Third generation sequencing technologies applied to diagnostic microbiology: benefits and challenges in applications and data analysis

Third generation sequencing transforming plant genome research: Current trends and challenges

In recent years, third-generation sequencing (TGS) technologies have transformed genomics and transcriptomics research, providing novel opportunities for significant discoveries. The long-read sequencing platforms, with their unique advantages over next-generation sequencing (NGS), including a definitive protocol, reduced operational time, and real-time sequencing, possess the potential to transform plant genomics. TGS optimizes and enhances the efficiency of data analysis by removing the necessity for time-consuming assembly tools. The current review examines the development and application of bioinformatics tools for data analysis and annotation, driven by the rapid advancement of TGS platforms like Oxford Nanopore Technologies and Pacific Biosciences. Transcriptome analysis utilizing TGS has been extensively employed to elucidate complex plant transcriptomes and genomes, particularly those characterized by high frequencies of duplicated genomes and repetitive sequences. As a result, current methodologies that allow for generating transcriptomes and comprehensive whole-genome sequences of complex plant genomes employing tailored hybrid sequencing techniques that integrate NGS and TGS technologies have been emphasized herein. This paper, thus, articulates a vision for a future in which TGS effectively addresses the challenges faced in plant research, offering a comprehensive understanding of its advantages, applications, limitations, and promising prospects.

Dysbiosis Signature of Fecal Microbiota in Patients with Pancreatic Adenocarcinoma and Pancreatic Intraductal Papillary Mucinous Neoplasms

Pancreatic cancer (PC) ranks as the seventh leading cause of cancer-related deaths, with approximately 500,000 new cases reported in 2020. Existing strategies for early PC detection primarily target individuals at high risk of developing the disease. Nevertheless, there is a pressing need to identify innovative clinical approaches and personalized treatments for effective PC management. This study aimed to explore the dysbiosis signature of the fecal microbiota in PC and potential distinctions between its Intraductal papillary mucinous neoplasm (IPMN) and pancreatic ductal adenocarcinoma (PDAC) phenotypes, which could carry diagnostic significance. The study enrolled 33 participants, including 22 diagnosed with PDAC, 11 with IPMN, and 24 healthy controls. Fecal samples were collected and subjected to microbial diversity analysis across various taxonomic levels. The findings revealed elevated abundances of Firmicutes and Proteobacteria in PC patients, whereas healthy controls exhibited higher proportions of Bacteroidota. Both LEfSe and Random Forest analyses indicated the microbiome's potential to effectively distinguish between PC and healthy control samples but fell short of differentiating between IPMN and PDAC samples. These results contribute to the current understanding of this challenging cancer type and highlight the applications of microbiome research. In essence, the study provides clear evidence of the gut microbiome's capability to serve as a biomarker for PC detection, emphasizing the steps required for further differentiation among its diverse phenotypes.

The Value of Next-Generation Sequencing in Diagnosis and Therapy of Critically Ill Patients with Suspected Bloodstream Infections: A Retrospective Cohort Study

Bloodstream infection (BSI), a frequent cause of severe sepsis, is a life-threatening complication in critically ill patients and still associated with a high mortality rate. Rapid pathogen identification from blood is crucial for an early diagnosis and the treatment of patients with suspected BSI. For this purpose, novel diagnostic tools on the base of genetic analysis have emerged for clinical application. The aim of this study was to assess the diagnostic value of additional next-generation sequencing (NGS) pathogen test for patients with suspected BSI in a surgical ICU and its potential impact on antimicrobial therapy. In this retrospective single-centre study, clinical data and results from blood culture (BC) and NGS pathogen diagnostics were analysed for ICU patients with suspected BSI. Consecutive changes in antimicrobial therapy and diagnostic procedures were evaluated. Results: 41 cases with simultaneous NGS and BC sampling were assessed. NGS showed a statistically non-significant higher positivity rate than BC (NGS: 58.5% (24/41 samples) vs. BC: 21.9% (9/41); p = 0.056). NGS detected eight different potentially relevant bacterial species, one fungus and six different viruses, whereas BC detected four different bacterial species and one fungus. NGS results affected antimicrobial treatment in 7.3% of cases. Conclusions: NGS-based diagnostics have the potential to offer a higher positivity rate than conventional culture-based methods in patients with suspected BSI. Regarding the high cost, their impact on anti-infective therapy is currently limited. Larger randomized prospective clinical multicentre studies are required to assess the clinical benefit of this novel diagnostic technology.

