Next Generation Sequencing and Bioinformatics Methodologies for Infectious Disease Research and Public Health: Approaches, Applications, and Considerations for Development of Laboratory Capacity

ESKAPE in China: epidemiology and characteristics of antibiotic resistance

The escalation of antibiotic resistance and the diminishing antimicrobial pipeline have emerged as significant threats to public health. The ESKAPE pathogens - Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. - were initially identified as critical multidrug-resistant bacteria, demanding urgently effective therapies. Despite the introduction of various new antibiotics and antibiotic adjuvants, such as innovative β-lactamase inhibitors, these organisms continue to pose substantial therapeutic challenges. People's Republic of China, as a country facing a severe bacterial resistance situation, has undergone a series of changes and findings in recent years in terms of the prevalence, transmission characteristics and resistance mechanisms of antibiotic resistant bacteria. The increasing levels of population mobility have not only shaped the unique characteristics of antibiotic resistance prevalence and transmission within People's Republic of China but have also indirectly reflected global patterns of antibiotic-resistant dissemination. What's more, as a vast nation, People's Republic of China exhibits significant variations in the levels of antibiotic resistance and the prevalence characteristics of antibiotic resistant bacteria across different provinces and regions. In this review, we examine the current epidemiology and characteristics of this important group of bacterial pathogens, delving into relevant mechanisms of resistance to recently introduced antibiotics that impact their clinical utility in China.

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Identification and clinicopathological analysis of potential p73-regulated biomarkers in colorectal cancer via integrative bioinformatics

This study aims to decipher crucial biomarkers regulated by p73 for the early detection of colorectal cancer (CRC) by employing a combination of integrative bioinformatics and expression profiling techniques. The transcriptome profile of HCT116 cell line p53- / - p73+ / + and p53- / - p73 knockdown was performed to identify differentially expressed genes (DEGs). This was corroborated with three CRC tissue expression datasets available in Gene Expression Omnibus. Further analysis involved KEGG and Gene ontology to elucidate the functional roles of DEGs. The protein-protein interaction (PPI) network was constructed using Cytoscape to identify hub genes. Kaplan-Meier (KM) plots along with GEPIA and UALCAN database analysis provided the insights into the prognostic and diagnostic significance of these hub genes. Machine/deep learning algorithms were employed to perform TNM-stage classification. Transcriptome profiling revealed 1289 upregulated and 1897 downregulated genes. When intersected with employed CRC datasets, 284 DEGs were obtained. Comprehensive analysis using gene ontology and KEGG revealed enrichment of the DEGs in metabolic process, fatty acid biosynthesis, etc. The PPI network constructed using these 284 genes assisted in identifying 20 hub genes. Kaplan-Meier, GEPIA, and UALCAN analyses uncovered the clinicopathological relevance of these hub genes. Conclusively, the deep learning model achieved TNM-stage classification accuracy of 0.78 and 0.75 using 284 DEGs and 20 hub genes, respectively. The study represents a pioneer endeavor amalgamating transcriptomics, publicly available tissue datasets, and machine learning to unveil key CRC-associated genes. These genes are found relevant regarding the patients' prognosis and diagnosis. The unveiled biomarkers exhibit robustness in TNM-stage prediction, thereby laying the foundation for future clinical applications and therapeutic interventions in CRC management.

Tips and tools to obtain and assess mosquito viromes

Due to their vectorial capacity, mosquitoes (Diptera: Culicidae) receive special attention from health authorities and entomologists. These cosmopolitan insects are responsible for the transmission of many viral diseases, such as dengue and yellow fever, causing huge impacts on human health and justifying the intensification of research focused on mosquito-borne diseases. In this context, the study of the virome of mosquitoes can contribute to anticipate the emergence and/or the reemergence of infectious diseases. The assessment of mosquito viromes also contributes to the surveillance of a wide variety of viruses found in these insects, allowing the early detection of pathogens with public health importance. However, the study of mosquito viromes can be challenging due to the number and complexities of steps involved in this type of research. Therefore, this article aims to describe, in a straightforward and simplified way, the steps necessary for obtention and assessment of mosquito viromes. In brief, this article explores: the capture and preservation of specimens; sampling strategies; treatment of samples before DNA/RNA extraction; extraction methodologies; enrichment and purification processes; sequencing choices; and bioinformatics analysis.

Recent Advances in Metagenomic Approaches, Applications, and Challenge

Advances in metagenomics analysis with the advent of next-generation sequencing have extended our knowledge of microbial communities as compared to conventional techniques providing advanced approach to identify novel and uncultivable microorganisms based on their genetic information derived from a particular environment. Shotgun metagenomics involves investigating the DNA of the entire community without the requirement of PCR amplification. It provides access to study all genes present in the sample. On the other hand, amplicon sequencing targets taxonomically important marker genes, the analysis of which is restricted to previously known DNA sequences. While sequence-based metagenomics is used to analyze DNA sequences directly from the environment without the requirement of library construction and with limited identification of novel genes and products that can be complemented by functional genomics, function-based metagenomics requires fragmentation and cloning of extracted metagenome DNA in a suitable host with subsequent functional screening and sequencing clone for detection of a novel gene. Although advances were made in metagenomics, different challenges arise. This review provides insight into advances in the metagenomic approaches combined with next-generation sequencing, their recent applications highlighting the emerging ones, such as in astrobiology, forensic sciences, and SARS-CoV-2 infection diagnosis, and the challenges associated. This review further discusses the different types of metagenomics and outlines advancements in bioinformatics tools and their significance in the analysis of metagenomic datasets.

Real-Time Nanopore Q20+ Sequencing Enables Extremely Fast and Accurate Core Genome MLST Typing and Democratizes Access to High-Resolution Bacterial Pathogen Surveillance

Next-generation whole-genome sequencing is essential for high-resolution surveillance of bacterial pathogens, for example, during outbreak investigations or for source tracking and escape variant analysis. However, current global sequencing and bioinformatic bottlenecks and a long time to result with standard technologies demand new approaches. In this study, we investigated whether novel nanopore Q20+ long-read chemistry enables standardized and easily accessible high-resolution typing combined with core genome multilocus sequence typing (cgMLST). We set high requirements for discriminatory power by using the slowly evolving bacterium Bordetella pertussis as a model pathogen. Our results show that the increased raw read accuracy enables the description of epidemiological scenarios and phylogenetic linkages at the level of gold-standard short reads. The same was true for our variant analysis of vaccine antigens, resistance genes, and virulence factors, demonstrating that nanopore sequencing is a legitimate competitor in the area of next-generation sequencing (NGS)-based high-resolution bacterial typing. Furthermore, we evaluated the parameters for the fastest possible analysis of the data. By combining the optimized processing pipeline with real-time basecalling, we established a workflow that allows for highly accurate and extremely fast high-resolution typing of bacterial pathogens while sequencing is still in progress. Along with advantages such as low costs and portability, the approach suggested here might democratize modern bacterial typing, enabling more efficient infection control globally.

