Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples

CRISPR-Cas technology in forensic investigations: Principles, applications, and ethical considerations

CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated proteins) systems are adaptive immune systems originally present in bacteria, where they are essential to protect against external genetic elements, including viruses and plasmids. Taking advantage of this system, CRISPR-Cas-based technologies have emerged as incredible tools for precise genome editing, thus significantly advancing several research fields. Forensic sciences represent a multidisciplinary field that explores scientific methods to investigate and resolve legal issues, particularly criminal investigations and subject identification. Consequently, it plays a critical role in the justice system, providing scientific evidence to support judicial investigations. Although less explored, CRISPR-Cas-based methodologies demonstrate strong potential in the field of forensic sciences due to their high accuracy and sensitivity, including DNA profiling and identification, interpretation of crime scene investigations, detection of food contamination or fraud, and other aspects related to environmental forensics. However, using CRISPR-Cas-based methodologies in human samples raises several ethical issues and concerns regarding the potential misuse of individual genetic information. In this manuscript, we provide an overview of potential applications of CRISPR-Cas-based methodologies in several areas of forensic sciences and discuss the legal implications that challenge their routine implementation in this research field.

The application status of sequencing technology in global respiratory infectious disease diagnosis

Next-generation sequencing (NGS) has revolutionized clinical microbiology, particularly in diagnosing respiratory infectious diseases and conducting epidemiological investigations. This narrative review summarizes conventional methods for routine respiratory infection diagnosis, including culture, smear microscopy, immunological assays, image techniques as well as polymerase chain reaction(PCR). In contrast to conventional methods, there is a new detection technology, sequencing technology, and here we mainly focus on the next-generation sequencing NGS, especially metagenomic NGS(mNGS). NGS offers significant advantages over traditional methods. Firstly, mNGS eliminates assumptions about pathogens, leading to faster and more accurate results, thus reducing diagnostic time. Secondly, it allows unbiased identification of known and novel pathogens, offering broad-spectrum coverage. Thirdly, mNGS not only identifies pathogens but also characterizes microbiomes, analyzes human host responses, and detects resistance genes and virulence factors. It can complement targeted sequencing for bacterial and fungal classification. Unlike traditional methods affected by antibiotics, mNGS is less influenced due to the extended survival of pathogen DNA in plasma, broadening its applicability. However, barriers to full integration into clinical practice persist, primarily due to cost constraints and limitations in sensitivity and turnaround time. Despite these challenges, ongoing advancements aim to improve cost-effectiveness and efficiency, making NGS a cornerstone technology for global respiratory infection diagnosis.

Why is next-generation sequencing essential in modern virology?

A contaminated viral stock results in considerable loss of time, resources and financial means and is generally discovered only by chance after years of research. Thus, it is necessary to implement a technique that can detect contamination without prior knowledge or assumptions, such as next-generation sequencing (NGS). Here, we describe the discovery of a cross-contaminated viral stock from a biological repository of an African Zika virus isolate with Toscana virus after performing NGS on infected cells. In addition, we also describe the consequences that we faced using this contaminated stock. These included the economic and time loss to the lab that needed to repeat all previously performed experiments, the generation of biologically flawed results with a subsequent potential retraction and the severe risk of infection of lab members who manipulated the contaminated stock.

MetaAll: integrative bioinformatics workflow for analysing clinical metagenomic data

Over the past decade, there have been many improvements in the field of metagenomics, including sequencing technologies, advances in bioinformatics and the development of reference databases, but a one-size-fits-all sequencing and bioinformatics pipeline does not yet seem achievable. In this study, we address the bioinformatics part of the analysis by combining three methods into a three-step workflow that increases the sensitivity and specificity of clinical metagenomics and improves pathogen detection. The individual tools are combined into a user-friendly workflow suitable for analysing short paired-end (PE) and long reads from metagenomics datasets-MetaAll. To demonstrate the applicability of the developed workflow, four complicated clinical cases with different disease presentations and multiple samples collected from different biological sites as well as the CAMI Clinical pathogen detection challenge dataset were used. MetaAll was able to identify putative pathogens in all but one case. In this case, however, traditional microbiological diagnostics were also unsuccessful. In addition, co-infection with Haemophilus influenzae and Human rhinovirus C54 was detected in case 1 and co-infection with SARS-Cov-2 and Influenza A virus (FluA) subtype H3N2 was detected in case 3. In case 2, in which conventional diagnostics could not find a pathogen, mNGS pointed to Klebsiella pneumoniae as the suspected pathogen. Finally, this study demonstrated the importance of combining read classification, contig validation and targeted reference mapping for more reliable detection of infectious agents in clinical metagenome samples.

Urinary Microbiome Research Has Not Established a Conclusive Influence: Revisiting Koch's Postulates

In order to establish a causal relationship between urinary microbiota and a urological disease or condition, a series of rigorous scientific criteria must be met. Demonstration of an association between microbiota and a condition does not necessarily imply causality, importance, or clinical relevance.

Identification of causative fungus from sterile abscess using metagenomics followed by in situ hybridization

Introduction. Invasive fungal infections require early diagnosis for treatment. Microscopic observation of biopsy and blood culture is the gold standard for the identification of the causative fungus, but it is difficult to identify the causative pathogen by a sterile abscess biopsy. Case Presentation. We present a case report of breakthrough invasive trichosporonosis in a 65-year-old Japanese male with acute myeloid leukaemia receiving antifungal prophylaxis. Blood cultures showed no fungal growth, and a liver biopsy and a removed spleen with abscess showed fragmented fungi, but no fungal identification was possible. This report demonstrates that retrospective analyses were able to identify the causative fungus. Conclusion. We narrowed down the candidate fungi by deep sequencing of the ITS1 region of fungal genome and confirmed that the fungus observed in the specimen was Trichosporon asahii by in situ hybridization using a DNA probe targeting 26S rRNA.

Anthocyanins from pomegranate peel (Punica granatum), chili pepper fruit (Capsicum annuum), and bougainvillea flowers (Bougainvillea spectabilis) with multiple biofunctions: Antibacterial, antioxidant, and anticancer

Background

Natural colorants, including natural pigments, e.g., anthocyanins, carotenoids, and chlorophylls, in novel and attractive food matrixes have become a popular trend. They impart favorite colors to food products and provide significant therapeutic effects. This study is aimed at extracting and identifying some natural pigments from different plant sources and evaluating their ability as antibacterial, antioxidant, and anticancer activities.