Distribution of drug-resistant genes in alveolar lavage fluid from patients with psittacosis and traceability analysis of causative organisms

Background

Chlamydia psittaci is a small bacterium often found in birds, including poultry, and domesticated mammals, which causes psittacosis (or parrot fever) in humans. Different strains of C. psittaci respond variably to antibiotics, suggesting a possible risk of antibiotic resistance. In general, different genotypes of C. psittaci have relatively stable hosts and different pathogenicity.

Methods

Macrogenomic sequencing was performed using nucleic acids extracted from psittacosis patients' alveolar lavage fluid samples and analyzed for genetic variability and antibiotic resistance genes. Nucleic acid amplification sequences specific to the core coding region of the C. psittaci ompA gene were used, and a phylogenetic tree was constructed with C. psittaci genotypic sequences from other sources, including Chinese published sources. The C. psittaci found in each patient were genotyped by comparing ompA gene sequences. In addition, to better illustrate the relationship between genotype and host of C. psittaci, 60 bird fecal samples were collected from bird-selling stores for screening and C. psittaci typing.

Results

Macrogenomic sequence alignment revealed the presence of resistance genes in varying abundance in samples from all three patients, including C. psittaci resistance gene sequences from two patients that matched those previously published on NCBI. Based on ompA genotyping, two patients were infected with C. psittaci genotype A and one patient was infected with genotype B. All five C. psittaci-positive samples obtained from bird-selling stores were genotype A. Both genotypes are reported to be infectious to humans. The host origin of the samples and the previously reported main sources of each genotype suggested that all but one of the C. psittaci genotype A in this study were derived from parrots, while genotype B was probably derived from chickens.

Conclusion

The presence of bacterial resistance genes in psittacosis patients may affect the efficacy of clinical antibiotic therapy. Focusing on the developmental progression of bacterial resistance genes and differences in the therapeutic efficacy may facilitate effective treatment of clinical bacterial infections. Pathogenicity genotypes (e.g., genotype A and genotype B) are not limited to one animal host, suggesting that monitoring the development and changes of C. psittaci may help prevent transmission to humans.

MALDI Mass Spectrometry Imaging: A Potential Game-Changer in a Modern Microbiology

Nowadays, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) is routinely implemented as the reference method for the swift and straightforward identification of microorganisms. However, this method is not flawless and there is a need to upgrade the current methodology in order to free the routine lab from incubation time and shift from a culture-dependent to an even faster independent culture system. Over the last two decades, mass spectrometry imaging (MSI) gained tremendous popularity in life sciences, including microbiology, due to its ability to simultaneously detect biomolecules, as well as their spatial distribution, in complex samples. Through this literature review, we summarize the latest applications of MALDI-MSI in microbiology. In addition, we discuss the challenges and avenues of exploration for applying MSI to solve current MALDI-TOF MS limits in routine and research laboratories.

RETRACTED: Unraveling the composition and succession of microbial community and its relationship to flavor substances during Xin-flavor baijiu brewing

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the authors. The authors reported unauthorized use of several figures in this paper of copyrighted material from the Daohuaxiang Liquor Co., Ltd. Therefore, the authors are retracting the paper in its entirety. They apologize for any inconvenience this may have caused.

