Next-Generation Sequencing for Biodefense: Biothreat Detection, Forensics, and the Clinic

Scalable search of massively pooled nucleic acid samples enabled by a molecular database query language

The surge in nucleic acid analytics requires scalable storage and retrieval systems akin to electronic databases used to organize digital data. Such a system could transform disease diagnosis, ecological preservation, and molecular surveillance of biothreats. Current storage systems use individual containers for nucleic acid samples, requiring single-sample retrieval that falls short compared with digital databases that allow complex and combinatorial data retrieval on aggregated data. Here, we leverage protective microcapsules with combinatorial DNA labeling that enables arbitrary retrieval on pooled biosamples analogous to Structured Query Languages. Ninety-six encapsulated pooled mock SARS-CoV-2 genomic samples barcoded with patient metadata are used to demonstrate queries with simultaneous matches to sample collection date ranges, locations, and patient health statuses, illustrating how such flexible queries can be used to yield immunological or epidemiological insights. The approach applies to any biosample database labeled with orthogonal barcodes, enabling complex post-hoc analysis, for example, to study global biothreat epidemiology.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Development and Evaluation of a Next-Generation Sequencing Panel for the Multiple Detection and Identification of Pathogens in Fermented Foods

These days, bacterial detection methods have some limitations in sensitivity, specificity, and multiple detection. To overcome these, novel detection and identification method is necessary to be developed. Recently, NGS panel method has been suggested to screen, detect, and even identify specific foodborne pathogens in one reaction. In this study, new NGS panel primer sets were developed to target 13 specific virulence factor genes from five types of pathogenic Escherichia coli, Listeria monocytogenes, and Salmonella enterica serovar Typhimurium, respectively. Evaluation of the primer sets using singleplex PCR, crosscheck PCR and multiplex PCR revealed high specificity and selectivity without interference of primers or genomic DNAs. Subsequent NGS panel analysis with six artificially contaminated food samples using those primer sets showed that all target genes were multi-detected in one reaction at 10⁸-10⁵ CFU of target strains. However, a few false-positive results were shown at 10⁶-10⁵ CFU. To validate this NGS panel analysis, three sets of qPCR analyses were independently performed with the same contaminated food samples, showing the similar specificity and selectivity for detection and identification. While this NGS panel still has some issues for detection and identification of specific foodborne pathogens, it has much more advantages, especially multiple detection and identification in one reaction, and it could be improved by further optimized NGS panel primer sets and even by application of a new real-time NGS sequencing technology. Therefore, this study suggests the efficiency and usability of NGS panel for rapid determination of origin strain in various foodborne outbreaks in one reaction.

MTSv: rapid alignment-based taxonomic classification and high-confidence metagenomic analysis

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.

Optimization of Oxford Nanopore Technology Sequencing Workflow for Detection of Amplicons in Real Time Using ONT-DART Tool

An optimized, well-tested and validated targeted genomic sequencing-based high-throughput assay is currently not available ready for routine biodefense and biosurveillance applications. Earlier, we addressed this gap by developing and establishing baseline comparisons of a multiplex end-point Polymerase Chain Reaction (PCR) assay followed by Oxford Nanopore Technology (ONT) based amplicon sequencing to real time PCR and customized data processing. Here, we expand upon this effort by identifying the optimal ONT library preparation method for integration into a novel software platform ONT-DART (ONT-Detection of Amplicons in Real-Time). ONT-DART is a dockerized, real-time, amplicon-sequence analysis workflow that is used to reproducibly process and filter read data to support actionable amplicon detection calls based on alignment metrics, within sample statistics, and no-template control data. This analysis pipeline was used to compare four ONT library preparation protocols using R9 and Flongle (FL) flow cells. The two 4-Primer methods tested required the shortest preparation times (5.5 and 6.5 h) for 48 libraries but provided lower fidelity data. The Native Barcoding and Ligation methods required longer preparation times of 8 and 12 h, respectively, and resulted in higher overall data quality. On average, data derived from R9 flow cells produced true positive calls for target organisms more than twice as fast as the lower throughput FL flow cells. These results suggest that utilizing the R9 flowcell with an ONT Native Barcoding amplicon library method in combination with ONT-DART platform analytics provides the best sequencing-based alternative to current PCR-based biodetection methods.

