Highly pathogenic avian influenza A(H5N1) virus has caused a multistate outbreak among US dairy cattle, spreading across 16 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk samples from 20 states for methods development, we found that H5N1 virus concentrations by digital PCR strongly correlated with quantitative PCR cycle threshold values; digital PCR exhibited greater sensitivity. Metagenomic sequencing after hybrid selection was best for higher concentration samples, whereas amplicon sequencing performed best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to perform monthly testing of bulk milk samples from all dairy cattle farms in Massachusetts, USA, which remain negative to date. The methods, workflow, and recommendations described provide a framework for others aiming to conduct H5N1 surveillance efforts.

Targeted enrichment via capture probes, also known as baits, is a promising complementary procedure for next-generation sequencing methods. This technique uses short biotinylated oligonucleotide probes that hybridize with complementary genetic material in a sample. Following hybridization, the target fragments can be easily isolated and processed with minimal contamination from irrelevant material. Designing an efficient set of baits for a set of target sequences, however, is an NP-hard problem.

We develop a novel heuristic algorithm that leverages the similarities between the characteristics of the Minimum Bait Cover and the Closest String problems to reduce the number of baits to cover a given target sequence. Our results on real and synthetic datasets demonstrate that our algorithm, OLTA produces fewest baits for nearly all experimental settings and datasets. On average, it produces 6% and 11% fewer baits than the next best state-of-the-art methods for two major real datasets, AIV and MEGARES. Also, its bait set has the highest utilization and the minimum redundancy.

Our algorithm is available at github.com/FuelTheBurn/OLTA-Optimizing-bait-seLection-for-TArgeted-sequencing. Test data and other software are archived at doi.org/10.5281/zenodo.15086636.

Hybrid capture-based target enrichment prior to sequencing has been shown to significantly improve the sensitivity of detection for genetic regions of interest. In the context of One Health relevant pathogen detection, we present a hybrid capture-based sequencing method that employs an optimized probe set consisting of 149,990 probes, targeting 663 viruses associated with humans and animals. The detection performance was initially assessed using viral reference materials in a background of human nucleic acids. Compared to standard metagenomic next-generation sequencing (mNGS), our method achieved substantial read enrichment, with increases ranging from 143- to 1126-fold, and enhanced detection sensitivity by lowering the limit of detection (LoD) from 103-104 copies to as few as 10 copies based on whole genomes. This method was further validated using infectious samples from both animals and humans, including bovine rectal swabs and throat swabs from SARS-CoV-2 patients across various concentration gradients. In both sample types, our hybrid capture-based sequencing method exhibited heightened sensitivity, increased viral genome coverage, and more comprehensive viral identification and characterization. Our method bridges a critical divide between diagnostic detection and genomic surveillance. These findings illustrate that our hybrid capture-based sequencing method can effectively enhance sensitivity to as few as 10 viral copies and genome coverage to >99% in medium-to-high viral loads. This dual capability is particularly impactful for emerging pathogens like SARS-CoV-2, where early detection and genomic characterization are equally vital, thereby addressing the limitations of metagenomics in the surveillance of emerging infectious diseases in complex samples.

Recent advances in cell culturing and DNA sequencing have dramatically altered the field of human microbiome research. Three-dimensional (3D) cell culture is an important tool in cell biology, in cancer research, and for studying host-microbe interactions, as it mimics the in vivo characteristics of the host environment in an in vitro system, providing reliable and reproducible models. This work provides an overview of the main 3D culture techniques applied to study interactions between host cells and pathogenic microorganisms, how these systems can be integrated with high-throughput molecular methods, and how multi-species model systems may pave the way forward to pinpoint interactions among host, beneficial microbes and pathogens.