Metagenomic Next-Generation Sequencing vs. Traditional Pathogen Detection in the Diagnosis of Infection After Allogeneic Hematopoietic Stem Cell Transplantation in Children

Infection is a severe complication of allo-HSCT in children, however, the accurate detection of the infection is hard. In this study, we traced the records of 101 pediatric recipients with allo-HSCT to investigate the pathogens of infection, and collected 54 bronchoalveolar lavage fluid, 32 blood, and 15 cerebrospinal fluid samples. In these samples, 87 was with post-transplant infection and 14 without infection. Using the metagenomic next-generation sequencing (mNGS) and traditional pathogen detection, we compared their sensitivity and specificity to detect pathogens of infection. Our results showed that mNGS was more sensitive (89.7%) than conventional pathogen detection (21.8%), with a difference of 67.9% (P < 0.001), However, mNGS was less specific (78.5%) than traditional methods (92.9%), with a difference of 14.4% (P = 0.596). The sensitivity of mNGS for diagnosing pulmonary infections, bloodstream infections or viremia, and CNS infections post-transplant were 91.7, 85.7, and 90.9%, respectively. In contrast, the sensitivity of conventional testing for diagnosing pulmonary infections, bloodstream infections or viremia, and CNS infections post-transplant were 22.9, 21.4, and 18.2%, respectively. There were significant differences in the sensitivity of mNGS and conventional testing in BALF, blood, and CSF samples, with P values of 0.000, 0.000, and 0.002 respectively. Among the patients with pulmonary infection, 11 pathogens were both identified by mNGS and conventional testing, and 33 by mNGS only. The percentage with the mNGS-positive result was 44/48 (91.7%), including viruses (n = 12), bacteria (n = 17), fungi (n = 9) and mixed infections (n = 6). Among the patients diagnosed with fungal pneumonia (n = 9), the most prevalent pathogenic fungi were Pneumocystis jiroveci (n = 6), which were also detected in 4 patients with mixed infectious pneumonia. In the 28 blood specimens of patients with bloodstream infections or viremia, five patients were positive by both mNGS and conventional testing, 19 were positive by mNGS, and 1 was positive by traditional testing only. The percentage with the mNGS-positive results was 24/28 (85.7%), including viruses (n = 12), bacteria (n = 4), fungi (n = 3), and mixed infections (n = 5). Of the 15 CSF specimens enrolled, 11 patients were eventually diagnosed with CNS infections. Ten pathogens were identified by mNGS in the 11 patients, including viruses (n = 8), bacteria (n = 1), and fungi (n = 1). These results suggest that mNGS is more sensitive than conventional pathogen detection for diagnosing infections post HSCT in children which may help the clinic diagnosis. Pneumocystis jiroveci was the most frequent pathogen of pulmonary infections post-transplant, while viruses were the most common pathogens of CNS infections in allo-HSCT recipients.

Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics

Although next-generation sequencing (NGS) technology revolutionized sequencing, offering a tremendous sequencing capacity with groundbreaking depth and accuracy, it continues to demonstrate serious limitations. In the early 2010s, the introduction of a novel set of sequencing methodologies, presented by two platforms, Pacific Biosciences (PacBio) and Oxford Nanopore Sequencing (ONT), gave birth to third-generation sequencing (TGS). The innovative long-read technologies turn genome sequencing into an ease-of-handle procedure by greatly reducing the average time of library construction workflows and simplifying the process of de novo genome assembly due to the generation of long reads. Long sequencing reads produced by both TGS methodologies have already facilitated the decipherment of transcriptional profiling since they enable the identification of full-length transcripts without the need for assembly or the use of sophisticated bioinformatics tools. Long-read technologies have also provided new insights into the field of epitranscriptomics, by allowing the direct detection of RNA modifications on native RNA molecules. This review highlights the advantageous features of the newly introduced TGS technologies, discusses their limitations and provides an in-depth comparison regarding their scientific background and available protocols as well as their potential utility in research and clinical applications.

Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies

A number of studies have shown that the microbial communities of the human body are integral for the maintenance of human health. Advances in next-generation sequencing have enabled rapid and large-scale quantification of the composition of microbial communities in health and disease. Microorganisms mediate diverse host responses including metabolic pathways and immune responses. Using a system biology approach to further understand the underlying alterations of the microbiota in physiological and pathological states can help reveal potential novel therapeutic and diagnostic interventions within the field of synthetic biology. Tools such as biosensors, memory arrays, and engineered bacteria can rewire the microbiome environment. In this article, we review the computational tools used to study microbiome communities and the current limitations of these methods. We evaluate how genome-scale metabolic models (GEMs) can advance our understanding of the microbe-microbe and microbe-host interactions. Moreover, we present how synergies between these system biology approaches and synthetic biology can be harnessed in human microbiome studies to improve future therapeutics and diagnostics and highlight important knowledge gaps for future research in these rapidly evolving fields.

Micropathogen community identification in ticks (Acari: Ixodidae) using third-generation sequencing

Ticks are important vectors that facilitate the transmission of a broad range of micropathogens to vertebrates, including humans. Because of their role in disease transmission, it has become increasingly important to identify and characterize the micropathogen profiles of tick populations. The objective of the present study was to survey the micropathogens of ticks by third-generation metagenomic sequencing using the PacBio Sequel platform. Approximately 46.481 Gbp of raw micropathogen sequence data were obtained from samples from four different regions of Heilongjiang Province, China. The clean consensus sequences were compared with host sequences and filtered at 90% similarity. Most of the identified genomes represent previously unsequenced strains. The draft genomes contain an average of 397,746 proteins predicted to be associated with micropathogens, over 30% of which do not have an adequate match in public databases. In these data, Anaplasma phagocytophilum and Coxiella burnetii were detected in all samples, while Borrelia burgdorferi was detected only in Ixodes persulcatus ticks from G1 samples. Viruses are a key component of micropathogen populations. In the present study, Simian foamy virus, Pustyn virus and Crimean-Congo haemorrhagic fever orthonairovirus were detected in different samples, and more than 10–30% of the viral community in all samples comprised unknown viruses. Deep metagenomic shotgun sequencing has emerged as a powerful tool to investigate the composition and function of complex microbial communities. Thus, our dataset substantially improves the coverage of tick micropathogen genomes in public databases and represents a valuable resource for micropathogen discovery and for studies of tick-borne diseases.

•

The microbial communities from ticks were analysed by third-generation metagenomic sequencing using the PacBio Sequel platform.

•

In these data, Anaplasma phagocytophilum and Coxiella burnetii were found in four groups, and Borrelia burgdorferi was detected only in Ixodes persulcatus ticks from G1 samples. Viruses are a key component of the composition of micropathogens.

•

The third-generation metagenomic sequencing is far superior to second-generation sequencing in genome sequence integrity, and the similarity of the sequences obtained via third-generation metagenomic sequencing for discrimination is unmatched by other sequencing methods.

•

Thus, our dataset substantially improves the coverage of tick micropathogen genomes in public databases and represents a valuable resource for micropathogen discovery and for studies of tick-borne diseases.

Precise diagnosis of Neisseria macacae infective endocarditis assisted by nanopore sequencing

Infective endocarditis caused by Neisseria macacae in humans is extremely rare. We presented here a case of N. macacae infective endocarditis in a 61-year-old man with a native aortic valve infection. N. macacae was isolated from blood culture and was detected by nanopore-based metagenomic sequencing in the vegetations. Finally, the patient recovered completely after surgery and antibiotic therapy.

Current Developments and Challenges in Plant Viral Diagnostics: A Systematic Review

Plant viral diseases are the foremost threat to sustainable agriculture, leading to several billion dollars in losses every year. Many viruses infecting several crops have been described in the literature; however, new infectious viruses are emerging frequently through outbreaks. For the effective treatment and prevention of viral diseases, there is great demand for new techniques that can provide accurate identification on the causative agents. With the advancements in biochemical and molecular biology techniques, several diagnostic methods with improved sensitivity and specificity for the detection of prevalent and/or unknown plant viruses are being continuously developed. Currently, serological and nucleic acid methods are the most widely used for plant viral diagnosis. Nucleic acid-based techniques that amplify target DNA/RNA have been evolved with many variants. However, there is growing interest in developing techniques that can be based in real-time and thus facilitate in-field diagnosis. Next-generation sequencing (NGS)-based innovative methods have shown great potential to detect multiple viruses simultaneously; however, such techniques are in the preliminary stages in plant viral disease diagnostics. This review discusses the recent progress in the use of NGS-based techniques for the detection, diagnosis, and identification of plant viral diseases. New portable devices and technologies that could provide real-time analyses in a relatively short period of time are prime important for in-field diagnostics. Current development and application of such tools and techniques along with their potential limitations in plant virology are likewise discussed in detail.