Microbial identification from traumatized immature permanent teeth with periapical lesions using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

This study aims at identifying the microbiota in traumatized immature permanent teeth with periapical lesions using Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS).

METHODS

The study included 16 immature maxillary central incisors with periapical lesions in 13 patients. Field decontamination and negative control samples were performed before and after access cavity preparation. Root canal samples were taken using sterile stainless-steel hand files following field decontamination. In-office inoculation and pure sub-cultures were performed. Bacterial isolates were prepared for MALDI-TOF MS (Bruker, Billerica, MA USA) analysis using the formic acid extraction method. A comparison of the prevalence of isolated microorganisms was done using a one-sample chi-square test. Comparisons between identified microbial species with the, cone beam computed tomography periapical index (CBCT PAI) scores and lesion volume were also conducted. The Chi-square test was applied to investigate the association between the categorical variables .

RESULTS

Out of the forty isolates recovered from the 16 traumatized teeth included in the present study with the mean patients' age of 10.93 ± 1.77, 37 isolates were reliably identified by MALDI-TOF MS. Twelve teeth (62.5%) were polymicrobial. The recovered bacteria belonged to five phyla, 15 genera and 25 species. Firmicutes were the predominant phylum (P < 0.001) over Bacteroidetes, Proteobacteria, Actinobacteria and Fusobacteria. Gram positive bacteria were significantly more prevalent than Gram negative (p = 0.03). Facultative anaerobes were the most prevalent (P < 0.001) compared to the obligate anaerobes and the obligate aerobes. The latter were the least prevalent. Statistically, significant differences existed in the comparison between CBCT PAI scores according to bacterial gram staining.

CONCLUSION

Traumatized immature permanent teeth with periapical lesions showed a significant predominance of Gram-positive facultative anaerobes. MALDI-TOF MS provided accurate identification of numerous viable endodontic microbes.

Mastadenovirus Molecular Diversity in Waste and Environmental Waters from the Lisbon Metropolitan Area

In face of the absence of epidemiological data regarding the circulation of human adenoviruses (HAdV) in Portugal, this study aimed at the evaluation of their molecular diversity in waste and environmental waters in the Lisbon Metropolitan Area (LMA). Using samples collected between 2018 and 2021, the HAdV hexon protein-coding sequence was partially amplified using three nested touch-down PCR protocols. The amplification products obtained were analyzed in parallel by two approaches: molecular cloning followed by Sanger sequencing and Next-Generation Sequencing (NGS) using Illumina^® sequencing. The analysis of NGS-generated data allowed the identification of a higher diversity of HAdV-A (19%), -B (1%), -C (3%), -D (24%), and -F (25%) viral types, along with murine adenovirus (MAdV-2; 30%) in the wastewater treatment plant samples. On the other hand, HAdV-A (19%), -D (32%), and -F (36%) were identified in environmental samples, and possibly MAdV-2 (14%). These results demonstrate the presence of fecal contamination in environmental waters and the assessment of the diversity of this virus provides important information regarding the distribution of HAdV in LMA, including the detection of HAdV-F41, the most frequently reported in water worldwide.

Electrochemical DNA Biosensor Based on Immobilization of a Non-Modified ssDNA Using Phosphoramidate-Bonding Strategy and Pencil Graphite Electrode Modified with AuNPs/CB and Self-Assembled Cysteamine Monolayer

The present paper describes an alternative approach to the traditionally used covalent immobilization methods that require cost-intensive and complicated chemistry modification of a single-stranded DNA (ssDNA) capture probe. The low-cost pencil graphite electrode (PGE) modified with carbon black (CB) and gold nanoparticles (AuNPs) was used as an electrochemical platform and the non-modified ssDNA was immobilized on a self-assembled cysteamine modified AuNPs/CB-PGE through a phosphoramidate bond between the 5'-terminal phosphate group of ssDNA and the primary amine group of cysteamine. The microRNA-21 was used as a target model in the fabrication of this electrochemical DNA biosensor and the hybridization process with the complementary probe was monitored by differential pulse voltammetry using methylene blue (MB) as an electrochemical hybridization indicator. The decreased reduction peak current of MB shows a good linear correlation with the increased concentration of microRNA-21 target sequences because the MB signal is determined by the amount of exposed guanine bases. The linear range of the fabricated DNA biosensor was from 1.0 × 10^-8 to 5.0 × 10^-7 M with a detection limit of 1.0 × 10^-9 M. These results show that the covalent immobilization of a non-modified ssDNA capture probe through a phosphoramidate-bonding strategy could serve as a cost-effective and versatile approach for the fabrication of DNA biosensors related to a wide range of applications that cover the fields of medical diagnostic and environmental monitoring. The fabricated electrochemical DNA biosensor was used to analyze microRNA-21 in a (spiked) human serum sample and it showed satisfactory and encouraging results as an electrochemical DNA biosensor platform.

A Serotype-Specific and Multiplex PCR Method for Whole-Genome Sequencing of Dengue Virus Directly from Clinical Samples

Dengue virus (DENV) is the most globally prevalent member of the genus Flavivirus in the family Flaviviridae, which can be classified into four serotypes. Historically, molecular epidemiological studies of DENV depended on E gene sequencing. The development of next-generation sequencing (NGS) allowed its application to viral whole-genome sequencing (WGS). In this study, we report the improvement of the existing WGS process for DENV by optimizing the primer design procedure, designing serotype-specific primer panels and reducing the sizes of amplicons. A total of 31 DENV-positive serum samples belonging to 4 serotypes and 9 genotypes of DENV were involved in the validation of the primer panels. The threshold cycle (CT) values of these samples ranged from 23.91 to 35.11. The validation results showed that the length of consensus sequences generated at a coverage depth of 20× or more ranged from 10,370 to 10,672 bp, with 100.00% coverage of the open reading frames and 97.34% to 99.52% coverage of the DENV genome. The amplification efficiency varied across amplicons, genotypes, and serotypes of DENVs. These results indicate that the serotype-specific primer panels allow users to obtain the whole genome of DENV directly from clinical samples, providing a universal, rapid, and effective tool for the integration of genomics with dengue surveillance. IMPORTANCE Dengue virus (DENV) is becoming the most globally prevalent arbovirus. The number of people living under the threat of DENV is increasing year by year. With the development of next-generation sequencing (NGS) technology, whole-genome sequencing (WGS) has been more and more widely used in infectious disease surveillance and molecular epidemiological studies. DENV population sequencing by NGS can increase our understanding of the changing epidemiology and evolution of the DENV genome at the molecular level, which demands universal primer panels and combination with NGS platforms. Multiplex PCR with a short-amplicon approach proved superior for amplifying viral genomes from clinical samples, particularly when the viral RNA was present at low concentrations. Additionally, DENV are known for their genetic diversity within serotype groups and geographical regions, so the primer panels we designed focused on universality, which would be useful in future local DENV outbreaks.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