SUMMARYPublic health microbiology focuses on microorganisms and infectious agents that impact human health. For years, this field has relied on culture or molecular methods to investigate complex samples of public health importance. However, with the increase in accuracy and decrease in sequencing cost over the last decade, there has been a transition to the use of next-generation sequencing in public health microbiology. Nevertheless, many available sequencing methods (e.g., shotgun metagenomics and amplicon sequencing) do not work well in complex sample types, require deep sequencing, or have inherent biases associated with them. Hybridization bait capture, also known as target enrichment, brings in solutions for such limitations. It is an increasingly popular technique to simultaneously characterize many thousands of genetic elements while reducing the amount of sequencing needed (thereby reducing the sequencing costs). Here, we summarize the concept of hybridization bait capture for public health, reviewing a total of 35 bait sets designed in six key topic areas for public health microbiology [i.e., antimicrobial resistance (AMR), bacteria, fungi, parasites, vectors, and viruses], and compare hybridization bait capture to previously relied upon methods. Furthermore, we provide an in-depth comparison of the three most popular bait sets designed for AMR by evaluating each of them against three major AMR databases: Comprehensive Antibiotic Resistance Database, Microbial Ecology Group Antimicrobial Resistance Database, and Pathogenicity Island Database. Thus, this article provides a review of hybridization bait capture for public health microbiologists.

Highly Pathogenic Avian Influenza strain H5N1 has caused a multi-state outbreak among US dairy cattle, spreading across 15 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk from 20 states for methods development, we found that H5N1 concentrations by digital PCR strongly correlated with qPCR cycle threshold (Ct) values, with dPCR exhibiting greater sensitivity. We also found that metagenomic sequencing after hybrid selection was best for higher concentration samples while amplicon sequencing performs best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to test bulk milk samples monthly from all cattle dairy farms within Massachusetts, which remain negative to date. The methods, workflow, and recommendations described here provide a framework for others aiming to conduct H5N1 surveillance efforts.

We investigated the efficiency of target-enriched long-read sequencing (TELSeq) for detecting antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) within complex matrices. We aimed to overcome limitations associated with traditional antimicrobial resistance (AMR) detection methods, including short-read shotgun metagenomics, which can lack sensitivity, specificity, and the ability to provide detailed genomic context. By combining biotinylated probe-based enrichment with long-read sequencing, we facilitated the amplification and sequencing of ARGs, eliminating the need for bioinformatic reconstruction. Our experimental design included replicates of human fecal microbiota transplant material, bovine feces, pristine prairie soil, and a mock human gut microbial community, allowing us to examine variables including genomic DNA input and probe set composition. Our findings demonstrated that TELSeq markedly improves the detection rates of ARGs and MGEs compared to traditional sequencing methods, underlining its potential for accurate AMR monitoring. A key insight from our research is the importance of incorporating mobilome profiles to better predict the transferability of ARGs within microbial communities, prompting a recommendation for the use of combined ARG-MGE probe sets for future studies. We also reveal limitations for ARG detection from low-input workflows, and describe the next steps for ongoing protocol refinement to minimize technical variability and expand utility in clinical and public health settings. This effort is part of our broader commitment to advancing methodologies that address the global challenge of AMR.

Mycobacterium houstonense (M. houstonense) belongs to the nontuberculous mycobacterium group. Infection caused by M. houstonense is prone to recurrence.

We present a patient who was diagnosed with osteomyelitis caused by M. houstonense and treated with a combination of cefoxitin, and amikacin combined with linezolid.

The emergence of metagenomic next-generation sequencing (NGS) has brought new hope for the diagnosis and treatment of listeria meningitis. NGS can analyze a large number of nucleic acid sequences in a short time and quickly determine the pathogen species in the sample. Compared with traditional cerebrospinal fluid culture, NGS can greatly shorten the diagnosis time and provide strong support for the timely treatment of patients. Regarding treatment, NGS can also play an important role. Rapid and accurate diagnosis can enable patients to start targeted treatment as soon as possible and improve the treatment effect. At the same time, by monitoring the changes in pathogen resistance, the treatment plan can be adjusted in time to avoid treatment failure.

Within a multistate viral genomic surveillance program, we evaluated whether proportions of severe acute respiratory syndrome coronavirus 2 (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 (adjusted odds ratio [aOR], 0.60 [95% confidence interval (CI), .43-.84; P = .003] and 0.35 [.21-.58; P < .001], respectively). JN.1 and HV.1 variants may be associated with a lower risk of severe illness. The severity of coronavirus disease 2019 may have attenuated as predominant circulating SARS-CoV-2 lineages shifted from EG.5 to HV.1 to JN.1.