Bacterial Succession through the Artisanal Process and Seasonal Effects Defining Bacterial Communities of Raw-Milk Adobera Cheese Revealed by High Throughput DNA Sequencing

The bacterial community of the artisanal Adobera cheese from Los Altos de Jalisco was described through high-throughput sequencing of 16S rRNA gene libraries. Samples were collected in two different seasons (dry and rainy) during four key steps of the manufacturing process (raw milk, fresh curd, matured curd, and cheese). Bacterial diversity was higher in early steps in comparison with the final elaboration stages. Firmicutes and Proteobacteria were the most abundant phyla, strongly represented by the Streptococcaceae, Enterobacteriaceae and Lactobacillaceae families, and core bacteria genera such as Streptococcus spp., Lactococcus spp., and Lactobacillus spp. Undesirable bacteria, including Pseudomonas spp. and Acinetobacter spp., were also detected in raw milk but almost undetectable at the end of the cheese manufacturing process, and seemed to be displaced by lactic-acid bacteria-related genera. Seasonal effects were observed on the community structure but did not define the core microbiota composition. Predictive metabolism was related to membrane transport, and amino-acid, lipid, and carbohydrate metabolism pathways. Our results contribute to deduce the role of bacteria involved in Adobera cheese manufacturing in terms of the metabolism involved, cheese microbial safety, and how undesirable bacterial populations could be regulated by process standardization as a potential tool to improve safety.

Emerging priorities for microbial metagenome research

Overwhelming anthropogenic activities lead to deterioration of natural resources and the environment. The microorganisms are considered desirable, due to their suitability for easy genetic manipulation and handling. With the aid of modern biotechnological techniques, the culturable microorganisms have been widely exploited for the benefit of mankind. Metagenomics, a powerful tool to access the abundant biodiversity of the environmental samples including the unculturable microbes, to determine microbial diversity and population structure, their ecological roles and expose novel genes of interest. This review focuses on the microbial adaptations to the adverse environmental conditions, metagenomic techniques employed towards microbial biotechnology. Metagenomic approach helps to understand microbial ecology and to identify useful microbial derivatives like antibiotics, toxins, and enzymes with diverse and enhanced function. It also summarizes the application of metagenomics in clinical diagnosis, improving microbial ecology, therapeutics, xenobiotic degradation and impact on agricultural crops.

[RETRACTED: High-throughput sequencing in diagnostics and prevention of herpes simplex virus infection (Herpesviridae, Alphaherpesvirinae, Simplexvirus, Human alphaherpesvirus 1)]

RETRACTEDHerpes simplex viruses types 1 (HSV-1) and 2 (HSV-2) are among the most common viruses in the human population. The clinical manifestations of HSV infection vary widely, which necessitates reliable molecular methods for the timely diagnosis of herpes virus infection, as well as for detection of mutations in the genes responsible for drug resistance. PCR is often unable to detect HSV isolates with nucleotide substitutions at the primer binding site. Sanger sequencing of the whole genome reveals mutations mainly at the consensus level, which accumulate at advanced stages of viral infection. High-throughput sequencing (HTS, next generation sequencing) offers an obvious advantage both in early diagnosis of herpes virus infection and identification of HSV variants.

Comparative sequencing data analysis of Ion Torrent and MinION sequencing platforms using a clinical diagnostic haematology panel

INTRODUCTION

Currently, two second-generation sequencing platforms-Ion Torrent and Illumina are being widely used for clinical testing and reporting of human samples. However, third-generation long read platforms like single molecule (PacBio) or direct sequencing (Nanopore) are gaining widespread interest in clinical genomics.