Current status and capacity of pathogen laboratories in centers for disease control and prevention in China during the COVID-19 pandemic: A nationwide cross-sectional survey

The pathogen laboratory (p-lab) is the core and primary department of centers for disease control and prevention (CDCs) in China to respond to infectious disease outbreaks such as COVID-19. To understand the current status and capacity of p-labs in Chinese CDCs during the COVID-19 pandemic, we conducted a nationwide cross-sectional survey among 399 respondents from 239 CDCs. Differences in the current status of p-labs in CDCs of provinces, cities, and counties mainly comprised laboratory equipment, IEIs, mastery of personal occupational skills, and maximum detection capacity. Most CDCs reported a lack of staff and funds for personnel, which should be a priority in China's upcoming public health reform. The development of sequencing technologies has received considerable attention in CDCs. These are mainly used to study respiratory viruses such as influenza and SARS-CoV-2. The COVID-19 pandemic has driven development of the CDCs in China, and personnel and funds are considered key factors in improving the detection capacity of CDC p-labs.

Viral Eco-Genomic Tools: Development and Implementation for Aquatic Biomonitoring

Enteric viruses (EVs) occurrence within aquatic environments varies and leads to significant risk on public health of humans, animals, and diversity of aquatic taxa. Early and efficacious recognition of cultivable and fastidious EVs in aquatic systems are important to ensure the sanitary level of aquatic water and implement required treatment strategies. Herein, we provided a comprehensive overview of the conventional and up-to-date eco-genomic tools for aquatic biomonitoring of EVs, aiming to develop better water pollution monitoring tools. In combination with bioinformatics techniques, genetic tools including cloning sequencing analysis, DNA microarray, next-generation sequencing (NGS), and metagenomic sequencing technologies are implemented to make informed decisions about the global burden of waterborne EVs-associated diseases. The data presented in this review are helpful to recommend that: (1) Each viral pollution detection method has its own merits and demerits; therefore, it would be advantageous for viral pollution evaluation to be integrated as a complementary platform. (2) The total viral genome pool extracted from aquatic environmental samples is a real reflection of pollution status of the aquatic eco-systems; therefore, it is recommended to conduct regular sampling through the year to establish an updated monitoring system for EVs, and quantify viral peak concentrations, viral typing, and genotyping. (3) Despite that conventional detection methods are cheaper, it is highly recommended to implement molecular-based technologies to complement aquatic ecosystems biomonitoring due to numerous advantages including high-throughput capability. (4) Continuous implementation of the eco-genetic detection tools for monitoring the EVs in aquatic ecosystems is recommended.

The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families

The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.

Advanced Molecular and Immunological Diagnostic Methods to Detect SARS-CoV-2 Infection

COVID-19 emerged in late 2019 in China and quickly spread across the globe, causing over 521 million cases of infection and 6.26 million deaths to date. After 2 years, numerous advances have been made. First of all, the preventive vaccine, which has been implemented in record time, is effective in more than 95% of cases. Additionally, in the diagnostic field, there are numerous molecular and antigenic diagnostic kits that are equipped with high sensitivity and specificity. Real Time-PCR-based assays for the detection of viral RNA are currently considered the gold-standard method for SARS-CoV-2 diagnosis and can be used efficiently on pooled nasopharyngeal, or oropharyngeal samples for widespread screening. Moreover, additional, and more advanced molecular methods such as droplet-digital PCR (ddPCR), clustered regularly interspaced short palindromic repeats (CRISPR) and next-generation sequencing (NGS), are currently under development to detect the SARS-CoV-2 RNA. However, as the number of subjects infected with SARS-CoV-2 continuously increases globally, health care systems are being placed under increased stress. Thus, the clinical laboratory plays an important role, helping to select especially asymptomatic individuals who are actively carrying the live replicating virus, with fast and non-invasive molecular technologies. Recent diagnostic strategies, other than molecular methods, have been adopted to either detect viral antigens, i.e., antigen-based immunoassays, or human anti-SARS-CoV-2 antibodies, i.e., antibody-based immunoassays, in nasal or oropharyngeal swabs, as well as in blood or saliva samples. However, the role of mucosal sIgAs, which are essential in the control of viruses entering the body through mucosal surfaces, remains to be elucidated, and in particular the role of the immune response in counteracting SARS-CoV-2 infection, primarily at the site(s) of virus entry that appears to be promising.

Case Report: "Area of Focus" Atypical Trichinellosis and Fascioliasis Coinfection

Parasitic co-infection is commonly observed in natural populations, yet rare in the laboratory. Multiparasitism can have negative effects on the host, ranging from the atypical manifestations to increased mortality, consequently, it may be misdiagnosed and treated with unsuitable anthelmintic medicines. Therefore, reliable diagnosis is critical for appropriate treatment of parasitic co-infection. Herein, we report a case of a 31-year-old woman with persistent eosinophilia and hypoechoic liver lesion on ultrasound. The microscopic examination of multiple stool specimens did not find any pathogens. The patient had serum specific anti-Trichinella IgG antibody by Dot enzyme-linked immunosorbent assay (Dot-ELISA). After treatment with albendazole, contrast-enhanced magnetic resonance imaging (MRI) revealed more lesions in the liver. Subsequently, liver biopsy was performed in this patient and Fasciola hepatica was identified using metagenomic next-generation sequencing (mNGS) as well as polymerase chain reaction. After treatment with triclabendazole, which is the only anthelmintic drug specifically available against this fluke, her eosinophil count returned normal, and the liver lesions were significantly regressed. This case highlights the diagnostic challenge posed by parasitic co-infection, which merits more in-depth evaluation to confirm the diagnosis.