Aquifers, which provide drinking water for nearly half the world's population, face significant challenges from microbial contamination, particularly from waterborne viruses such as human adenovirus (HAdV), norovirus (NoV) and enterovirus (EV). This study, conducted as part of the UPWATER project, investigates the sources of urban groundwater contamination using viral passive sampling (VPS) and target enrichment sequencing (TES). We assessed the abundance of eight viral pathogens (HAdV, EV, NoV genogroup I and II, rotavirus, influenza A virus, hepatitis E virus and SARS-CoV-2) and investigated the virome diversity of groundwater in the aquifer of the Besòs River Delta in Catalonia. Over a period of 7 months, we collected 114 samples from the aquifer using nylon and nitrocellulose membranes to adsorb viruses over a 10-day period. Human faecal contamination was detected in nearly 50 % of the groundwater samples, with mean HAdV total counts ranging from 1.23E+02 to 3.66E+03 GC, and occasional detections of EV and NoV GI and GII. In addition, deep sequencing revealed a diverse virome in the aquifer, with detection of human pathogens, including adenovirus, astrovirus, calicivirus, enterovirus, herpesvirus, papillomavirus and rotavirus. Time-integrated sampling using VPS increases the likelihood of virus detection and, when combined with TES, can provide a deeper understanding of virus prevalence in this important water compartment. This approach is expected to streamline long-term monitoring efforts and enable small communities or water managers with limited resources to effectively manage their groundwater reservoirs.

The use of metagenomic next-generation sequencing technology to obtain complete viral genome sequences directly from clinical samples with low viral load remains challenging-especially in the case of respiratory viruses-due to the low copy number of viral versus host genomes. To overcome this limitation, target capture sequencing for the enrichment of specific genomes has been developed and applied for direct genome sequencing of viruses. However, as the efficiency of enrichment varies depending on the probes, the type of clinical sample, etc., validation is essential before target capture sequencing can be applied to clinical diagnostics. In this study, we evaluated the utility of target capture sequencing with a comprehensive viral probe panel for clinical respiratory specimens collected from patients diagnosed with SARS-CoV-2 or influenza type A. We focused on clinical specimens containing low copy numbers of viral genomes. Target capture sequencing yielded approximately 180- and 2,000-fold higher read counts of SARS-CoV-2 and influenza A virus, respectively, than metagenomic sequencing when the RNA extracted from specimens contained 59.3 copies/µL of SARS-CoV-2 or 625.1 copies/µL of influenza A virus. In addition, the target capture sequencing identified sequence reads in all SARS-CoV-2- or influenza type A-positive specimens with <26 RNA copies/µL, some of which also yielded >70% of the full-length genomes of SARS-CoV-2 or influenza A virus. Furthermore, the target capture sequencing using comprehensive probes identified co-infections with viruses other than SARS-CoV-2, suggesting that this approach will not only detect a wide range of viruses but also contribute to epidemiological studies.IMPORTANCETarget capture sequencing has been developed and applied for direct genome sequencing of viruses in clinical specimens to overcome the low detection sensitivity of metagenomic next-generation sequencing. In this study, we evaluated the utility of target capture sequencing with a comprehensive viral probe panel for clinical respiratory specimens collected from patients diagnosed with SARS-CoV-2 or influenza type A, focusing on clinical specimens containing low copy numbers of viral genomes. Our results showed that the target capture sequencing yielded dramatically higher read counts than metagenomic sequencing for both viruses. Furthermore, the target capture sequencing using comprehensive probes identified co-infections with other viruses, suggesting that this approach will not only detect a wide range of viruses but also contribute to epidemiological studies.

Low-abundance members of microbial communities are difficult to study in their native habitats, including Escherichia coli, a minor but common inhabitant of the gastrointestinal tract, and key opportunistic pathogen of the urinary tract. While multi-omic analyses have detailed interactions between uropathogenic Escherichia coli (UPEC) and the bladder mediating urinary tract infection (UTI), little is known about UPEC in its pre-infection reservoir, the gastrointestinal tract, partly due to its low relative abundance (<1%). To sensitively explore the genomes and transcriptomes of diverse gut E. coli, we develop E. coli PanSelect, which uses probes designed to specifically capture E. coli's broad pangenome. We demonstrate its ability to enrich diverse E. coli by orders of magnitude, in a mock community and in human stool from a study investigating recurrent UTI (rUTI). Comparisons of transcriptomes between gut E. coli of women with and without history of rUTI suggest rUTI gut E. coli are responding to increased oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of in vivo E. coli biology in other low-abundance environments, and the framework described here has broad applicability to other diverse, low-abundance organisms.

