts FDLs between ~5 and ~25 times better than a baseline approach. For example, the B.1.617.2 vaccine reference strain was flagged as FDL when its frequency was only 0.01%, more than a year before it was considered for an updated COVID-19 vaccine. Furthermore, DeepAutoCoV outputs interpretable results by pinpointing specific mutations potentially linked to increased fitness and may provide significant insights for the optimization of public health 'pre-emptive' intervention strategies.

Motifs in SARS-CoV-2 evolution.

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of coevolving sites in the alignment (motifs), identified via coevolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the coevolutionary coupling of pairs and manifest as coevolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness, and robustness. Lastly, we study how well each lineage is classified by such a system.

Bacterial Genomics for National Antimicrobial Resistance Surveillance in Cambodia.

BACKGROUND: Antimicrobial resistance (AMR) surveillance in low- and middle-income countries (LMICs) often relies on poorly resourced laboratory processes. Centralized sequencing was combined with cloud-based, open-source bioinformatics solutions for national AMR surveillance in Cambodia. METHODS: Blood cultures growing gram-negative bacteria were collected at six Cambodian hospitals (January 2021 - October 2022). Isolates were obtained from pure plate growth and shotgun DNA sequencing performed in-country. Using public nucleotide and protein databases, reads were aligned for pathogen identification and AMR gene characterization. Multilocus sequence typing was performed on whole genome assemblies and haplotype clusters compared against published genomes. FINDINGS: Genes associated with acquired resistance to fluoroquinolones were identified in 59%, TMP/SMX in 45%, and aminoglycosides in 52% of 715 isolates. Extended-spectrum beta-lactamase encoding genes were identified in 34% isolates, most commonly blaCTX-M-15, blaCTX-M-27, and blaCTX-M-55 in E. coli sequence types 131 and 1193. Carbapenemase genes were identified in 12% isolates, most commonly blaOXA-23, blaNDM-1, blaOXA-58 and blaOXA-66 in Acinetobacter species. Phylogenetic analysis revealed clonal strains of A. baumannii, representing suspected nosocomial outbreaks, and genetic clusters of quinolone-resistant typhoidal Salmonella and ESBL E. coli cases suggesting community transmission. INTERPRETATION: With accessible sequencing platforms and bioinformatics solutions, bacterial genomics can supplement AMR surveillance in LMICs. FUNDING: Research was supported by the National Institute of Allergy and Infectious Diseases and the Bill and Melinda Gates Foundation [OPP1211806].

Reduced Likelihood of Hospitalization with the JN.1 or HV.1 SARS-CoV-2 Variants Compared to the EG.5 Variant.

Within a multi-state viral genomic surveillance program, we evaluated whether proportions of SARS-CoV-2 infections attributed to the JN.1 variant and to XBB-lineage variants (including HV.1 and EG.5) differed between inpatient and outpatient care settings during periods of cocirculation. Both JN.1 and HV.1 were less likely than EG.5 to account for infections among inpatients versus outpatients (aOR=0.60 [95% CI: 0.43-0.84; p=0.003] and aOR=0.35 [95% CI: 0.21-0.58; p<0.001], respectively). JN.1 and HV.1 variants may be associated with a lower risk of severe illness. The severity of COVID-19 may have attenuated as predominant circulating SARS-CoV-2 lineages shifted from EG.5 to HV.1 to JN.1.

Genomic diversity and antimicrobial susceptibility of invasive Neisseria meningitidis in South Africa, 2016-2021.