VPipe: an Automated Bioinformatics Platform for Assembly and Management of Viral Next-Generation Sequencing Data

Next-generation sequencing (NGS) is a powerful tool for detecting and investigating viral pathogens; however, analysis and management of the enormous amounts of data generated from these technologies remains a challenge. Here, we present VPipe (the Viral NGS Analysis Pipeline and Data Management System), an automated bioinformatics pipeline optimized for whole-genome assembly of viral sequences and identification of diverse species. VPipe automates the data quality control, assembly, and contig identification steps typically performed when analyzing NGS data. Users access the pipeline through a secure web-based portal, which provides an easy-to-use interface with advanced search capabilities for reviewing results. In addition, VPipe provides a centralized system for storing and analyzing NGS data, eliminating common bottlenecks in bioinformatics analyses for public health laboratories with limited on-site computational infrastructure. The performance of VPipe was validated through the analysis of publicly available NGS data sets for viral pathogens, generating high-quality assemblies for 12 data sets. VPipe also generated assemblies with greater contiguity than similar pipelines for 41 human respiratory syncytial virus isolates and 23 SARS-CoV-2 specimens. IMPORTANCE Computational infrastructure and bioinformatics analysis are bottlenecks in the application of NGS to viral pathogens. As of September 2021, VPipe has been used by the U.S. Centers for Disease Control and Prevention (CDC) and 12 state public health laboratories to characterize >17,500 and 1,500 clinical specimens and isolates, respectively. VPipe automates genome assembly for a wide range of viruses, including high-consequence pathogens such as SARS-CoV-2. Such automated functionality expedites public health responses to viral outbreaks and pathogen surveillance.

Functional Diversity within Gut Microbiomes: Implications for Conserving Biodiversity

Conservation research has historically been conducted at the macro level, focusing on animals and plants and their role in the wider ecosystem. However, there is a growing appreciation of the importance of microbial communities in conservation. Most microbiome research in conservation thus far has used amplicon sequencing methods to assess the taxonomic composition of microbial communities and inferred functional capabilities from these data. However, as manipulation of the microbiome as a conservation tool becomes more and more feasible, there is a growing need to understand the direct functional consequences of shifts in microbiome composition. This review outlines the latest advances in microbiome research from a functional perspective and how these data can be used to inform conservation strategies. This review will also consider some of the challenges faced when studying the microbiomes of wild animals and how they can be overcome by careful study design and sampling methods. Environmental changes brought about by climate change or direct human actions have the potential to alter the taxonomic composition of microbiomes in wild populations. Understanding how taxonomic shifts affect the function of microbial communities is important for identifying species most threatened by potential disruption to their microbiome. Preservation or even restoration of these functions has the potential to be a powerful tool in conservation biology and a shift towards functional characterisation of gut microbiome diversity will be an important first step.

Recent advances in detection technologies for COVID-19

Corona Virus Disease 2019 (COVID-19) is a highly infectious respiratory illness that was caused by the SARS-CoV-2. It spread around the world in just a few months and became a worldwide pandemic. Quick and accurate diagnosis of infected patients is very important for controlling transmission. In addition to the commonly used Real-time reverse-transcription polymerase chain reaction (RT-PCR) detection techniques, other diagnostic techniques are also emerging endlessly. This article reviews the current diagnostic methods for COVID-19 and discusses their advantages and disadvantages. It provides an important reference for the diagnosis of COVID-19.

Diversity of International High-Risk Clones of Acinetobacter baumannii Revealed in a Russian Multidisciplinary Medical Center during 2017-2019

Acinetobacter baumannii is a dangerous bacterial pathogen possessing the ability to persist on various surfaces, especially in clinical settings, and to rapidly acquire the resistance to a broad spectrum of antibiotics. Thus, the epidemiological surveillance of A. baumannii within a particular hospital, region, and across the world is an important healthcare task that currently usually includes performing whole-genome sequencing (WGS) of representative isolates. During the past years, the dissemination of A. baumannii across the world was mainly driven by the strains belonging to two major groups called the global clones or international clones (ICs) of high risk (IC1 and IC2). However, currently nine ICs are already considered. Although some clones were previously thought to spread in particular regions of the world, in recent years this is usually not the case. In this study, we determined five ICs, as well as three isolates not belonging to the major ICs, in one multidisciplinary medical center within the period 2017-2019. We performed WGS using both short- and long-read sequencing technologies of nine representative clinical A. baumannii isolates, which allowed us to determine the antibiotic resistance and virulence genomic determinants, reveal the CRISPR/Cas systems, and obtain the plasmid structures. The phenotypic and genotypic antibiotic resistance profiles are compared, and the possible ways of isolate and resistance spreading are discussed. We believe that the data obtained will provide a better understanding of the spreading and resistance acquisition of the ICs of A. baumannii and further stress the necessity for continuous genomic epidemiology surveillance of this problem-causing bacterial species.

HPV DeepSeq: An Ultra-Fast Method of NGS Data Analysis and Visualization Using Automated Workflows and a Customized Papillomavirus Database in CLC Genomics Workbench

Next-generation sequencing (NGS) has actualized the human papillomavirus (HPV) virome profiling for in-depth investigation of viral evolution and pathogenesis. However, viral computational analysis remains a bottleneck due to semantic discrepancies between computational tools and curated reference genomes. To address this, we developed and tested automated workflows for HPV taxonomic profiling and visualization using a customized papillomavirus database in the CLC Microbial Genomics Module. HPV genomes from Papilloma Virus Episteme were customized and incorporated into CLC “ready-to-use” workflows for stepwise data processing to include: (1) Taxonomic Analysis, (2) Estimate Alpha/Beta Diversities, and (3) Map Reads to Reference. Low-grade (n = 95) and high-grade (n = 60) Pap smears were tested with ensuing collective runtimes: Taxonomic Analysis (36 min); Alpha/Beta Diversities (5 s); Map Reads (45 min). Tabular output conversion to visualizations entailed 1–2 keystrokes. Biodiversity analysis between low- (LSIL) and high-grade squamous intraepithelial lesions (HSIL) revealed loss of species richness and gain of dominance by HPV-16 in HSIL. Integrating clinically relevant, taxonomized HPV reference genomes within automated workflows proved to be an ultra-fast method of virome profiling. The entire process named “HPV DeepSeq” provides a simple, accurate and practical means of NGS data analysis for a broad range of applications in viral research.

Use of Metagenomic Next-Generation Sequencing to Identify Pathogens in Pediatric Osteoarticular Infections

BACKGROUND

Osteoarticular infections (OAIs) are frequently encountered in children. Treatment may be guided by isolation of a pathogen; however, operative cultures are often negative. Metagenomic next-generation sequencing (mNGS) allows for broad and sensitive pathogen detection that is culture-independent. We sought to evaluate the diagnostic utility of mNGS in comparison to culture and usual care testing to detect pathogens in acute osteomyelitis and/or septic arthritis in children.