AIMS AND OBJECTIVES

The current study attempts to analyse and compare MinION sequencing data with Ion Torrent data, using a haematology ampliseq panel, to shed light on its current standing in reporting of clinical diagnostic samples.

METHODOLOGY

A custom targeted Next-generation sequencing ampliseq panel comprising of 33 genes related to detection of inherited bone marrow failure syndrome cases was used to sequence five samples on both Ion Torrent and Oxford MinION platforms. The resulting data were analysed for output, quality and variant metrics across both platforms independently.

RESULTS

Overall, MinION produced longer reads (range 108-7227 bp) than Ion Torrent (25-580 bp). Moreover, it generated more reads than Ion Torrent in high %GC content (P < .005) or repeat regions. But Ion Torrent had much lower error rate of 1.59% compared with MinION's 20.31%. Despite high error, MinION platform was able to identify and report the pathogenic variant in all samples.

DISCUSSION AND CONCLUSION

The extremely long read lengths of MinION sequencers and better coverage in difficult to sequence regions give it an edge in generating contig free whole-genome sequences. However, the pore technology and chemistry of MinION needs further tuning to reduce error rate before it can be incorporated for clinical testing and reporting of human samples.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

Highly sensitive and simultaneous detection of microRNAs in serum using stir-bar assisted magnetic DNA nanospheres-encoded probes

There are critical interests in the detection of microRNA (miRNA) because it can be a blood-borne biomarker, but analytical strategies are still limited by its small size, high sequence homology among family members and low abundance. In this work, three-dimensional magnetic DNA nanospheres were synthesized and immobilized on a gold stir-bar as encoded probes for miRNA capture and signal amplification. Electrochemical tags-labeled DNAs were immobilized on gold coated magnetic nanospheres via a hyperbranched hybridization chain reaction (HHCR). Subsequently, the magnetic DNA nanospheres were immobilized on the gold stir-bar as encoded probes. Target miRNAs were captured on the surface of the stir-bar by replacing the magnetic DNA nanospheres-encoded probes, and the probes were magnetically enriched for highly sensitive and selective electrochemical detection. The gold stir-bar assisted magnetic DNA nanospheres-encoded probes possess dual functions: They are as a nanocarrier to increase the loading amounts of HHCR products, and they are also a platform for efficient electrochemical signal amplification via magnetic enrichment. The method was successfully applied for the detection of miRNA21 and miRNA155 in a wide linear range of 5 fM to 2 nM, and with detection limits of 1.5 fM and 1.8 fM, respectively. The preliminary application of the method suggests that it has great potential in the detection of miRNAs in serum samples.

Understanding the Promises and Hurdles of Metagenomic Next-Generation Sequencing as a Diagnostic Tool for Infectious Diseases

Agnostic metagenomic next-generation sequencing (mNGS) has emerged as a promising single, universal pathogen detection method for infectious disease diagnostics. This methodology allows for identification and genomic characterization of bacteria, fungi, parasites, and viruses without the need for a priori knowledge of a specific pathogen directly from clinical specimens. Although there are increasing reports of mNGS successes, several hurdles need to be addressed, such as differentiation of colonization from infection, extraneous sources of nucleic acid, method standardization, and data storage, protection, analysis, and interpretation. As more commercial and clinical microbiology laboratories develop mNGS assays, it is important for treating practitioners to understand both the power and limitations of this method as a diagnostic tool for infectious diseases.

Metagenomic next-generation sequencing diagnosis of peripheral pulmonary infectious lesions through virtual navigation, radial EBUS, ultrathin bronchoscopy, and ROSE

Objective

To evaluate the efficacy of combined rapid on-site evaluation of cytology (ROSE), ultrathin bronchoscopy, virtual bronchoscopic navigation, radial endobronchial ultrasound (EBUS), and metagenomic next-generation sequencing (mNGS) for diagnosis of peripheral pulmonary infectious lesions.