Methods

The anthocyanin-rich extract (ARE) is derived from three natural plant sources: pomegranate peel (Punica granatum), chili pepper fruit (Capsicum annuum), and Bougainvillea flowers. Bougainvillea spectabilis are analyzed for biochemical composition, as well as antioxidant, antibacterial, and anticancer activity, HPLC, DPPH, FRAP, disc diffusion assay, MIC, MTT, VEGFR-2, and caspase-9 assays.

Results

All three extracts had varying total phenolic contents, ranging from 14 to 466 mg GAE/g extract, where Punica granatum was the highest (466 mg GAE/g extract), followed by Bougainvillea spectabilis (180 mg GAE/g extract), and then Capsicum annuum (14 mg GAE/g extract). The antioxidant activity rose steadily with raising concentration. The ARE of pomegranate peels recorded highest value, followed by Bougainvillea flowers and chili pepper fruit. The MTT assay revealed an inhibitory action of the tested extracts on the proliferation of HCT-116, MCF-7, and HepG2 in a concentration-based manner. Gene expression of caspase-9 transcripts was considerably multiplied by the application of ARE of pomegranate peels. All the tested extracts inhibited VEGFR-2, and the inhibition (%) expanded gradually with increasing concentrations, achieving the highest value (80 %) at 10 μg/mL. The ARE of pomegranate peels scored highest antibacterial activity, followed by ARE of chili pepper fruit and Bougainvillea flowers. The inhibition zone diameter escalated gradually with rising concentrations of the tested samples.

Conclusion

The AREs of the three studied plant sources can be used as multifunctional products with antioxidant, anticancer, and antibacterial activities that are natural, safe, and cheap.

Clinical applications of metagenomics next-generation sequencing in infectious diseases

Infectious diseases are a great threat to human health. Rapid and accurate detection of pathogens is important in the diagnosis and treatment of infectious diseases. Metagenomics next-generation sequencing (mNGS) is an unbiased and comprehensive approach for detecting all RNA and DNA in a sample. With the development of sequencing and bioinformatics technologies, mNGS is moving from research to clinical application, which opens a new avenue for pathogen detection. Numerous studies have revealed good potential for the clinical application of mNGS in infectious diseases, especially in difficult-to-detect, rare, and novel pathogens. However, there are several hurdles in the clinical application of mNGS, such as: (1) lack of universal workflow validation and quality assurance; (2) insensitivity to high-host background and low-biomass samples; and (3) lack of standardized instructions for mass data analysis and report interpretation. Therefore, a complete understanding of this new technology will help promote the clinical application of mNGS to infectious diseases. This review briefly introduces the history of next-generation sequencing, mainstream sequencing platforms, and mNGS workflow, and discusses the clinical applications of mNGS to infectious diseases and its advantages and disadvantages.

The microbiological diagnostic performance of metagenomic next-generation sequencing in patients with infectious diseases

OBJECTIVE

Metagenomic next-generation sequencing (mNGS) can be used to detect pathogens in clinical infectious diseases through the sequencing analysis of microbial and host nucleic acids in clinical samples. This study aimed to assess the diagnostic performance of mNGS in patients with infections.

METHODS

In this study, 641 patients with infectious diseases were enrolled. These patients simultaneously underwent pathogen detection by both mNGS and microbial culture. Through statistical analysis, we judged the diagnostic performance of mNGS and microbial culture on different pathogens.

RESULTS

Among 641 patients, 276 cases of bacteria and 95 cases of fungi were detected by mNGS, whereas 108 cases of bacteria and 41 cases of fungi were detected by traditional cultures. Among all mixed infections, combined bacterial and viral infections were the highest (51%, 87/169), followed by combined bacterial with fungal infections (16.57%, 28/169) and mixed bacterial, fungal, and viral infections (13.61%, 23/169). Among all sample types, bronchoalveolar lavage fluid (BALF) samples had the highest positive rate (87.8%, 144/164), followed by sputum (85.4%, 76/89) and blood samples (61.2%, 158/258). For the culture method, sputum samples had the highest positive rate (47.2%, 42/89), followed by BALF (37.2%, 61/164). The positive rate of mNGS was 69.89% (448/641), which was significantly higher than that of traditional cultures (22.31% [143/641]) (P < .05).

CONCLUSIONS

Our results show that mNGS is an effective tool for the rapid diagnosis of infectious diseases. Compared with traditional detection methods, mNGS also showed obvious advantages in mixed infections and infections with uncommon pathogens.

Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection

BACKGROUND

The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood.

METHODS

Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol-SepsiPURE.

RESULTS

After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50-100 colony forming units (CFU)/mL to 1-5 CFU/mL.

CONCLUSION

In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Performance of metagenomic next-generation sequencing in cerebrospinal fluid for diagnosis of tuberculous meningitis

Purpose. Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases, while its performance in diagnosis of tuberculous meningitis (TBM) is incompletely characterized. The aim of this study was to assess the performance of mNGS in the diagnosis of TBM, and illustrate the sensitivity and specificity of different methods.Methods. We retrospectively recruited TBM patients between January 2021 and March 2023 to evaluate the performance of mNGS on cerebrospinal fluid (CSF) samples, in comparison with conventional microbiological testing, including culturing of Mycobacterium tuberculosis (MTB), acid-fast bacillus (AFB) stain, reverse transcription PCR and Xpert MTB/RIF.Results. Of the 40 enrolled, 34 participants were diagnosed with TBM, including 15(44.12 %) definite and 19(55.88 %) clinical diagnosis based upon clinical manifestations, CSF parameters, brain imaging, pathogen evidence and treatment response. The mNGS method identified sequences of Mycobacterium tuberculosis complex (MTBC) in 11 CSF samples. In patients with definite TBM, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of mNGS were 78.57, 100, 100, 66.67 and 85 %, respectively. Compared to conventional diagnostic methods, the sensitivity of mNGS (78.57 %) was higher than AFB (0 %), culturing (0 %), RT-PCR (60 %) and Xpert MTB/RIF (14.29 %).Conclusions. Our study indicates that mNGS of CSF exhibited an overall improved sensitivity over conventional diagnostic methods for TBM and can be considered a front-line CSF test.