METHODS

This was a single-site study to evaluate the use of mNGS in comparison to culture to detect pathogens in acute pediatric osteomyelitis and/or septic arthritis. Subjects admitted to a tertiary children's hospital with suspected OAI were eligible for enrollment. We excluded subjects with bone or joint surgery within 30 days of admission or with chronic osteomyelitis. Operative samples were obtained at the surgeon's discretion per standard care (fluid or tissue) and based on imaging and operative findings. We compared mNGS to culture and usual care testing (culture and polymerase chain reaction [PCR]) from the same site.

RESULTS

We recruited 42 subjects over the enrollment period. mNGS of the operative samples identified a pathogen in 26 subjects compared to 19 subjects in whom culture identified a pathogen. In 4 subjects, mNGS identified a pathogen where combined usual care testing (culture and PCR) was negative. Positive predictive agreement and negative predictive agreement both were 93.0% for mNGS.

CONCLUSIONS

In this single-site prospective study of pediatric OAI, we demonstrated the diagnostic utility of mNGS testing in comparison to culture and usual care (culture and PCR) from operative specimens.

New evaluation methods of read mapping by 17 aligners on simulated and empirical NGS data: an updated comparison of DNA- and RNA-Seq data from Illumina and Ion Torrent technologies

During the last (15) years, improved omics sequencing technologies have expanded the scale and resolution of various biological applications, generating high-throughput datasets that require carefully chosen software tools to be processed. Therefore, following the sequencing development, bioinformatics researchers have been challenged to implement alignment algorithms for next-generation sequencing reads. However, nowadays selection of aligners based on genome characteristics is poorly studied, so our benchmarking study extended the “state of art” comparing 17 different aligners. The chosen tools were assessed on empirical human DNA- and RNA-Seq data, as well as on simulated datasets in human and mouse, evaluating a set of parameters previously not considered in such kind of benchmarks. As expected, we found that each tool was the best in specific conditions. For Ion Torrent single-end RNA-Seq samples, the most suitable aligners were CLC and BWA-MEM, which reached the best results in terms of efficiency, accuracy, duplication rate, saturation profile and running time. About Illumina paired-end osteomyelitis transcriptomics data, instead, the best performer algorithm, together with the already cited CLC, resulted Novoalign, which excelled in accuracy and saturation analyses. Segemehl and DNASTAR performed the best on both DNA-Seq data, with Segemehl particularly suitable for exome data. In conclusion, our study could guide users in the selection of a suitable aligner based on genome and transcriptome characteristics. However, several other aspects, emerged from our work, should be considered in the evolution of alignment research area, such as the involvement of artificial intelligence to support cloud computing and mapping to multiple genomes.

Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data

The unprecedented surge of a novel coronavirus in the month of December 2019, named as COVID-19 by the World Health organization has caused a serious impact on the health and socioeconomic activities of the public all over the world. Since its origin, the number of infected and deceased cases has been growing exponentially in almost all the affected countries of the world. The rapid spread of the novel coronavirus across the world results in the scarcity of medical resources and overburdened hospitals. As a result, the researchers and technocrats are continuously working across the world for the inculcation of efficient strategies which may assist the government and healthcare system in controlling and managing the spread of the COVID-19 pandemic. Therefore, this study provides an extensive review of the ongoing strategies such as diagnosis, prediction, drug and vaccine development and preventive measures used in combating the COVID-19 along with technologies used and limitations. Moreover, this review also provides a comparative analysis of the distinct type of data, emerging technologies, approaches used in diagnosis and prediction of COVID-19, statistics of contact tracing apps, vaccine production platforms used in the COVID-19 pandemic. Finally, the study highlights some challenges and pitfalls observed in the systematic review which may assist the researchers to develop more efficient strategies used in controlling and managing the spread of COVID-19.

HIV-1 Drug Resistance Genotyping in Resource Limited Settings: Current and Future Perspectives in Sequencing Technologies

Affordable, sensitive, and scalable technologies are needed for monitoring antiretroviral treatment (ART) success with the goal of eradicating HIV-1 infection. This review discusses use of Sanger sequencing and next generation sequencing (NGS) methods for HIV-1 drug resistance (HIVDR) genotyping, focusing on their use in resource limited settings (RLS). Sanger sequencing remains the gold-standard method for detecting HIVDR mutations of clinical relevance but is mainly limited by high sequencing costs and low-throughput. NGS is becoming a more common sequencing method, with the ability to detect low-abundance drug-resistant variants and reduce per sample costs through sample pooling and massive parallel sequencing. However, use of NGS in RLS is mainly limited by infrastructure costs. Given these shortcomings, our review discusses sequencing technologies for HIVDR genotyping, focusing on common in-house and commercial assays, challenges with Sanger sequencing in keeping up with changes in HIV-1 treatment programs, as well as challenges with NGS that limit its implementation in RLS and in clinical diagnostics. We further discuss knowledge gaps and offer recommendations on how to overcome existing barriers for implementing HIVDR genotyping in RLS, to make informed clinical decisions that improve quality of life for people living with HIV.

Centralised or Localised Pathogen Whole Genome Sequencing: Lessons Learnt From Implementation in a Clinical Diagnostic Laboratory

Whole genome sequencing (WGS) has had widespread use in the management of microbial outbreaks in a public health setting. Current models encompass sending isolates to a central laboratory for WGS who then produce a report for various levels of government. This model, although beneficial, has multiple shortcomings especially for localised infection control interventions and patient care. One reason for the slow rollout of WGS in clinical diagnostic laboratories has been the requirement for professionally trained personal in both wet lab techniques and in the analysis and interpretation of data, otherwise known as bioinformatics. A further bottleneck has been establishment of regulations in order to certify clinical and technical validity and demonstrate WGS as a verified diagnostic test. Nevertheless, this technology is far superior providing information that would normally require several diagnostic tests to achieve. An obvious barrier to informed outbreak tracking is turnaround time and requires isolates to be sequenced in real-time to rapidly identify chains of transmission. One way this can be achieved is through onsite hospital sequencing with a cumulative analysis approach employed. Onsite, as opposed to centralised sequencing, has added benefits including the increased agility to combine with local infection control staff to iterate through the data, finding links that aide in understanding transmission chains and inform infection control strategies. Our laboratory has recently instituted a pathogen WGS service within a diagnostic laboratory, separate to a public health laboratory. We describe our experience, address the challenges faced and demonstrate the advantages of de-centralised sequencing through real-life scenarios.