Highly pathogenic avian influenza viruses (HPAIV) H5N1 clade 2.3.4.4b continue to have unprecedented global impacts on wild birds and mammals, with especially significant mortality observed in colonial surface-nesting seabirds and in some marine mammal species. In July of 2023 H5N1 HPAIV 2.3.4.4b was detected in Caspian terns nesting on Rat Island, Washington USA. An estimated 1,800-1,900 adult terns populated the breeding colony, based on aerial photographs taken at the start of the outbreak. On a near-weekly basis throughout July and August, we counted and removed carcasses, euthanized moribund birds, and collected swab and tissue samples for diagnostic testing and next-generation sequencing. We directly counted 1,101 dead Caspian tern adults and 520 dead chicks, indicating a minimum 56% loss of the adult colony population and potential impacts to reproductive success. Combining the observed mortality on Rat Island with HPAI-related Caspian tern deaths recorded elsewhere in Washington and Oregon, we estimate that 10-14% of the Pacific Flyway population was lost in the summer of 2023. Comparatively few adult Glaucous-winged gulls (hybrids) nesting on Rat Island died (~3% of the local population), although gull chick mortality was high. Sixteen harbor seals in the immediate or nearby area stranded during the outbreak, and H5N1 HPAIV was detected in brain and/or lung tissue of five seals. These cases are the first known detections of HPAIV in a marine mammal on the Pacific coast of North America. Phylogenetic analyses support the occurrence of at least three independent avian-mammalian virus spillover events (tern or gull to harbor seal). Whole genome sequencing indicated that H5N1 HPAIV may have been introduced to Washington from Caspian terns in Oregon. Ongoing monitoring and surveillance for H5N1 HPAIV in the marine environment is necessary to understand the epidemiology of this virus, assess conservation impacts to susceptible species, and provide support for data-driven management and response actions.

Probe-based nucleic acid enrichment represents an effective route to enhance the detection capacity of next-generation sequencing (NGS) in a set of clinically diverse and relevant microbial species. In this study, we assessed the effect of the enrichment-based sequencing on identifying respiratory infections using tiling RNA probes targeting 76 respiratory pathogens and sequenced using both Illumina and Oxford Nanopore platforms. Forty respiratory swab samples pre-tested for a panel of respiratory pathogens by qPCR were used to benchmark the sequencing data. We observed a general improvement in sensitivity after enrichment. The overall detection rate increased from 73 to 85% after probe capture detected by Illumina. Moreover, enrichment with probe sets boosted the frequency of unique pathogen reads by 34.6 and 37.8-fold for Illumina DNA and cDNA sequencing, respectively. This also resulted in significant improvements on genome coverage especially in viruses. Despite these advantages, we found that library pooling may cause reads mis-assignment, probably due to crosstalk issues arise from post-capture PCR and from pooled sequencing, thus increasing the risk of bleed-through signal. Taken together, an overall improvement in the breadth and depth of pathogen coverage is achieved using enrichment-based sequencing method. For future applications, automated library processing and pooling-free sequencing could enhance the precision and timeliness of probe enrichment-based clinical metagenomics.

Several steps in the abattoir can influence the presence of microbes and associated resistance genes (ARGs) on the animal carcasses used for further meat processing. We investigated how these processes influence the resistome-microbiome of groups of pigs with different on-farm antimicrobial exposure status, from the moment they entered the abattoir until the end of carcass processing. Using a targeted enrichment metagenomic approach, we identified 672 unique ARGs conferring resistance to 43 distinct AMR classes from pooled skin (N = 42) and carcass swabs (N = 63) collected sequentially before, during, and after the slaughter process and food safety interventions. We observed significant variations in the resistome and microbial profiles of pigs before and after slaughter, as well as a significant decline in ARG counts, diversity, and microbial DNA load during slaughter and carcass processing, irrespective of prior antimicrobial treatments on the farm. These results suggest that existing interventions in the abattoir are effective in reducing not only the pathogen load but also the overall bacterial burden, including ARGs on pork carcasses. Concomitant with reductions in microbial and ARG counts, we observed an increase in the relative abundance of non-drug-specific ARGs, such as those conferring resistance to metals and biocides, and in particular mercury. Using a strict colocalization procedure, we found that most mercury ARGs were associated with genomes from the Pseudomonadaceae and Enterobacteriaceae families. Collectively, these findings demonstrate that slaughter and processing practices within the abattoir can shape the microbial and ARG profiles of pork carcasses during the transition from living muscle to meat.