Methods

Specimens from patients with peripheral lung infection were obtained by transbronchial lung biopsy (TBLB) and bronchoalveolar lavage (BAL), and mNGS was used to detect pathogenic microorganisms. The sensitivity and specificity of mNGS were compared between TBLB tissue and BAL fluid.

Results

The most common pathogens of pulmonary infectious lesions in this study were Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii. The specificity of mNGS was higher in TBLB tissue than in BAL fluid, but mNGS of BAL fluid had higher sensitivity.

Conclusions

The combination of ROSE, ultrathin bronchoscopy, virtual bronchoscopic navigation, radial EBUS, and mNGS technology yielded high efficacy for the diagnosis of peripheral pulmonary infectious lesions. TBLB and BAL specimens have respective advantages in specificity and sensitivity for mNGS analysis.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Herpes Simplex Virus Disease Management and Diagnostics in the Era of High-Throughput Sequencing

Herpes simplex virus (HSV) serotypes 1 and 2 are among the most widespread human viruses. HSV disease has a complex phenotype, with symptoms that can range from mild lesions to encephalitis. In the clinical setting, this diversity of outcomes poses a major challenge, making timely disease diagnosis and treatment challenging. High-throughput sequencing (HTS) has been one of the breakthrough technologies in the modern era of molecular biology, and it is revolutionizing the study of pathogen biology and clinical diagnostics. Here, we review recent studies that have used HTS to answer questions related to the evolution of drug resistance, transmission and spread, virulence marker identification, and the design of better antiviral therapeutics for HSV. We also highlight practical considerations for handling computational analysis of HSV genomes and adoption of HTS as a routine diagnostic procedure in the clinical laboratories.

Zseq: An Approach for Preprocessing Next-Generation Sequencing Data

Next-generation sequencing technology generates a huge number of reads (short sequences), which contain a vast amount of genomic data. The sequencing process, however, comes with artifacts. Preprocessing of sequences is mandatory for further downstream analysis. We present Zseq, a linear method that identifies the most informative genomic sequences and reduces the number of biased sequences, sequence duplications, and ambiguous nucleotides. Zseq finds the complexity of the sequences by counting the number of uniquek-mers in each sequence as its corresponding score and also takes into the account other factors such as ambiguous nucleotides or high GC-content percentage ink-mers. Based on az-score threshold, Zseq sweeps through the sequences again and filters those with a z-score less than the user-defined threshold.

Zseq algorithm is able to provide a better mapping rate; it reduces the number of ambiguous bases significantly in comparison with other methods. Evaluation of the filtered reads has been conducted by aligning the reads and assembling the transcripts using the reference genome as well as de novo assembly. The assembled transcripts show a better discriminative ability to separate cancer and normal samples in comparison with another state-of-the-art method. Moreover, de novo assembled transcripts from the reads filtered by Zseq have longer genomic sequences than other tested methods. Estimating the threshold of the cutoff point is introduced using labeling rules with optimistic results.

Zika virus: from pathogenesis to disease control

Zika virus is a mosquito-borne flavivirus discovered in Uganda in 1947. The virus has emerged in recent years and spread in the Pacific Area and the Americas, where it has caused large human outbreaks. The factors involved in the virus's emergence are still unknown, but probably include its introduction in naïve environments characterised by the presence of high densities of competent Aedes spp. mosquitoes and susceptible human hosts in urban areas. Unique features of Zika virus infection are sexual and transplacental transmission and associated neurological morbidities, i.e. Guillain-Barré syndrome and fetal microcephaly. Diagnosis relies on the detection of viral nucleic acids in biological samples, while detection of a specific antibody response may be inconclusive because of the broad cross-reactivity of antibodies among flaviviruses. Experimental studies have clarified some mechanisms of Zika virus pathogenesis and have identified potential targets for antiviral drugs. In animal models, the virus can infect and efficiently replicate in the placenta and in the brain, and induce fetal demise or neural damage, recapitulating human diseases. These animal models have been used to evaluate candidate vaccines and promising results have been obtained.