Comparison of Illumina and Oxford Nanopore Sequencing Technologies for Pathogen Detection from Clinical Matrices Using Molecular Inversion Probes

Next-generation sequencing is rapidly finding footholds in numerous microbiological fields, including infectious disease diagnostics. Here, we describe a molecular inversion probe panel for the identification of bacterial, viral, and parasitic pathogens. We describe the ability of Illumina and Oxford Nanopore Technologies (ONT) to sequence small amplicons originating from this panel for the identification of pathogens in complex matrices. The panel correctly classified 31 bacterial pathogens directly from positive blood culture bottles with a genus-level concordance of 96.7% and 90.3% on the Illumina and ONT platforms, respectively. Both sequencing platforms detected 18 viral and parasitic organisms directly from mock clinical samples of plasma and whole blood at concentrations of 10⁴ PFU/mL with few exceptions. In general, Illumina sequencing exhibited greater read counts with lower percent mapped reads; however, this resulted in no effect on limits of detection compared with ONT sequencing. Mock clinical evaluation of the probe panel on the Illumina and ONT platforms resulted in positive predictive values of 0.91 and 0.88 and negative predictive values of 1 and 1 from de-identified human chikungunya virus samples compared with gold standard quantitative RT-PCR. Overall, these data show that molecular inversion probes are an adaptable technology capable of pathogen detection from complex sample matrices on current next-generation sequencing platforms.

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

High-throughput sequencing technologies in the detection of livestock pathogens, diagnosis, and zoonotic surveillance

Increasing globalization, agricultural intensification, urbanization, and climatic changes have resulted in a significant recent increase in emerging infectious zoonotic diseases. Zoonotic diseases are becoming more common, so innovative, effective, and integrative research is required to better understand their transmission, ecological implications, and dynamics at wildlife-human interfaces. High-throughput sequencing (HTS) methodologies have enormous potential for unraveling these contingencies and improving our understanding, but they are only now beginning to be realized in livestock research. This study investigates the current state of use of sequencing technologies in the detection of livestock pathogens such as bovine, dogs (Canis lupus familiaris), sheep (Ovis aries), pigs (Sus scrofa), horses (Equus caballus), chicken (Gallus gallus domesticus), and ducks (Anatidae) as well as how it can improve the monitoring and detection of zoonotic infections. We also described several high-throughput sequencing approaches for improved detection of known, unknown, and emerging infectious agents, resulting in better infectious disease diagnosis, as well as surveillance of zoonotic infectious diseases. In the coming years, the continued advancement of sequencing technologies will improve livestock research and hasten the development of various new genomic and technological studies on farm animals.

Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

Bioaerosol monitoring by integrating DC impedance microfluidic cytometer with wet-cyclone air sampler

The recent outbreak of COVID-19 has highlighted the seriousness of airborne diseases and the need for a proper pathogen detection system. Compared to the ample amount of research on biological detection, work on integrated devices for air monitoring is rare. In this work, we integrated a wet-cyclone air sampler and a DC impedance microfluidic cytometer to build a cyclone-cytometer integrated air monitor (CCAM). The wet-cyclone air sampler sucks the air and concentrates the bioaerosols into 10 mL of aqueous solvent. After 5 min of air sampling, the bioaerosol-containing solution was conveyed to the microfluidic cytometer for detection. The device was tested with aerosolized microbeads, dust, and Escherichia coli (E. coli). CCAM is shown to differentiate particles from 0.96 to 2.95 μm with high accuracy. The wet cyclone air-sampler showed a 28.04% sampling efficiency, and the DC impedance cytometer showed 87.68% detection efficiency, giving a total of 24.59% overall CCAM efficiency. After validation of the device performance, CCAM was used to detect bacterial aerosols and their viability without any separate pretreatment step. Differentiation of dust, live E. coli, and dead E. coli was successfully performed by the addition of BacLight bacterial viability reagent in the sampling solvent. The usage could be further extended to detection of specific species with proper antibody fluorescent label. A promising strategy for aerosol detection is proposed through the constructive integration of a DC impedance microfluidic cytometer and a wet-cyclone air sampler.