Metagenomic next-generation sequencing (mNGS), which provides untargeted and unbiased pathogens detection, has been extensively applied to improve diagnosis of pulmonary infection. This study aimed to compare the clinical performance between mNGS and targeted NGS (tNGS) for microbial detection and identification in bronchoalveolar lavage fluid (BALF) from kidney transplantation recipients (KTRs).

BALF samples with microbiological results from mNGS and conventional microbiological test (CMT) were included. For tNGS, samples were extracted, amplified by polymerase chain reaction with pathogen-specific primers, and sequenced on an Illumina Nextseq.

A total of 99 BALF from 99 KTRs, among which 93 were diagnosed as pulmonary infection, were analyzed. Compared with CMT, both mNGS and tNGS showed higher positive rate and sensitivity (p<0.001) for overall, bacterial and fungal detection. Although the positive rate for mNGS and tNGS was comparable, mNGS significantly outperformed tNGS in sensitivity (100% vs. 93.55%, p<0.05), particularly for bacteria and virus (p<0.001). Moreover, the true positive rate for detected microbes of mNGS was superior over that of tNGS (73.97% vs. 63.15%, p<0.05), and the difference was also significant when specific for bacteria (94.59% vs. 64.81%, p<0.001) and fungi (93.85% vs. 72.58%, p<0.01). Additionally, we found that, unlike most microbes such as SARS-CoV-2, Aspergillus, and EBV, which were predominantly detected from recipients who underwent surgery over 3 years, Torque teno virus (TTV) were principally detected from recipients within 1-year post-transplant, and as post-transplantation time increased, the percentage of TTV positivity declined.

Although tNGS was inferior to mNGS owing to lower sensitivity and true positive rate in identifying respiratory pathogens among KTRs, both considerably outperformed CMT.

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu  and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar .

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples.

Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

Low-abundance members of microbial communities are difficult to study in their native habitats. This includes Escherichia coli, a minor, but common inhabitant of the gastrointestinal tract and opportunistic pathogen, including of the urinary tract, where it is the primary pathogen. While multi-omic analyses have detailed critical interactions between uropathogenic Escherichia coli (UPEC) and the bladder that mediate UTI outcome, comparatively little is known about UPEC in its pre-infection reservoir, partly due to its low abundance there (<1% relative abundance). To accurately and sensitively explore the genomes and transcriptomes of diverse E. coli in gastrointestinal communities, we developed E. coli PanSelect which uses a set of probes designed to specifically recognize and capture E. coli's broad pangenome from sequencing libraries. We demonstrated the ability of E. coli PanSelect to enrich, by orders of magnitude, sequencing data from diverse E. coli using a mock community and a set of human stool samples collected as part of a cohort study investigating drivers of recurrent urinary tract infections (rUTI). Comparisons of genomes and transcriptomes between E. coli residing in the gastrointestinal tracts of women with and without a history of rUTI suggest that rUTI gut E. coli are responding to increased levels of oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of native in vivo biology of E. coli in other environments where it is at low relative abundance, and the framework described here has broad applicability to other highly diverse, low abundance organisms.