sRNAflow: A Tool for the Analysis of Small RNA-Seq Data

The analysis of small RNA sequencing data across a range of biofluids is a significant research area, given the diversity of RNA types that hold potential diagnostic, prognostic, and predictive value. The intricate task of segregating the complex mixture of small RNAs from both human and other species, including bacteria, fungi, and viruses, poses one of the most formidable challenges in the analysis of small RNA sequencing data, currently lacking satisfactory solutions. This study introduces sRNAflow, a user-friendly bioinformatic tool with a web interface designed for the analysis of small RNAs obtained from biological fluids. Tailored to the unique requirements of such samples, the proposed pipeline addresses various challenges, including filtering potential RNAs from reagents and environment, classifying small RNA types, managing small RNA annotation overlap, conducting differential expression assays, analysing isomiRs, and presenting an approach to identify the sources of small RNAs within samples. sRNAflow also encompasses an alternative alignment-free analysis of RNA-seq data, featuring clustering and initial RNA source identification using BLAST. This comprehensive approach facilitates meaningful comparisons of results between different analytical methods.

Application of VirCapSeq-VERT and BacCapSeq in the diagnosis of presumed and definitive neuroinfectious diseases

Unbiased high-throughput sequencing (HTS) has enabled new insights into the diversity of agents implicated in central nervous system (CNS) infections. The addition of positive selection capture methods to HTS has enhanced the sensitivity while reducing sequencing costs and the complexity of bioinformatic analysis. Here we report the use of virus capture-based sequencing for vertebrate viruses (VirCapSeq-VERT) and bacterial capture sequencing (BacCapSeq) in investigating CNS infections. Thirty-four samples were categorized: (1) patients with definitive CNS infection by routine testing; (2) patients meeting clinically the Brighton criteria (BC) for meningoencephalitis; (3) patients with presumptive infectious etiology highest on the differential. RNA extracts from cerebrospinal fluid (CSF) were used for VirCapSeq-VERT, and DNA extracts were used for BacCapSeq analysis. Among 8 samples from known CNS infections in group 1, VirCapSeq and BacCapSeq confirmed 3 expected diagnoses (42.8%), were negative in 2 (25%), yielded an alternative result in 1 (11.1%), and did not detect 2 expected negative pathogens. The confirmed cases identified HHV-6, HSV-2, and VZV while the negative samples included JCV and HSV-2. In groups 2 and 3, 11/26 samples (42%) were positive for at least one pathogen; however, 27% of the total samples (7/26) were positive for commensal organisms. No microbial nucleic acids were detected in negative control samples. HTS showed limited promise for pathogen identification in presumed CNS infectious diseases in our small sample. Before conducting larger-scale prospective studies to assess the clinical value of this novel technique, clinicians should understand the benefits and limitations of using this modality.

Profiling of Microbial Landscape in Lung of Chronic Obstructive Pulmonary Disease Patients Using RNA Sequencing

Purpose

The aim of the study was to use RNA sequencing (RNA-seq) data of lung from chronic obstructive pulmonary disease (COPD) patients to identify the bacteria that are most commonly detected. Additionally, the study sought to investigate the differences in these infections between normal lung tissues and those affected by COPD.

Patients and Methods

We re-analyzed RNA-seq data of lung from 99 COPD patients and 93 non-COPD smokers to determine the extent to which the metagenomes differed between the two groups and to assess the reliability of the metagenomes. We used unmapped reads in the RNA-seq data that were not aligned to the human reference genome to identify more common infections in COPD patients.

Results

We identified 18 bacteria that exhibited significant differences between the COPD and non-COPD smoker groups. Among these, Yersinia enterocolitica was found to be more than 30% more abundant in COPD. Additionally, we observed difference in detection rate based on smoking history. To ensure the accuracy of our findings and distinguish them from false positives, we double-check the metagenomic profile using Basic Local Alignment Search Tool (BLAST). We were able to identify and remove specific species that might have been misclassified as other species in Kraken2 but were actually Staphylococcus aureus, as identified by BLAST analysis.

Conclusion

This study highlighted the method of using unmapped reads, which were not typically used in sequencing data, to identify microorganisms present in patients with lung diseases such as COPD. This method expanded our understanding of the microbial landscape in COPD and provided insights into the potential role of microorganisms in disease development and progression.

Application of VirCapSeq-VERT and BacCapSeq In the Diagnosis of Presumed and Definitive Neuroinfectious Diseases

Background

Unbiased high-throughput sequencing (HTS) has enabled new insights into the diversity of agents implicated in central nervous system (CNS) infections. The addition of positive selection capture methods to HTS has enhanced the sensitivity while reducing sequencing costs and complexity of bioinformatic analysis. Here we report the use of virus capture based sequencing for vertebrate viruses (VirCapSeq-VERT) and bacterial capture sequencing (BacCapSeq) in investigating CNS infections.

Design/Methods

Thirty-four samples were categorized: (1) Patients with definitive CNS infection by routine testing; (2) Patients meeting clinically Brighton Criteria (BC) for meningoencephalitis (3) Patients with presumptive infectious etiology highest on the differential. RNA extracts from cerebrospinal fluid (CSF) were used for VirCapSeq-VERT and DNA extracts were used for BacCapSeq analysis.

Results

Among 8 samples from known CNS infections in group 1, VirCapSeq and BacCapSeq confirmed 3 expected diagnoses (42.8%), were negative in 2 (25%), yielded an alternative result in 1 (11.1%), and did not detect 2 expected negative pathogens. The confirmed cases identified HHV-6, HSV-2, and VZV while the negative samples included JCV and HSV-2. In groups 2 and 3,11/26 samples (42%) were positive for at least one pathogen, however 27% of the total samples (7/26) were positive for commensal organisms. No microbial nucleic acids were detected in negative control samples.

Conclusions

HTS showed limited promise for pathogen identification in presumed CNS infectious diseases in our small sample. Before conducting larger-scale prospective studies to assess clinical value of this novel technique, clinicians should understand benefits and limitations of using this modality.