AFM-Based Correlative Microscopy Illuminates Human Pathogens

Microbes have an arsenal of virulence factors that contribute to their pathogenicity. A number of challenges remain to fully understand disease transmission, fitness landscape, antimicrobial resistance and host heterogeneity. A variety of tools have been used to address diverse aspects of pathogenicity, from molecular host-pathogen interactions to the mechanisms of disease acquisition and transmission. Current gaps in our knowledge include a more direct understanding of host-pathogen interactions, including signaling at interfaces, and direct phenotypic confirmation of pathogenicity. Correlative microscopy has been gaining traction to address the many challenges currently faced in biomedicine, in particular the combination of optical and atomic force microscopy (AFM). AFM, generates high-resolution surface topographical images, and quantifies mechanical properties at the pN scale under physiologically relevant conditions. When combined with optical microscopy, AFM probes pathogen surfaces and their physical and molecular interaction with host cells, while the various modes of optical microscopy view internal cellular responses of the pathogen and host. Here we review the most recent advances in our understanding of pathogens, recent applications of AFM to the field, how correlative AFM-optical microspectroscopy and microscopy have been used to illuminate pathogenicity and how these methods can reach their full potential for studying host-pathogen interactions.

Next Generation Sequencing for the Prediction of the Antibiotic Resistance in Helicobacter pylori: A Literature Review

Background and aims: Only a few antimicrobials are effective against H. pylori, and antibiotic resistance is an increasing problem for eradication therapies. In 2017, the World Health Organization categorized clarithromycin resistant H. pylori as a "high-priority" bacterium. Standard antimicrobial susceptibility testing can be used to prescribe appropriate therapies but is currently recommended only after the second therapeutic failure. H. pylori is, in fact, a "fastidious" microorganism; culture methods are time-consuming and technically challenging. The advent of molecular biology techniques has enabled the identification of molecular mechanisms underlying the observed phenotypic resistance to antibiotics in H. pylori. The aim of this literature review is to summarize the results of original articles published in the last ten years, regarding the use of Next Generation Sequencing, in particular of the whole genome, to predict the antibiotic resistance in H. pylori.Methods: a literature research was made on PubMed. The research was focused on II and III generation sequencing of the whole H. pylori genome. Results: Next Generation Sequencing enabled the detection of novel, rare and complex resistance mechanisms. The prediction of resistance to clarithromycin, levofloxacin and amoxicillin is accurate; for other antimicrobials, such as metronidazole, rifabutin and tetracycline, potential genetic determinants of the resistant status need further investigation.

Detection and Typing of Human Enteroviruses from Clinical Samples by Entire-Capsid Next Generation Sequencing

There are increasing concerns of infections by enteroviruses (EVs) causing severe disease in humans. EV diagnostic laboratory methods show differences in sensitivity and specificity as well as the level of genetic information provided. We examined a detection method for EVs based on next generation sequencing (NGS) analysis of amplicons covering the entire capsid coding region directly synthesized from clinical samples. One hundred and twelve clinical samples from England; previously shown to be positive for EVs, were analyzed. There was high concordance between the results obtained by the new NGS approach and those from the conventional Sanger method used originally with agreement in the serotypes identified in the 83 samples that were typed by both methods. The sensitivity and specificity of the NGS method compared to those of the conventional Sanger sequencing typing assay were 94.74% (95% confidence interval, 73.97% to 99.87%) and 97.85% (92.45% to 99.74%) for Enterovirus A, 93.75% (82.80% to 98.69%) and 89.06% (78.75% to 95.49%) for Enterovirus B, 100% (59.04% to 100%) and 98.10% (93.29% to 99.77%) for Enterovirus C, and 100% (75.29% to 100%) and 100% (96.34% to 100%) for Enterovirus D. The NGS method identified five EVs in previously untyped samples as well as additional viruses in some samples, indicating co-infection. This method can be easily expanded to generate whole-genome EV sequences as we show here for EV-D68. Information from capsid and whole-genome sequences is critical to help identifying the genetic basis for changes in viral properties and establishing accurate spatial-temporal associations between EV strains of public health relevance.

Rapid nanopore-based DNA sequencing protocol of antibiotic-resistant bacteria for use in surveillance and outbreak investigation

Outbreak investigations are essential to control and prevent the dissemination of pathogens. This study developed and validated a complete analysis protocol for faster and more accurate surveillance and outbreak investigations of antibiotic-resistant microbes based on Oxford Nanopore Technologies (ONT) DNA whole-genome sequencing. The protocol was developed using 42 methicillin-resistant Staphylococcus aureus (MRSA) isolates identified from former well-characterized outbreaks. The validation of the protocol was performed using Illumina technology (MiSeq, Illumina). Additionally, a real-time outbreak investigation of six clinical S. aureus isolates was conducted to test the ONT-based protocol. The suggested protocol includes: (1) a 20 h sequencing run; (2) identification of the sequence type (ST); (3) de novo genome assembly; (4) polishing of the draft genomes; and (5) phylogenetic analysis based on SNPs. After the sequencing run, it was possible to identify the ST in 2 h (20 min per isolate). Assemblies were achieved after 4 h (40 min per isolate) while the polishing was carried out in 7 min per isolate (42 min in total). The phylogenetic analysis took 0.6 h to confirm an outbreak. Overall, the developed protocol was able to at least discard an outbreak in 27 h (mean) after the bacterial identification and less than 33 h to confirm it. All these estimated times were calculated considering the average time for six MRSA isolates per sequencing run. During the real-time S. aureus outbreak investigation, the protocol was able to identify two outbreaks in less than 31 h. The suggested protocol enables identification of outbreaks in early stages using a portable and low-cost device along with a streamlined downstream analysis, therefore having the potential to be incorporated in routine surveillance analysis workflows. In addition, further analysis may include identification of virulence and antibiotic resistance genes for improved pathogen characterization.

Identification of differentially expressed lncRNAs as potential plasma biomarkers for active tuberculosis

BACKGROUND

Tuberculosis, one of the deadliest infectious diseases worldwide, is difficult to diagnose. As long noncoding RNAs (lncRNAs) were demonstrated to be promising biomarkers, we aimed to identify lncRNAs in plasma as potential biomarkers for tuberculosis.

METHODS

We analyzed a GEO dataset (GSE94907) to identify the differential lncRNAs in serum exosomes between active tuberculosis (ATB) patients and healthy controls. To search for promising candidates that can be used for tuberculosis diagnosis, we excluded low-abundance lncRNAs using a cutoff value of FPKM >5. Four lncRNAs were selected for validation using real-time quantitative PCR in 69 ATB patients and 69 healthy individuals. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of these lncRNAs for ATB.

RESULTS

Integrated analysis of the GEO dataset and NONCODE database identified nine dysregulated lncRNAs in ATB patient serum exosomes. Compared with the heathy controls, NONHSAT101518.2, NONHSAT067134.2, NONHSAT148822.1 and NONHSAT078957.2 were significantly downregulated in ATB patient plasma. ROC curve analysis suggests that these four lncRNAs can discriminate ATB from healthy individuals with high specificity and sensitivity.