Orthohantaviruses, transmitted primarily by rodents, cause hemorrhagic fever with renal syndrome (HFRS) in Eurasia and hantavirus pulmonary syndrome in the Americas. These viruses, with documented human-to-human transmission, exhibit a wide case-fatality rate, 0.5-40 %, depending on the virus species, and no vaccine or effective treatment for severe Orthohantavirus infections exists. In Europe, the Puumala virus (PUUV), carried by the bank vole Myodes glareolus, causes a milder form of HFRS. Despite the reliance on serology and PCR for diagnosis, the three genomic segments of Swedish wild-type PUUV have yet to be completely sequenced. We have developed a targeted hybrid-capture method aimed at comprehensive genomic sequencing of wild-type PUUV isolates and the identification of other Orthohantaviruses. Our custom-designed panel includes >11,200 probes covering the entire Orthohantavirus genus. Using this panel, we sequenced complete viral genomes from bank vole lung tissue, human plasma samples, and cell-cultured reference strains. Analysis revealed that Swedish PUUV isolates belong to the Northern Scandinavian lineage, with nucleotide diversity ranging from 2.8 % to 3.7 % among them. Notably, no significant genotypic differences were observed between the viral sequences from reservoirs and human cases except in the nonstructural protein. Despite the high endemicity of PUUV in Northern Sweden, these are the first complete Swedish wild-type PUUV genomes and substantially increase our understanding of PUUV evolution and epidemiology. The panel's sensitivity enables genomic sequencing of human samples with viral RNA levels reflecting the natural progression of infection and underscores our panel's diagnostic value, and could help to uncover novel Orthohantavirus transmission routes.

Rapid and accurate sequencing of the entire viral genome, coupled with continuous monitoring of genetic changes, is crucial for understanding the epidemiology of coronaviruses. We designed a novel method called micro target hybrid capture system (MT-Capture) to enable whole-genome sequencing in a timely manner. The novel design of probes used in target binding exhibits a unique and synergistic "hand-in-hand" conjugation effect. The entire hybrid capture process is within 2.5 hours, overcoming the time-consuming and complex operation characteristics of the traditional liquid-phase hybrid capture (T-Capture) system. By designing specific probes for these coronaviruses, MT-Capture effectively enriched isolated strains and 112 clinical samples of coronaviruses with cycle threshold values below 37. Compared to multiplex PCR sequencing, it does not require frequent primer updates and has higher compatibility. MT-Capture is highly sensitive and capable of tracking variants.IMPORTANCEMT-Capture is meticulously designed to enable the efficient acquisition of the target genome of the common human coronavirus. Coronavirus is a kind of virus that people are generally susceptible to and is epidemic and infectious, and it is the virus with the longest genome among known RNA viruses. Therefore, common human coronavirus samples are selected to evaluate the accuracy and sensitivity of MT-Capture. This method utilizes innovative probe designs optimized through probe conjugation techniques, greatly shortening the time and simplifying the handwork compared with traditional hybridization capture processes. Our results demonstrate that MT-Capture surpasses multiplex PCR in terms of sensitivity, exhibiting a thousandfold increase. Moreover, MT-Capture excels in the identification of mutation sites. This method not only is used to target the coronaviruses but also may be used to diagnose other diseases, including various infectious diseases, genetic diseases, or tumors.

High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.

Target enrichment sequencing techniques are gaining widespread use in the field of genomics, prized for their economic efficiency and swift processing times. However, their success depends on the performance of probes and the evenness of sequencing depth among each probe. To accurately predict probe coverage depth, a model called Deqformer is proposed in this study. Deqformer utilizes the oligonucleotides sequence of each probe, drawing inspiration from Watson-Crick base pairing and incorporating two BERT encoders to capture the underlying information from the forward and reverse probe strands, respectively. The encoded data are combined with a feed-forward network to make precise predictions of sequencing depth. The performance of Deqformer is evaluated on four different datasets: SNP panel with 38 200 probes, lncRNA panel with 2000 probes, synthetic panel with 5899 probes and HD-Marker panel for Yesso scallop with 11 000 probes. The SNP and synthetic panels achieve impressive factor 3 of accuracy (F3acc) of 96.24% and 99.66% in 5-fold cross-validation. F3acc rates of over 87.33% and 72.56% are obtained when training on the SNP panel and evaluating performance on the lncRNA and HD-Marker datasets, respectively. Our analysis reveals that Deqformer effectively captures hybridization patterns, making it robust for accurate predictions in various scenarios. Deqformer leads to a novel perspective for probe design pipeline, aiming to enhance efficiency and effectiveness in probe design tasks.