The forensic landscape and the population genetic analyses of Hainan Li based on massively parallel sequencing DNA profiling

Due to the formation of the Qiongzhou Strait by climate change and marine transition, Hainan island was isolated from the mainland southern China during the Last Glacial Maximum. Hainan island, located at the southernmost part of China and separated from the Leizhou Peninsula by the Qiongzhou Strait, laid on one of the modern human northward migration routes from Southeast Asia to East Asia. The Hlai language-speaking Li minority, the second largest population after Han Chinese in Hainan island, is the direct descendants of the initial migrants in Hainan island and has unique ethnic properties and derived characteristics; however, the forensic-associated studies on Hainan Li population are still insufficient. Hence, 136 Hainan Li individuals were genotyped in this study using the MPS-based ForenSeq™ DNA Signature Prep Kit (DNA Primer Set A, DPMA) to characterize the forensic genetic polymorphism landscape, and DNA profiles were obtained from 152 different molecular genetic markers (27 autosomal STRs, 24 Y-STRs, 7 X-STRs, and 94 iiSNPs). A total of 419 distinct length variants and 586 repeat sequence sub-variants, with 31 novel alleles (at 17 loci), were identified across the 58 STR loci from the DNA profiles of Hainan Li population. We evaluated the forensic characteristics and efficiencies of DPMA, demonstrating that the STRs and iiSNPs in DPMA were highly polymorphic in Hainan Li population and could be employed in forensic applications. In addition, we set up three datasets, which included the genetic data of (i) iiSNPs (27 populations, 2640 individuals), (ii) Y-STRs (42 populations, 8281 individuals), and (iii) Y haplogroups (123 populations, 4837 individuals) along with the population ancestries and language families, to perform population genetic analyses separately from different perspectives. In conclusion, the phylogenetic analyses indicated that Hainan Li, with a southern East Asia origin and Tai-Kadai language-speaking language, is an isolated population relatively. But the genetic pool of Hainan Li influenced by the limited gene flows from other Tai-Kadai populations and Hainan populations. Furthermore, the establishment of isolated population models will be beneficial to clarify the exquisite population structures and develop specific genetic markers for subpopulations in forensic genetic fields.

Crimean-Congo Hemorrhagic Fever Virus (CCHFV): A Silent but Widespread Threat

Purpose of Review

This review is aimed at highlighting recent research and articles on the complicated relationship between virus, vector, and host and how biosurveillance at each level informs disease spread and risk.

Recent Findings

While human cases of CCHFV and tick identification in non-endemic areas in 2019–2020 were reported to sites such as ProMed, there is a gap in recent published literature on these and broader CCHFV surveillance efforts from the late 2010s.

Summary

A review of the complex aspects of CCHFV maintenance in the environment coupled with high fatality rate and lack of vaccines and therapeutics warrants the need for a One-Health approach toward detection and increased biosurveillance programs for CCHFV.

How Cooperative Engagement Programs Strengthen Sequencing Capabilities for Biosurveillance and Outbreak Response

The threat of emerging and re-emerging infectious diseases continues to be a challenge to public and global health security. Cooperative biological engagement programs act to build partnerships and collaborations between scientists and health professionals to strengthen capabilities in biosurveillance. Biosurveillance is the systematic process of detecting, reporting, and responding to especially dangerous pathogens and pathogens of pandemic potential before they become outbreaks, epidemics, and pandemics. One important tool in biosurveillance is next generation sequencing. Expensive sequencing machines, reagents, and supplies make it difficult for countries to adopt this technology. Cooperative engagement programs help by providing funding for technical assistance to strengthen sequencing capabilities. Through workshops and training, countries are able to learn sequencing and bioinformatics, and implement these tools in their biosurveillance programs. Cooperative programs have an important role in building and sustaining collaborations among institutions and countries. One of the most important pieces in fostering these collaborations is trust. Trust provides the confidence that a successful collaboration will benefit all parties involved. With sequencing, this enables the sharing of pathogen samples and sequences. Obtaining global sequencing data helps to identify unknown etiological agents, track pathogen evolution and infer transmission networks throughout the duration of a pandemic. Having sequencing technology in place for biosurveillance generates the capacity to provide real-time data to understand and respond to pandemics. We highlight the need for these programs to continue to strengthen sequencing in biosurveillance. By working together to strengthen sequencing capabilities, trust can be formed, benefitting global health in the face of biological threats.