BACKGROUND: Invasive meningococcal isolates in South Africa have in previous years (<2008) been characterized by serogroup B, C, W and Y lineages over time, with penicillin intermediate resistance (peni) at 6%. We describe the population structure and genomic markers of peni among invasive meningococcal isolates in South Africa, 2016-2021. METHODS: Meningococcal isolates were collected through national, laboratory-based invasive meningococcal disease (IMD) surveillance. Phenotypic antimicrobial susceptibility testing and whole-genome sequencing were performed, and the mechanism of reduced penicillin susceptibility was assessed in silico. RESULTS: Of 585 IMD cases reported during the study period, culture and PCR-based capsular group was determined for 477/585 (82%); and 241/477 (51%) were sequenced. Predominant serogroups included NmB (210/477; 44%), NmW (116/477; 24%), NmY (96/477; 20%) and NmC (48/477; 10%). Predominant clonal complexes (CC) were CC41/44 in NmB (27/113; 24%), CC11 in NmW (46/56; 82%), CC167 in NmY (23/44; 53%), and CC865 in NmC (9/24; 38%). Peni was detected in 16% (42/262) of isolates, and was due to the presence of a penA mosaic, with the majority harboring penA7, penA9 or penA14. CONCLUSION: IMD lineages circulating in South Africa were consistent with those circulating prior to 2008, however peni was higher than previously reported, and occurred in a variety of lineages.

Dengue virus surveillance in Nepal yields the first on-site whole genome sequences of isolates from the 2022 outbreak.

BACKGROUND: The 4 serotypes of dengue virus (DENV1-4) can each cause potentially deadly dengue disease, and are spreading globally from tropical and subtropical areas to more temperate ones. Nepal provides a microcosm of this global phenomenon, having met each of these grim benchmarks. To better understand DENV transmission dynamics and spread into new areas, we chose to study dengue in Nepal and, in so doing, to build the onsite infrastructure needed to manage future, larger studies. METHODS AND RESULTS: During the 2022 dengue season, we enrolled 384 patients presenting at a hospital in Kathmandu with dengue-like symptoms; 79% of the study participants had active or recent DENV infection (NS1 antigen and IgM). To identify circulating serotypes, we screened serum from 50 of the NS1+ participants by RT-PCR and identified DENV1, 2, and 3 - with DENV1 and 3 codominant. We also performed whole-genome sequencing of DENV, for the first time in Nepal, using our new on-site capacity. Sequencing analysis demonstrated the DENV1 and 3 genomes clustered with sequences reported from India in 2019, and the DENV2 genome clustered with a sequence reported from China in 2018. CONCLUSION: These findings highlight DENV's geographic expansion from neighboring countries, identify China and India as the likely origin of the 2022 DENV cases in Nepal, and demonstrate the feasibility of building onsite capacity for more rapid genomic surveillance of circulating DENV. These ongoing efforts promise to protect populations in Nepal and beyond by informing the development and deployment of DENV drugs and vaccines in real time.

DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus.

BACKGROUND: The increasing burden of dengue virus on public health due to more explosive and frequent outbreaks highlights the need for improved surveillance and control. Genomic surveillance of dengue virus not only provides important insights into the emergence and spread of genetically diverse serotypes and genotypes, but it is also critical to monitor the effectiveness of newly implemented control strategies. Here, we present DengueSeq, an amplicon sequencing protocol, which enables whole-genome sequencing of all four dengue virus serotypes. RESULTS: We developed primer schemes for the four dengue virus serotypes, which can be combined into a pan-serotype approach. We validated both approaches using genetically diverse virus stocks and clinical specimens that contained a range of virus copies. High genome coverage (>95%) was achieved for all genotypes, except DENV2 (genotype VI) and DENV 4 (genotype IV) sylvatics, with similar performance of the serotype-specific and pan-serotype approaches. The limit of detection to reach 70% coverage was 10-100 RNA copies/µL for all four serotypes, which is similar to other commonly used primer schemes. DengueSeq facilitates the sequencing of samples without known serotypes, allows the detection of multiple serotypes in the same sample, and can be used with a variety of library prep kits and sequencing instruments. CONCLUSIONS: DengueSeq was systematically evaluated with virus stocks and clinical specimens spanning the genetic diversity within each of the four dengue virus serotypes. The primer schemes can be plugged into existing amplicon sequencing workflows to facilitate the global need for expanded dengue virus genomic surveillance.

Reemergence of Clade IIb-Associated Mpox, Germany, July-December 2023.

In July 2023, clade IIb-associated mpox reemerged in Germany at low levels, mainly affecting men who have sex with men. We report a representative case and phylogeny of available genome sequences. Our findings underscore the need for standardized surveillance and indication-based vaccination to limit transmission and help prevent endemicity.

Phylogenomics of Dengue Virus Isolates Causing Dengue Outbreak, São Tomé and Príncipe, 2022.