Existing diagnostic approaches for paucibacillary tuberculosis (TB) are limited by the low sensitivity of testing methods and difficulty in obtaining suitable samples.

An ultrasensitive TB diagnostic strategy was established, integrating efficient and specific TB targeted next-generation sequencing and machine learning models, and validated in clinical cohorts to test plasma cfDNA, cerebrospinal fluid (CSF) DNA collected from tuberculous meningitis (TBM) and pediatric pulmonary TB (PPTB) patients.

In the detection of 227 samples, application of the specific thresholds of CSF DNA (AUC = 0.974) and plasma cfDNA (AUC = 0.908) yielded sensitivity of 97.01 % and the specificity of 95.65 % in CSF samples and sensitivity of 82.61 % and specificity of 86.36 % in plasma samples, respectively. In the analysis of 44 paired samples from TBM patients, our strategy had a high concordance of 90.91 % (40/44) in plasma cfDNA and CSF DNA with both sensitivity of 95.45 % (42/44). In the PPTB patient, the sensitivity of the TB diagnostic strategy yielded higher sensitivity on plasma specimen than Xpert assay on gastric lavage (28.57 % VS. 15.38 %).

Our TB diagnostic strategy provides greater detection sensitivity for paucibacillary TB, while plasma cfDNA as an easily collected specimen, could be an appropriate sample type for PTB and TBM diagnosis.

Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 2 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluated Olivar on real wastewater samples and found that Olivar had up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available as a web application at https://olivar.rice.edu. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https://github.com/treangenlab/Olivar.

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.

On Aug 29, 2021, Operation Allies Welcome (OAW) was established to support the resettlement of more than 80 000 Afghan evacuees in the USA. After identification of measles among evacuees, incoming evacuee flights were temporarily paused, and mass measles vaccination of evacuees aged 6 months or older was introduced domestically and overseas, with a 21-day quarantine period after vaccination. We aimed to evaluate patterns of measles virus transmission during this outbreak and the impact of control measures.

We conducted a measles outbreak investigation among Afghan evacuees who were resettled in the USA as part of OAW. Patients with measles were defined as individuals with an acute febrile rash illness between Aug 29, 2021, and Nov 26, 2021, and either laboratory confirmation of infection or epidemiological link to a patient with measles with laboratory confirmation. We analysed the demographics and clinical characteristics of patients with measles and used epidemiological information and whole-genome sequencing to track transmission pathways. A transmission model was used to evaluate the effects of vaccination and other interventions.

47 people with measles (attack rate: 0·65 per 1000 evacuees) were reported in six US locations housing evacuees in four states. The median age of patients was 1 year (range 0-26); 33 (70%) were younger than 5 years. The age distribution shifted during the outbreak towards infants younger than 12 months. 20 (43%) patients with wild-type measles virus had rash onset after vaccination. No fatalities or community spread were identified, nor further importations after flight resumption. In a non-intervention scenario, transmission models estimated that a median of 5506 cases (IQR 10-5626) could have occurred. Infection clusters based on epidemiological criteria could be delineated into smaller clusters using phylogenetic analyses; however, sequences with few substitution count differences did not always indicate single lines of transmission.

Implementation of control measures limited measles transmission during OAW. Our findings highlight the importance of integration between epidemiological and genetic information in discerning between individual lines of transmission in an elimination setting.

US Centers for Disease Control and Prevention.

The diagnosis and specific and causal treatment of myocarditis and inflammatory cardiomyopathy remain a major clinical challenge. Despite the rapid development of new imaging techniques, endomyocardial biopsies remain the gold standard for accurate diagnosis of inflammatory myocardial disease. With the introduction and continued development of immunohistochemical inflammation diagnostics in combination with viral nucleic acid testing, myocarditis diagnostics have improved significantly since their introduction. Together with new technologies such as miRNA and gene expression profiling, quantification of specific immune cell markers, and determination of viral activity, diagnostic accuracy and patient prognosis will continue to improve in the future. In this review, we summarize the current knowledge on the pathogenesis and diagnosis of myocarditis and inflammatory cardiomyopathies and highlight future perspectives for more in-depth and specialized biopsy diagnostics and precision, personalized medicine approaches.

Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.