CONCLUSION

We identified four differentially expressed lncRNAs in ATB patient plasma that can be used as potential diagnostic biomarkers of ATB.

Effect of low-passage number on dengue consensus genomes and intra-host variant frequencies

Intra-host single nucleotide variants (iSNVs) have been increasingly used in genomic epidemiology to increase phylogenetic resolution and reconstruct fine-scale outbreak dynamics. These analyses are preferably done on sequence data from direct clinical samples, but in many cases due to low viral loads, there might not be enough genetic material for deep sequencing and iSNV determination. Isolation of the virus from clinical samples with low-passage number increases viral load, but few studies have investigated how dengue virus (DENV) culture isolation from a clinical sample impacts the consensus sequence and the intra-host virus population frequencies. In this study, we investigate consensus and iSNV frequency differences between DENV sequenced directly from clinical samples and their corresponding low-passage isolates. Twenty five DENV1 and DENV2 positive sera and their corresponding viral isolates (T. splendens inoculation and C6/36 passage) were obtained from a prospective cohort study in the Philippines. These were sequenced on MiSeq with minimum nucleotide depth of coverage of 500×, and iSNVs were detected using LoFreq. For both DENV1 and DENV2, we found a maximum of one consensus nucleotide difference between clinical sample and isolate. Interestingly, we found that iSNVs with frequencies ≥5 % were often preserved between the samples, and that the number of iSNV positions, and sample diversity, at this frequency cutoff did not differ significantly between the sample pairs (clinical sample and isolate) in either DENV1 or DENV2 data. Our results show that low-passage DENV isolate consensus genomes are largely representative of their direct sample parental viruses, and that low-passage isolates often mirror high frequency within-host variants from direct samples.

Species-Specific Immunoassay Aids Identification of Pathogen and Tracks Infectivity in Foot Infection

BACKGROUND

Conventional bacterial cultures frequently fail to identify the dominant pathogen in polymicrobial foot infections, in which Staphylococcus aureus is the most common infecting pathogen. Previous work has shown that species-specific immunoassays may be able to identify the main pathogen in musculoskeletal infections. We sought to investigate the clinical applicability of a S. aureus immunoassay to accurately identify the infecting pathogen and monitor its infectivity longitudinally in foot infection. We hypothesized that this species-specific immunoassay could aid in the diagnosis of S. aureus and track the therapeutic response in foot infections.

METHODS

From July 2015 to July 2019, 83 infected foot ulcer patients undergoing surgical intervention (debridement or amputation) were recruited and blood was drawn at 0, 4, 8, and 12 weeks. Whole blood was analyzed for S. aureus-specific serum antibodies (mix of historic and new antibodies) and plasmablasts were isolated and cultured to quantify titers of newly synthesized antibodies (NSAs). Anti-S. aureus antibody titers were compared with culture results to assess their concordance in identifying S. aureus as the pathogen. The NSA titer changes at follow-ups were compared with wound healing status to evaluate concordance between evolving host immune response and clinically resolving or relapsing infection.

RESULTS

Analysis of serum for anti-S. aureus antibodies showed significantly increased titers of 3 different anti-S. aureus antibodies, IsdH (P = .037), ClfB (P = .025), and SCIN (P = .005), in S. aureus culture-positive patients compared with culture-negative patients. Comparative analysis of combining antigens for S. aureus infection diagnosis increased the concordance further. During follow-up, changes of NSA titers against a single or combination of S. aureus antigens significantly correlated with clinically resolving or recurring infection represented by wound healing status.

CONCLUSION

In the management of foot infection, the use of S. aureus-specific immunoassay may aid in diagnosis of the dominant pathogen and monitoring of the host immune response against a specific pathogen in response to treatment. Importantly, this immunoassay could detect recurrent foot infection, which may guide a surgeon's decision to intervene.

LEVEL OF EVIDENCE

Level II, prospective comparative study.

Emerging Options for the Diagnosis of Bacterial Infections and the Characterization of Antimicrobial Resistance

Precise and rapid identification and characterization of pathogens and antimicrobial resistance patterns are critical for the adequate treatment of infections, which represent an increasing problem in intensive care medicine. The current situation remains far from satisfactory in terms of turnaround times and overall efficacy. Application of an ineffective antimicrobial agent or the unnecessary use of broad-spectrum antibiotics worsens the patient prognosis and further accelerates the generation of resistant mutants. Here, we provide an overview that includes an evaluation and comparison of existing tools used to diagnose bacterial infections, together with a consideration of the underlying molecular principles and technologies. Special emphasis is placed on emerging developments that may lead to significant improvements in point of care detection and diagnosis of multi-resistant pathogens, and new directions that may be used to guide antibiotic therapy.

A Department of Defense Laboratory Consortium Approach to Next Generation Sequencing and Bioinformatics Training for Infectious Disease Surveillance in Kenya

Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants) noted significant median gains in knowledge domains related to NGS targeted sequencing, bioinformatics for genome assembly, and sequence quality assessment. The participants also reported that the information on study design, sample preparation, sequencing quality control, data quality assessment, reporting, and basic and advanced bioinformatics analysis were the most useful information presented in the training. While longer-term evaluations are planned, the training resulted in significant short-term improvement of a laboratory’s self-reported wet lab and bioinformatics capabilities. This framework can be used for future DoD laboratory development in the area of NGS and BI for infectious disease surveillance, ultimately enhancing this global DoD capability.

Characterization of methicillin-resistant Staphylococcus aureus through genomics approach

In the present study, a total of 35 S. aureus isolates collected from two different geographical locations viz., Germany and Hungary were tested for their methicillin-resistant phenotype which revealed a high incidence of methicillin-resistant S. aureus. The quantitative test for biofilm production revealed that 73.3% of isolates were biofilm producers. The isolates were further characterized using a set of biochemical and genotypic methods such as amplification and analysis of S. aureus species-specific sequence and mecA gene. The 33 mecA positive isolates were then characterized by the amplification of SCCmec and pvl toxin genes. Further, based on the biofilm-forming phenotype, 15 isolates were selected and characterized through PCR–RFLP of coa gene, polymorphism of spa gene and amplification of biofilm-associated genes. The dendrogram prepared from the results of both biochemical and genotypic analyses of the 15 isolates showed that except for the isolates SA G5 and SA H29, the rest of the isolates grouped themselves according to their locations. Thus, the two isolates were selected for further characterization through whole-genome sequencing. Comparative genome analysis revealed that SA G5 and SA H29 have 97.20% ANI values with 2344 gene clusters (core-genome) of which 16 genes were related to antibiotic resistance genes and 57 genes encode virulence factors. The highest numbers of singleton genes were found in SA H29 that encodes proteins for virulence, resistance, mobile elements, and lanthionine biosynthesis. The high-resolution phylogenetic trees generated based on shared proteins and SNPs revealed a clear difference between the two strains and can be useful in distinguishing closely related genomes. The present study demonstrated that the whole-genome sequence analysis technique is required to get a better insight into the MRSA strains which would be helpful in improving diagnostic investigations in real-time to improve patient care.