Metagenomic profile of the bacterial communities associated with Ixodes granulatus (Acari: Ixodidae): a potential vector of tick-borne diseases

Ixodes granulatus Supino, 1897 (Acari: Ixodida) is one of Malaysia's most common hard ticks and is a potential vector for tick-borne diseases (TBDs). Despite its great public health importance, research on I. granulatus microbial communities remains largely unexplored. Therefore, this study aimed to investigate the bacterial communities of on-host I. granulatus collected from three different recreational areas on the East Coast of Peninsular Malaysia using high throughput Next Generation Sequencing (NGS). A total of 9 females on-host I. granulatus were subjected to metabarcoding analysis targeting V3-V4 regions of 16S ribosomal RNA (rRNA) using the Illumina MiSeq platform. This study identified 15 bacterial phyla corresponding to 19 classes, 54 orders, and 90 families from 435 amplicon sequence variants (ASVs), revealing a diverse bacterial community profile. Together with 130 genera assigned, local I. granulatus harbored 4 genera of pathogens, i.e., Rickettsia da Rocha Lima, 1916 (Rickettsiales: Rickettsiaceae) (58.6%), Borrelia Swellengrebel 1907 (Spirochaetales: Borreliaceae) (31.6%), Borreliella Adeolu and Gupta 2015 (Spirochaetales: Borreliaceae) (0.6%), and Ehrlichia Cowdria Moshkovski 1947 (Rickettsiales: Ehrlichiaceae) (39.9%). Some endosymbiont bacteria, such as Coxiella (Philip, 1943) (Legionellales: Coxiellaceae), Wolbachia Hertig 1936 (Rickettsiales: Ehrlichiaceae), and Rickettsiella Philip, 1956 (Legionellales: Coxiellaceae), were also detected at very low abundance. Interestingly, this study reported the co-infection of Borrelia and Ehrlichia for the first time, instilling potential health concerns in the context of co-transmission to humans, especially in areas with a high population of I. granulatus. This study successfully characterized the tick microbiome and provided the first baseline data of I. granulatus bacterial communities in Malaysia. These results support the need for way-forward research on tick-associated bacteria using NGS, focusing on medically important species toward TBD prevention.

De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee

Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low-biomass environments. Contamination from DNA extraction kits or sampling lab environments leaves taxonomic "bread crumbs" across multiple distinct sample types. Here we describe Squeegee, a de novo contamination detection tool that is based upon this principle, allowing the detection of microbial contaminants when negative controls are unavailable. On the low-biomass samples, we compare Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers putative contaminants. We analyze samples of varying biomass from the Human Microbiome Project and identify likely, previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision and thus represents a computational approach for contaminant detection when negative controls are unavailable.

Dehydration response in Stylosanthes scabra: Transcriptional, biochemical, and physiological modulations

Stylosanthes scabra, popularly known as stylo, is native to the Brazilian Caatinga semiarid region and stands out as a drought-tolerant shrub forage crop. This work provides information about the plant response during the first 48 h of water deficit, followed by a rehydration treatment. Besides root transcriptomics data, 13 physiological or biochemical parameters were scrutinized. Additionally, RNA-Seq annotated transcripts not associated with the "Viridiplantae" clade were taxonomically categorized. It was found that S. scabra quickly perceives and recovers from the oscillations of the imposed water regime. Physiologically, mechanisms that minimize evapotranspiration or protect the photosynthetic apparatus stood out. Biochemically, it was found that the root tissue invests in synthesizing compounds that can act as osmolytes (proline and sugars), emphasizing the importance of osmoregulation to water deficit acclimation. Consistently, transcriptome and qPCR analyses showed that a set of enriched biological processes with upregulated (UR) transcripts were involved in protective functions against reactive oxygen species or encoding enzymes of important metabolic pathways, which might contribute to S. scabra response to water deficit. Additionally, several UR kinases and transcription factors were identified. Finally, in an innovative approach, some naturally occurring microbial groups (such as Schizosaccharomyces, Bradyrhizobium, etc.) were identified in the S. scabra roots. This study reveals insights into the physiological, biochemical, and molecular mechanisms underlying the S. scabra response to water deficit and provides candidate genes that may be useful in developing drought-tolerant crop varieties through biotechnological applications.

Advantages and challenges of metagenomic sequencing for the diagnosis of pulmonary infectious diseases

Objective

We aim to familiarize the application status of metagenomic sequencing in diagnosing pulmonary infections, to compare metagenomic sequencing with traditional diagnostic methods, to conclude the advantages and limitations of metagenomic sequencing, and to provide some advice for clinical practice and some inspiration for associated researches.

Data Sources

The data were obtained from peer‐reviewed literature, white papers, and meeting reports.

Results

This review focused on the applications of untargeted metagenomic sequencing in lungs infected by bacteria, viruses, fungi, chlamydia pneumoniae, Mycoplasma pneumoniae, parasites, and other pathogens. Compared with conventional diagnostic methods, metagenomic sequencing is better in detecting novel, rare, and unexpected pathogens and being applied in co‐infections. Meanwhile, it can also provide more comprehensive information about pathogens. However, metagenomic sequencing still has limitations. Also, the situations that should be applied in and how the results should be interpreted are discussed in this review.

Conclusion

Metagenomic sequencing improves efficiency to identify pathogens compared with traditional diagnostic methods and can be applied in clinical diagnosis. However, the technology of metagenomic sequencing still needs to be improved. Also, clinicians should learn more about when to use metagenomic sequencing and how to interpret its results.

CleanSeq: A Pipeline for Contamination Detection, Cleanup, and Mutation Verifications from Microbial Genome Sequencing Data

Contaminations frequently occur in bacterial cultures, which significantly affect the reproducibility and reliability of the results from whole-genome sequencing (WGS). Decontaminated WGS data with clean reads is the only desirable source for detecting possible variants correctly. Improvements in bioinformatics are essential to analyze the contaminated WGS dataset. Existing pipelines usually contain contamination detection, decontamination, and variant calling separately. The efficiency and results from existing pipelines fluctuate since distinctive computational models and parameters are applied. It is then promising to develop a bioinformatical tool containing functions to discriminate and remove contaminated reads and improve variant calling from clean reads. In this study, we established a Python-based pipeline named CleanSeq for automatic detection and removal of contaminating reads, analyzing possible genome variants with proper verifications via local re-alignments. The application and reproducibility are proven in either simulated, publicly available datasets or actual genome sequencing reads from our experimental evolution study in Escherichia coli. We successfully obtained decontaminated reads, called out all seven consistent mutations from the contaminated bacterial sample, and derived five colonies. Collectively, the results demonstrated that CleanSeq could effectively process the contaminated samples to achieve decontaminated reads, based on which reliable results (i.e., variant calling) could be obtained.