Genome-scale de novo assembly using ALGA

Motivation

There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out.

Results

We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland.

Availability and implementation

ALGA is available at http://alga.put.poznan.pl.

Supplementary information

Supplementary data are available at Bioinformatics online.

Pulmonary actinomycosis diagnosed by radial endobronchial ultrasound coupled with metagenomic next-generation sequencing: A case report and brief literature review

Pulmonary actinomycosis (PA) is an uncommon pulmonary infectious disease that often is misdiagnosed. Metagenomic next-generation sequencing (mNGS) is a highly sensitive and culture-independent new molecular technology for precise infectious disease diagnosis. Here we report a PA case diagnosed by the combination of a radial endobronchial-ultrasonography guide sheath (R-EBUS-GS) and mNGS, along with a brief review of the literature.

A Survey of Antimicrobial Resistance Determinants in Category A Select Agents, Exempt Strains, and Near-Neighbor Species

A dramatic increase in global antimicrobial resistance (AMR) has been well documented. Of particular concern is the dearth of information regarding the spectrum and prevalence of AMR within Category A Select Agents. Here, we performed a survey of horizontally and vertically transferred AMR determinants among Category A agents and their near neighbors. Microarrays provided broad spectrum screening of 127 Francisella spp., Yersinia spp., and Bacillus spp. strains for the presence/absence of 500+ AMR genes (or families of genes). Detecting a broad variety of AMR genes in each genus, microarray analysis also picked up the presence of an engineered plasmid in a Y. pestis strain. High resolution melt analysis (HRMA) was also used to assess the presence of quinolone resistance-associated mutations in 100 of these strains. Though HRMA was able to detect resistance-causing point mutations in B. anthracis strains, it was not capable of discriminating these point mutations from other nucleotide substitutions (e.g., arising from sequence differences in near neighbors). Though these technologies are well-established, to our knowledge, this is the largest survey of Category A agents and their near-neighbor species for genes covering multiple mechanisms of AMR.

On DNA Signatures, Their Dual-Use Potential for GMO Counterfeiting, and a Cyber-Based Security Solution

This study investigates the role and functionality of special nucleotide sequences ("DNA signatures") to detect the presence of an organism and to distinguish it from all others. After highlighting vulnerabilities of the prevalent DNA signature paradigm for the identification of agricultural genetically modified (GM) organisms it will be argued that these so-called signatures really are no signatures at all - when compared to the notion of traditional (handwritten) signatures and their generalizations in the modern (digital) world. It is suggested that a recent contamination event of an unauthorized GM Bacillus subtilis strain (Paracchini et al., 2017) in Europe could have been-or the same way could be - the consequence of exploiting gaps of prevailing DNA signatures. Moreover, a recent study (Mueller, 2019) proposes that such DNA signatures may intentionally be exploited to support the counterfeiting or even weaponization of GM organisms (GMOs). These concerns mandate a re-conceptualization of how DNA signatures need to be realized. After identifying central issues of the new vulnerabilities and overlying them with practical challenges that bio-cyber hackers would be facing, recommendations are made how DNA signatures may be enhanced. To overcome the core problem of signature transferability in bioengineered mediums, it is necessary that the identifier needs to remain secret during the entire verification process. On the other hand, however, the goal of DNA signatures is to enable public verifiability, leading to a paradoxical dilemma. It is shown that this can be addressed with ideas that underlie special cryptographic signatures, in particular those of "zero-knowledge" and "invisibility." This means more than mere signature hiding, but relies on a knowledge-based proof and differentiation of a secret (here, as assigned to specific clones) which can be realized without explicit demonstration of that secret. A re-conceptualization of these principles can be used in form of a combined (digital and physical) method to establish confidentiality and prevent un-impersonation of the manufacturer. As a result, this helps mitigate the circulation of possibly hazardous GMO counterfeits and also addresses the situation whereby attackers try to blame producers for deliberately implanting illicit adulterations hidden within authorized GMOs.