COVID-19 diagnostic testing: Technology perspective

The corona virus disease 2019 (COVID-19) is a highly contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). More than 18 million people were infected with a total of 0.7 million deaths in ∼188 countries. Controlling the spread of SARS-CoV-2 is therefore inherently dependent on identifying and isolating infected individuals, especially since COVID-19 can result in little to no symptoms. Here, we provide a comprehensive review of the different primary technologies used to test for COVID-19 infection, discuss the advantages and disadvantages of each technology, and highlight the studies that have employed them. We also describe technologies that have the potential to accelerate SARS-CoV-2 detection in the future, including digital PCR, CRISPR, and microarray. Finally, remaining challenges in COVID-19 diagnostic testing are discussed, including (a) the lack of universal standards for diagnostic testing; (b) the identification of appropriate sample collection site(s); (c) the difficulty in performing large population screening; and (d) the limited understanding of SARS-COV-2 viral invasion, replication, and transmission.

Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing

External quality assessment (EQA) is a keystone element in the validation and implementation of next generation sequencing (NGS)-based HIV drug resistance testing (DRT). Software validation and evaluation is a critical element in NGS EQA programs. While the development, sharing, and adoption of wet lab protocols is coupled with the increasing access to NGS technology worldwide, rendering it easy to produce NGS data for HIV-DRT, bioinformatic data analysis remains a bottleneck for most of the diagnostic laboratories. Several computational tools have been made available, via free or commercial sources, to automate the conversion of raw NGS data into an actionable clinical report. Although different software platforms yield equivalent results when identical raw NGS datasets are analyzed for variations at higher abundance, discrepancies arise when variations at lower frequencies are considered. This implies that validation and performance assessment of the bioinformatics tools applied in NGS HIV-DRT is critical, and the origins of the observed discrepancies should be determined. Well-characterized reference NGS datasets with ground truth on the genotype composition at all examined loci and the exact frequencies of HIV variations they may harbor, so-called dry panels, would be essential in such cases. The strategic design and construction of such panels are challenging but imperative tasks in support of EQA programs for NGS-based HIV-DRT and the validation of relevant bioinformatics tools. Here, we present criteria that can guide the design of such dry panels, which were discussed in the Second International Winnipeg Symposium themed for EQA strategies for NGS HIVDR assays.

Next-Generation Sequencing of the Whole Bacterial Genome for Tracking Molecular Insight into the Broad-Spectrum Antimicrobial Resistance of Helicobacter pylori Clinical Isolates from the Democratic Republic of Congo

Antimicrobial susceptibility testing (AST) is increasingly needed to guide the Helicobacter pylori (H. pylori) treatment but remains laborious and unavailable in most African countries. To assess the clinical relevance of bacterial whole genome sequencing (WGS)-based methods for predicting drug susceptibility in African H. pylori, 102 strains isolated from the Democratic Republic of Congo were subjected to the phenotypic AST and next-generation sequencing (NGS). WGS was used to screen for the occurrence of genotypes encoding antimicrobial resistance (AMR). We noted the broad-spectrum AMR of H. pylori (rates from 23.5 to 90.0%). A WGS-based method validated for variant discovery in AMR-related genes (discovery rates of 100%) helped in identifying mutations of key genes statistically related to the phenotypic AMR. These included mutations often reported in Western and Asian populations and, interestingly, several putative AMR-related new genotypes in the pbp1A (e.g., T558S, F366L), gyrA (e.g., A92T, A129T), gyrB (e.g., R579C), and rdxA (e.g., R131_K166del) genes. WGS showed high performance for predicting AST phenotypes, especially for amoxicillin, clarithromycin, and levofloxacin (Youden's index and Cohen's Kappa > 0.80). Therefore, WGS is an accurate alternative to the phenotypic AST that provides substantial decision-making information for public health policy makers and clinicians in Africa, while providing insight into AMR mechanisms for researchers.

Development and Application of Performance Assessment Criteria for Next-Generation Sequencing-Based HIV Drug Resistance Assays

Next-generation sequencing (NGS)-based HIV drug resistance (HIVDR) assays outperform conventional Sanger sequencing in scalability, sensitivity, and quantitative detection of minority resistance variants. Thus far, HIVDR assays have been applied primarily in research but rarely in clinical settings. One main obstacle is the lack of standardized validation and performance evaluation systems that allow regulatory agencies to benchmark and accredit new assays for clinical use. By revisiting the existing principles for molecular assay validation, here we propose a new validation and performance evaluation system that helps to both qualitatively and quantitatively assess the performance of an NGS-based HIVDR assay. To accomplish this, we constructed a 70-specimen proficiency test panel that includes plasmid mixtures at known ratios, viral RNA from infectious clones, and anonymized clinical specimens. We developed assessment criteria and benchmarks for NGS-based HIVDR assays and used these to assess data from five separate MiSeq runs performed in two experienced HIVDR laboratories. This proposed platform may help to pave the way for the standardization of NGS HIVDR assay validation and performance evaluation strategies for accreditation and quality assurance purposes in both research and clinical settings.

External Quality Assessment for Next-Generation Sequencing-Based HIV Drug Resistance Testing: Unique Requirements and Challenges

Over the past decade, there has been an increase in the adoption of next generation sequencing (NGS) technologies for HIV drug resistance (HIVDR) testing. NGS far outweighs conventional Sanger sequencing as it has much higher throughput, lower cost when samples are batched and, most importantly, significantly higher sensitivities for variants present at low frequencies, which may have significant clinical implications. Despite the advantages of NGS, Sanger sequencing remains the gold standard for HIVDR testing, largely due to the lack of standardization of NGS-based HIVDR testing. One important aspect of standardization includes external quality assessment (EQA) strategies and programs. Current EQA for Sanger-based HIVDR testing includes proficiency testing where samples are sent to labs and the performance of the lab conducting such assays is evaluated. The current methods for Sanger-based EQA may not apply to NGS-based tests because of the fundamental differences in their technologies and outputs. Sanger-based genotyping reports drug resistance mutations (DRMs) data as dichotomous, whereas NGS-based HIVDR genotyping also reports DRMs as numerical data (percent abundance). Here we present an overview of the need to develop EQA for NGS-based HIVDR testing and some unique challenges that may be encountered.