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.

Metagenomics-enabled microbial surveillance

Lessons learnt from the COVID-19 pandemic include increased awareness of the potential for zoonoses and emerging infectious diseases that can adversely affect human health. Although emergent viruses are currently in the spotlight, we must not forget the ongoing toll of morbidity and mortality owing to antimicrobial resistance in bacterial pathogens and to vector-borne, foodborne and waterborne diseases. Population growth, planetary change, international travel and medical tourism all contribute to the increasing frequency of infectious disease outbreaks. Surveillance is therefore of crucial importance, but the diversity of microbial pathogens, coupled with resource-intensive methods, compromises our ability to scale-up such efforts. Innovative technologies that are both easy to use and able to simultaneously identify diverse microorganisms (viral, bacterial or fungal) with precision are necessary to enable informed public health decisions. Metagenomics-enabled surveillance methods offer the opportunity to improve detection of both known and yet-to-emerge pathogens.

Optimization of cerebrospinal fluid microbial DNA metagenomic sequencing diagnostics

Infection in the central nervous system is a severe condition associated with high morbidity and mortality. Despite ample testing, the majority of encephalitis and meningitis cases remain undiagnosed. Metagenomic sequencing of cerebrospinal fluid has emerged as an unbiased approach to identify rare microbes and novel pathogens. However, several major hurdles remain, including establishment of individual limits of detection, removal of false positives and implementation of universal controls. Twenty-one cerebrospinal fluid samples, in which a known pathogen had been positively identified by available clinical techniques, were subjected to metagenomic DNA sequencing. Fourteen samples contained minute levels of Epstein-Barr virus. The detection threshold for each sample was calculated by using the total leukocyte content in the sample and environmental contaminants found in the bioinformatic classifiers. Virus sequences were detected in all ten samples, in which more than one read was expected according to the calculations. Conversely, no viral reads were detected in seven out of eight samples, in which less than one read was expected according to the calculations. False positive pathogens of computational or environmental origin were readily identified, by using a commonly available cell control. For bacteria, additional filters including a comparison between classifiers removed the remaining false positives and alleviated pathogen identification. Here we show a generalizable method for identification of pathogen species using DNA metagenomic sequencing. The choice of bioinformatic method mainly affected the efficiency of pathogen identification, but not the sensitivity of detection. Identification of pathogens requires multiple filtering steps including read distribution, sequence diversity and complementary verification of pathogen reads.

Metagenomic Sequencing for Microbial DNA in Human Samples: Emerging Technological Advances

Whole genome metagenomic sequencing is a powerful platform enabling the simultaneous identification of all genes from entirely different kingdoms of organisms in a complex sample. This technology has revolutionised multiple areas from microbiome research to clinical diagnoses. However, one of the major challenges of a metagenomic study is the overwhelming non-microbial DNA present in most of the host-derived specimens, which can inundate the microbial signals and reduce the sensitivity of microorganism detection. Various host DNA depletion methods to facilitate metagenomic sequencing have been developed and have received considerable attention in this context. In this review, we present an overview of current host DNA depletion approaches along with explanations of their underlying principles, advantages and disadvantages. We also discuss their applications in laboratory microbiome research and clinical diagnoses and, finally, we envisage the direction of the further perfection of metagenomic sequencing in samples with overabundant host DNA.

Presence of periodontal pathogenic bacteria in blood of patients with coronary artery disease

It has been hypothesised that oral bacteria can migrate, through the blood, from the mouth to the arterial plaques, thus exacerbating atherosclerosis. This study compared bacteria present in the peripheral blood of individuals with and without coronary artery disease (CAD). RNA sequences obtained from blood were downloaded from GEO (GSE58150). Eight patients with coronary artery calcification (CAC) scoring > 500 and eight healthy individuals were analysed. After conducting quality control, the sequences were aligned to the hg38 reference genome using Hisat2. Bacterial taxa were analysed by inputting the unmapped sequences into Kraken. Ecological indices were calculated using Vegan. The package DESeq2 was used to compare the counts of bacteria per standard rank between groups. A total of 51 species were found only in patients with CAD and 41 were exclusively present in healthy individuals. The counts of one phylum, one class, three orders, two families and one genus were significantly different between the analysed groups (p < 0.00032, FDR < 10%), including the orders Cardiobacteriales, Corynebacteriales and Fusobacteriales. Twenty-three bacterial species belonging to the subgingival plaque bacterial complexes were also identified in the blood of individuals from both the groups; Fusobacterium nucleatum was significantly less frequent in patients with CAD (p = 0.0012, FDR = 4.8%). Furthermore, the frequency of another 11 bacteria differed significantly among patients with CAD than that among healthy individuals (p < 0.0030, FDR < 10%). These bacteria have not been previously reported in patients with atherosclerosis and periodontitis. The presence of members of the subgingival plaque bacterial complexes in the blood of patients with CAC supports the hypothesis that the periodontopathogens can be disseminated through the blood flow to other body parts where they may enhance inflammatory processes that can lead to the development or exacerbation of atherosclerosis.

Contamination Issue in Viral Metagenomics: Problems, Solutions, and Clinical Perspectives

We describe the most common internal and external sources and types of contamination encountered in viral metagenomic studies and discuss their negative impact on sequencing results, particularly for low-biomass samples and clinical applications. We also propose some basic recommendations for reducing the background noise in viral shotgun metagenomic (SM) studies, which would limit the bias introduced by various classes of contaminants. Regardless of the specific viral SM protocol, contamination cannot be totally avoided; in particular, the issue of reagent contamination should always be addressed with high priority. There is an urgent need for the development and validation of standards for viral metagenomic studies especially if viral SM protocols will be more widely applied in diagnostics.