We determined that the dengue outbreak in São Tomé and Príncipe during 2022 was caused by dengue virus serotype 3 genotype III. Phylogenomic analyses showed that the outbreak strain was closely related to the newly identified GIII-American-II lineage and that the virus probably was introduced from the Americas.

Evidence of Lineage 1 and 3 West Nile Virus in Person with Neuroinvasive Disease, Nebraska, USA, 2023.

West Nile virus (WNV) is the most common cause of human arboviral disease in the contiguous United States, where only lineage 1 (L1) WNV had been found. In 2023, an immunocompetent patient was hospitalized in Nebraska with West Nile neuroinvasive disease and multisystem organ failure. Testing at the Centers for Disease Control and Prevention indicated an unusually high viral load and acute antibody response. Upon sequencing of serum and cerebrospinal fluid, we detected lineage 3 (L3) and L1 WNV genomes. L3 WNV had previously only been found in Central Europe in mosquitoes. The identification of L3 WNV in the United States and the observed clinical and laboratory features raise questions about the potential effect of L3 WNV on the transmission dynamics and pathogenicity of WNV infections. Determining the distribution and prevalence of L3 WNV in the United States and any public health and clinical implications is critical.

Novel Avian Influenza A(H5N6) Virus in Wild Birds, South Korea, 2023.

We isolated novel reassortant avian influenza A(H5N6) viruses containing genes from clade 2.3.4.4b H5N1 virus and low pathogenicity avian influenza viruses in carcasses of whooper swans and bean geese in South Korea during December 2023. Neuraminidase gene was from a clade 2.3.4.4b H5N6 virus infecting poultry and humans in China.

Evolution and Spread of Highly Pathogenic Avian Influenza A(H5N1) Clade 2.3.4.4b Virus in Wild Birds, South Korea, 2022-2023.

During October 2022-March 2023, highly pathogenic avian influenza (HPAI) A(H5N1) clade 2.3.4.4b virus caused outbreaks in South Korea, including 174 cases in wild birds. To understand the origin and role of wild birds in the evolution and spread of HPAI viruses, we sequenced 113 HPAI isolates from wild birds and performed phylogenetic analysis. We identified 16 different genotypes, indicating extensive genetic reassortment with viruses in wild birds. Phylodynamic analysis showed that the viruses were most likely introduced to the southern Gyeonggi-do/northern Chungcheongnam-do area through whooper swans (Cygnus cygnus) and spread southward. Cross-species transmission occurred between various wild bird species, including waterfowl and raptors, resulting in the persistence of HPAI in wild bird populations and further geographic spread as these birds migrated throughout South Korea. Enhanced genomic surveillance was an integral part of the HPAI outbreak response, aiding in timely understanding of the origin, evolution, and spread of the virus.

Detection of cefiderocol and aztreonam/avibactam resistance in epidemic Escherichia coli ST-361 carrying blaNDM-5 and blaKPC-3 from foreign fighters evacuated from Ukraine.

Genomic surveillance detected clonal Escherichia coli sequence type-361 isolates carrying blaNDM-5, blaKPC-3, blaCTX-M-15, and rmtB1 from a patient in Ukraine and four wounded foreign soldiers evacuated to Germany. Isolates were non-susceptible to carbapenems, aminoglycosides, and cefiderocol and aztreonam/avibactam due to a PBP3 YRIN insertion and the blaCMY-145 AmpC ß-lactamase. Coordinated surveillance efforts across civilian, military, and veteran healthcare systems are essential to prevent further spread as international volunteers return home after medical evacuation from Ukraine.

A multicenter study on accuracy and reproducibility of nanopore sequencing-based genotyping of bacterial pathogens.