A Review of the Impact of Alterations in Gut Microbiome on the Immunopathogenesis of Ocular Diseases

Recent studies have highlighted the association between ocular diseases and microbiota profiles of the host intestinal tract and oral cavity. There is mounting evidence supporting the existence of a 'gut-eye axis', whereby changes in gut microbiome alter host immunity, with consequential implications for ocular health and disease. In this review, we examined recent published findings on the association between gut microbiome and ocular morbidity, based on 25 original articles published between 2011 to 2020. The review included both clinical and in vivo animal studies, with particular focus on the influence of the microbiome on host immunity and metabolism. Significant associations between altered intestinal microbiome and specific ocular diseases and pathological processes, including Behçet's syndrome, autoimmune uveitis, age-related macular degeneration, choroidal neovascularization, bacterial keratitis, and Sjögren-like lacrimal keratoconjunctivitis have been demonstrated. Furthermore, alterations in the gut microbiome resulted in quantifiable changes in the host immune response, suggesting immunopathogenesis as the basis for the link between intestinal dysbiosis and ocular disease. We also examined and compared different techniques used in the identification and quantification of gut microorganisms. With our enhanced understanding of the potential role of gut commensals in ophthalmic disease, the stage is set for further studies on the underlying mechanisms linking the gut microbiome, the host immune response, and the pathogenesis of ophthalmic disease.

Evaluation of a high-throughput, cost-effective Illumina library preparation kit

Library preparation for high-throughput sequencing applications is a critical step in producing representative, unbiased sequencing data. The iGenomX Riptide High Throughput Rapid Library Prep Kit purports to provide high-quality sequencing data with lower costs compared to other Illumina library kits. To test these claims, we compared sequence data quality of Riptide libraries to libraries constructed with KAPA Hyper and NEBNext Ultra. Across several single-source genome samples, mapping performance and de novo assembly of Riptide libraries were similar to conventional libraries prepared with the same DNA. Poor performance of some libraries resulted in low sequencing depth. In particular, degraded DNA samples may be challenging to sequence with Riptide. There was little cross-well plate contamination with the overwhelming majority of reads belong to the proper source genomes. The sequencing of metagenome samples using different Riptide primer sets resulted in variable taxonomic assignment of reads. Increased adoption of the Riptide kit will decrease library preparation costs. However, this method might not be suitable for degraded DNA.

Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.

De Novo Transcriptome Meta-Assembly of the Mixotrophic Freshwater Microalga Euglena gracilis

Euglena gracilis is a well-known photosynthetic microeukaryote considered as the product of a secondary endosymbiosis between a green alga and a phagotrophic unicellular belonging to the same eukaryotic phylum as the parasitic trypanosomatids. As its nuclear genome has proven difficult to sequence, reliable transcriptomes are important for functional studies. In this work, we assembled a new consensus transcriptome by combining sequencing reads from five independent studies. Based on a detailed comparison with two previously released transcriptomes, our consensus transcriptome appears to be the most complete so far. Remapping the reads on it allowed us to compare the expression of the transcripts across multiple culture conditions at once and to infer a functionally annotated network of co-expressed genes. Although the emergence of meaningful gene clusters indicates that some biological signal lies in gene expression levels, our analyses confirm that gene regulation in euglenozoans is not primarily controlled at the transcriptional level. Regarding the origin of E. gracilis, we observe a heavily mixed gene ancestry, as previously reported, and rule out sequence contamination as a possible explanation for these observations. Instead, they indicate that this complex alga has evolved through a convoluted process involving much more than two partners.

Distribution of Merlin in eukaryotes and first report of DNA transposons in kinetoplastid protists

DNA transposons are defined as repeated DNA sequences that can move within the host genome through the action of transposases. The transposon superfamily Merlin was originally found mainly in animal genomes. Here, we describe a global distribution of the Merlin in animals, fungi, plants and protists, reporting for the first time their presence in Rhodophyceae, Metamonada, Discoba and Alveolata. We identified a great variety of potentially active Merlin families, some containing highly imperfect terminal inverted repeats and internal tandem repeats. Merlin-related sequences with no evidence of mobilization capacity were also observed and may be products of domestication. The evolutionary trees support that Merlin is likely an ancient superfamily, with early events of diversification and secondary losses, although repeated re-invasions probably occurred in some groups, which would explain its diversity and discontinuous distribution. We cannot rule out the possibility that the Merlin superfamily is the product of multiple horizontal transfers of related prokaryotic insertion sequences. Moreover, this is the first account of a DNA transposon in kinetoplastid flagellates, with conserved Merlin transposase identified in Bodo saltans and Perkinsela sp., whereas it is absent in trypanosomatids. Based on the level of conservation of the transposase and overlaps of putative open reading frames with Merlin, we propose that in protists it may serve as a raw material for gene emergence.

Comprehensive comparative genomics reveals over 50 phyla of free-living and pathogenic bacteria are associated with diverse members of the amoebozoa

The Amoebozoa, a group containing predominantly amoeboid unicellular protists has been shown to play an important ecological role in controlling environmental bacteria. Amoebozoans not only graze bacteria but also serve as a safe niche for bacterial replication and harbor endosymbiotic bacteria including dangerous human pathogens. Despite their importance, only a few lineages of Amoebozoa have been studied in this regard. In this research, we conducted a comprehensive genomic and transcriptomic study with expansive taxon sampling by including representatives from the three known clades of the Amoebozoa. We used culture independent whole culture and single cell genomics/transcriptomics to investigate the association of bacteria with diverse amoebozoans. Relative to current published evidence, we recovered the largest number of bacterial phyla (64) and human pathogen genera (51) associated with the Amoebozoa. Using single cell genomics/transcriptomics we were able to determine up to 24 potential endosymbiotic bacterial phyla, some potentially endosymbionts. This includes the majority of multi-drug resistant pathogens designated as major public health threats. Our study demonstrates amoebozoans are associated with many more phylogenetically diverse bacterial phyla than previously recognized. It also shows that all amoebozoans are capable of harboring far more dangerous human pathogens than presently documented, making them of primal public health concern.

COVID-19 and human reproduction: A pandemic that packs a serious punch

The COVID-19 pandemic has led to a worldwide health emergency that has impacted 188 countries at last count. The rapid community transmission and relatively high mortality rates with COVID-19 in modern times are relatively unique features of this flu pandemic and have resulted in an unparalleled global health crisis. SARS-CoV-2, being a respiratory virus, mainly affects the lungs, but is capable of infecting other vital organs, such as brain, heart and kidney. Emerging evidence suggests that the virus also targets male and female reproductive organs that express its main receptor ACE2, although it is as yet unclear if this has any implications for human fertility. Furthermore, professional bodies have recommended discontinuing fertility services during the pandemic such that reproductive services have also been affected. Although increased safety measures have helped to mitigate the propagation of COVID-19 in a number of countries, it seems that there is no predictable timeline to containment of the virus, a goal likely to remain elusive until an effective vaccine becomes available  and widely distributed across the globe. In parallel, research on reproduction has been postponed for obvious reasons, while diagnostic tests that detect the virus or antibodies against it are of vital importance to support public health policies, such as social distancing and our obligation to wear masks in public spaces. This review aims to provide an overview of critical research and ethics issues that have been continuously emerging in the field of reproductive medicine as the COVID-19 pandemic tragically unfolds.Abbreviations: ACE2: angiotensin- converting enzyme 2; ART: Assisted reproductive technology; ASRM: American Society for Reproductive Medicine; CCR9: C-C Motif Chemokine Receptor 9; CDC: Centers for Disease Control and Prevention; COVID-19: Coronavirus disease 2019; Ct: Cycle threshold; CXCR6: C-X-C Motif Chemokine Receptor 6; ELISA: enzyme-linked immunosorbent assay; ESHRE: European Society of Human Reproduction and Embryology; ET: Embryo transfer; FSH: Follicle Stimulating Hormone; FFPE: formalin fixed paraffin embedded; FYCO1: FYVE And Coiled-Coil Domain Autophagy Adaptor 1; IFFS: International Federation of Fertility Societies; IUI: Intrauterine insemination; IVF: In vitro fertilization; LH: Luteinizing Hormone; LZTFL1: Leucine Zipper Transcription Factor Like 1; MAR: medically assisted reproduction services; MERS: Middle East Respiratory syndrome; NGS: Next Generation Sequencing; ORF: Open Reading Frame; PPE: personal protective equipment; RE: RNA Element; REDa: RNA Element Discovery algorithm; RT-PCR: Reverse=trascriptase transcriptase-polymerase chain reaction; SARS: Severe acute respiratory syndrome; SARS-CoV-2: Severe Acute Respiratory Syndrome Coronavirus 2; SLC6A20: Solute Carrier Family 6 Member 20; SMS: Single Molecule Sequencing; T: Testosterone; TMPRSS2: transmembrane serine protease 2; WHO: World Health Organization; XCR1: X-C Motif Chemokine Receptor.

High Throughput Sequencing for the Detection and Characterization of RNA Viruses

This review aims to assess and recommend approaches for targeted and agnostic High Throughput Sequencing of RNA viruses in a variety of sample matrices. HTS also referred to as deep sequencing, next generation sequencing and third generation sequencing; has much to offer to the field of environmental virology as its increased sequencing depth circumvents issues with cloning environmental isolates for Sanger sequencing. That said however, it is important to consider the challenges and biases that method choice can impart to sequencing results. Here, methodology choices from RNA extraction, reverse transcription to library preparation are compared based on their impact on the detection or characterization of RNA viruses.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Sequencing facility and DNA source associated patterns of virus-mappable reads in whole-genome sequencing data

Numerous viral sequences have been reported in the whole-genome sequencing (WGS) data of human blood. However, it is not clear to what degree the virus-mappable reads represent true viral sequences rather than random-mapping or noise originating from sample preparation, sequencing processes, or other sources. Identification of patterns of virus-mappable reads may generate novel indicators for evaluating the origins of these viral sequences. We characterized paired-end unmapped reads and reads aligned to viral references in human WGS datasets, then compared patterns of the virus-mappable reads among DNA sources and sequencing facilities which produced these datasets. We then examined potential origins of the source- and facility-associated viral reads. The proportions of clean unmapped reads among the seven sequencing facilities were significantly different (P < 2 × 10-16). We identified 260,339 reads that were mappable to a total of 99 viral references in 2535 samples. The majority (86.7%) of these virus-mappable reads (corresponding to 47 viral references), which can be classified into four groups based on their distinct patterns, were strongly associated with sequencing facility or DNA source (adjusted P value <0.01). Possible origins of these reads include artificial sequences in library preparation, recombinant vectors in cell culture, and phages co-contaminated with their host bacteria. The sequencing facility-associated virus-mappable reads and patterns were repeatedly observed in other datasets produced in the same facilities. We have constructed an analytic framework and profiled the unmapped reads mappable to viral references. The results provide a new understanding of sequencing facility- and DNA source-associated batch effects in deep sequencing data and may facilitate improved bioinformatics filtering of reads.

Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid for the Diagnosis of External Ventricular and Lumbar Drainage-Associated Ventriculitis and Meningitis

Metagenomic next-generation sequencing (mNGS) has become a widely used technology that can accurately detect individual pathogens. This prospective study was performed between February 2019 and September 2019 in one of the largest clinical neurosurgery centers in China. The study aimed to evaluate the performance of mNGS on cerebrospinal fluid (CSF) from neurosurgical patients for the diagnosis of external ventricular and lumbar drainage (EVD/LD)-associated ventriculitis and meningitis (VM). We collected CSF specimens from neurosurgical patients with EVD/LD for more than 24 h to perform conventional microbiological studies and mNGS analyses in a pairwise manner. We also investigated the usefulness of mNGS of CSF for the diagnosis of EVD/LD-associated VM. In total, 102 patients were enrolled in this study and divided into three groups, including confirmed VM (cVM) (39), suspected VM (sVM) (49), and non-VM (nVM) (14) groups. Of all the patients, mNGS detected 21 Gram-positive bacteria, 20 Gram-negative bacteria, and five fungi. The three primary bacteria detected were Staphylococcus epidermidis (9), Acinetobacter baumannii (5), and Staphylococcus aureus (3). The mNGS-positive coincidence rate of confirmed EVD/LD-associated VM was 61.54% (24/39), and the negative coincidence rate of the nVM group was 100% (14/14). Of 15 VM pathogens not identified by mNGS in the cVM group, eight were negative with mNGS and seven were inconsistent with the conventional microbiological identification results. In addition, mNGS identified pathogens in 22 cases that were negative using conventional methods; of them, 10 patients received a favorable clinical treatment; thus, showing the benefit of mNGS-guided therapy.