Nanopore sequencing has shown the potential to democratize genomic pathogen surveillance due to its ease of use and low entry cost. However, recent genotyping studies showed discrepant results compared to gold-standard short-read sequencing. Furthermore, although essential for widespread application, the reproducibility of nanopore-only genotyping remains largely unresolved. In our multicenter performance study involving five laboratories, four public health-relevant bacterial species were sequenced with the latest R10.4.1 flow cells and V14 chemistry. Core genome MLST analysis of over 500 data sets revealed highly strain-specific typing errors in all species in each laboratory. Investigation of the methylation-related errors revealed consistent DNA motifs at error-prone sites across participants at read level. Depending on the frequency of incorrect target reads, this either leads to correct or incorrect typing, whereby only minimal frequency deviations can randomly determine the final result. PCR preamplification, recent basecalling model updates and an optimized polishing strategy notably diminished the non-reproducible typing. Our study highlights the potential for new errors to appear with each newly sequenced strain and lays the foundation for computational approaches to reduce such typing errors. In conclusion, our multicenter study shows the necessity for a new validation concept for nanopore sequencing-based, standardized bacterial typing, where single nucleotide accuracy is critical.

Early Genomic Surveillance and Phylogeographic Analysis of Getah Virus, a Reemerging Arbovirus, in Livestock in China.

Getah virus (GETV) mainly causes disease in livestock and may pose an epidemic risk due to its expanding host range and the potential of long-distance dispersal through animal trade. Here, we used metagenomic next-generation sequencing (mNGS) to identify GETV as the pathogen responsible for reemerging swine disease in China and subsequently estimated key epidemiological parameters using phylodynamic and spatially-explicit phylogeographic approaches. The GETV isolates were able to replicate in a variety of cell lines, including human cells, and showed high pathogenicity in a mouse model, suggesting the potential for more mammal hosts. We obtained 16 complete genomes and 79 E2 gene sequences from viral strains collected in China from 2016 to 2021 through large-scale surveillance among livestock, pets, and mosquitoes. Our phylogenetic analysis revealed that three major GETV lineages are responsible for the current epidemic in livestock in China. We identified three potential positively selected sites and mutations of interest in E2, which may impact the transmissibility and pathogenicity of the virus. Phylodynamic inference of the GETV demographic dynamics identified an association between livestock meat consumption and the evolution of viral genetic diversity. Finally, phylogeographic reconstruction of GETV dispersal indicated that the sampled lineages have preferentially circulated within areas associated with relatively higher mean annual temperature and pig population density. Our results highlight the importance of continuous surveillance of GETV among livestock in southern Chinese regions associated with relatively high temperatures. IMPORTANCE Although livestock is known to be the primary reservoir of Getah virus (GETV) in Asian countries, where identification is largely based on serology, the evolutionary history and spatial epidemiology of GETV in these regions remain largely unknown. Through our sequencing efforts, we provided robust support for lineage delineation of GETV and identified three major lineages that are responsible for the current epidemic in livestock in China. We further analyzed genomic and epidemiological data to reconstruct the recent demographic and dispersal history of GETV in domestic animals in China and to explore the impact of environmental factors on its genetic diversity and its diffusion. Notably, except for livestock meat consumption, other pig-related factors such as the evolution of live pig transport and pork production do not show a significant association with the evolution of viral genetic diversity, pointing out that further studies should investigate the potential contribution of other host species to the GETV outbreak. Our analysis of GETV demonstrates the need for wider animal species surveillance and provides a baseline for future studies of the molecular epidemiology and early warning of emerging arboviruses in China.

Developing a next level integrated genomic surveillance: Advances in the molecular epidemiology of HIV in Germany.

Advances in the molecular epidemiological studies of the Human Immunodeficiency Virus (HIV) at the Robert Koch Institute (RKI) by laboratory and bioinformatic automation should allow the processing of larger numbers of samples and more comprehensive and faster data analysis in order to provide a higher resolution of the current HIV infection situation in near real-time and a better understanding of the dynamic of the German HIV epidemic. The early detection of the emergence and transmission of new HIV variants is important for the adaption of diagnostics and treatment guidelines. Likewise, the molecular epidemiological detection and characterization of spatially limited HIV outbreaks or rapidly growing sub-epidemics is of great importance in order to interrupt the transmission pathways by regionally adapting prevention strategies. These aims are becoming even more important in the context of the SARS-CoV2 pandemic and the Ukrainian refugee movement, which both have effects on the German HIV epidemic that should be monitored to identify starting points for targeted public health measures in a timely manner. To this end, a next level integrated genomic surveillance of HIV is to be established.