Charting Extracellular Transcriptomes in The Human Biofluid RNA Atlas

Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease. Where most studies focus on blood-derived fluids, other biofluids may be more informative. We present an atlas of messenger, circular, and small RNA transcriptomes of a comprehensive collection of 20 human biofluids. By means of synthetic spike-in controls, we compare RNA content across biofluids, revealing a 10,000-fold difference in concentration. The circular RNA fraction is increased in most biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. Our atlas enables an informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Spike-normalized data are publicly available in the R2 web portal for further exploration.

Metagenomic Next-Generation Sequencing of Nasopharyngeal Specimens Collected from Confirmed and Suspect COVID-19 Patients

Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome.IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.

Search for viral agents in cerebrospinal fluid in patients with multiple sclerosis using real-time PCR and metagenomics

Multiple sclerosis (MS) is a chronic, immune-mediated demyelinating disease of the central nervous system of unclear etiology, but there is some evidence that viral infections could be responsible for triggering autoimmune mechanisms against myelin. We searched for viral RNA and DNA in cerebrospinal fluid (CSF) of 34 MS patients and 13 controls using RT-PCR/PCR against common neurotropic viruses. In addition, shotgun DNA- and RNA-based metagenomics were done in 13 MS patients and 4 controls. Specific quantitative real-time RT-PCR/PCR testing revealed the presence of viral nucleic acid in seven (20.59%) MS patients and in one (7.69%) control patient. In MS patients the most frequently detected was human herpesvirus type 6 (HHV-6; 3 cases; 8.82%); followed by Epstein-Barr virus (EBV; 2 cases; 5.88%), varicella zoster virus (VZV; 1 case; 2.94%) and Enterovirus (EV; 1 case; 2.94%). The single identified virus among controls was EBV (7.69%). DNA and RNA metagenomic assays did not identify any known eukaryotic viruses even though three of the analyzed samples were low-level positive by specific quantitative real-time PCR. In conclusion, we detected the presence of Herpesviridae and occasionally Enteroviridae in CSF from patients with MS but their prevalence was not significantly higher than among controls. Metagenomic analysis seems to be less sensitive than real-time RT-PCR/PCR and it did not detect any potential viral pathogens.

The reuse of public datasets in the life sciences: potential risks and rewards

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

Virome assembly and annotation in brain tissue based on next-generation sequencing

The glioblastoma multiforme (GBM) is one of the deadliest tumors. It has been speculated that virus plays a role in GBM but the evidences are controversy. Published researches are mainly limited to studies on the presence of human cytomegalovirus (HCMV) in GBM. No comprehensive assessment of the brain virome, the collection of viral material in the brain, based on recently sequenced data has been performed. Here, we characterized the virome from 111 GBM samples and 57 normal brain samples from eight projects in the SRA database by a tested and comprehensive assembly approach. The annotation of the assembled contigs showed that most viral sequences in the brain belong to the viral family Retroviridae. In some GBM samples, we also detected full genome sequence of a novel picornavirus recently discovered in invertebrates. Unlike previous reports, our study did not detect herpes virus such as HCMV in GBM from the data we used. However, some contigs that cannot be annotated with any known genes exhibited antibody epitopes in their sequences. These findings provide several avenues for potential cancer therapy: the newly discovered picornavirus could be a starting point to engineer novel oncolytic virus; and the exhibited antibody epitopes could be a source to explore potential drug targets for immune cancer therapy. By characterizing the virosphere in GBM and normal brain at a global level, the results from this study strengthen the link between GBM and viral infection which warrants the further investigation.

Taxon Appearance From Extraction and Amplification Steps Demonstrates the Value of Multiple Controls in Tick Microbiota Analysis

Background

The development of high-throughput sequencing technologies has substantially improved analysis of bacterial community diversity, composition, and functions. Over the last decade, high-throughput sequencing has been used extensively to identify the diversity and composition of tick microbial communities. However, a growing number of studies are warning about the impact of contamination brought along the different steps of the analytical process, from DNA extraction to amplification. In low biomass samples, e.g., individual tick samples, these contaminants may represent a large part of the obtained sequences, and thus generate considerable errors in downstream analyses and in the interpretation of results. Most studies of tick microbiota either do not mention the inclusion of controls during the DNA extraction or amplification steps, or consider the lack of an electrophoresis signal as an absence of contamination. In this context, we aimed to assess the proportion of contaminant sequences resulting from these steps. We analyzed the microbiota of individual Ixodes ricinus ticks by including several categories of controls throughout the analytical process: homogenization, DNA extraction, and DNA amplification.

Results

Controls yielded a significant number of sequences (1,126-13,198 mean sequences, depending on the control category). Some operational taxonomic units (OTUs) detected in these controls belong to genera reported in previous tick microbiota studies. In this study, these OTUs accounted for 50.9% of the total number of sequences in our samples, and were considered contaminants. Contamination levels (i.e., the percentage of sequences belonging to OTUs identified as contaminants) varied with tick instar and sex: 76.3% of nymphs and 75% of males demonstrated contamination over 50%, while most females (65.7%) had rates lower than 20%. Contamination mainly corresponded to OTUs detected in homogenization and extraction reagent controls, highlighting the importance of carefully controlling these steps.

Conclusion

Here, we showed that contaminant OTUs from sample laboratory processing steps can represent more than half the total sequence yield in sequencing runs, and lead to unreliable results when characterizing tick microbial communities. We thus strongly advise the routine use of negative controls in tick microbiota studies, and more generally in studies involving low biomass samples.

Poor Unstable Midgut Microbiome of Hard Ticks Contrasts With Abundant and Stable Monospecific Microbiome in Ovaries

Culture-independent metagenomic methodologies have enabled detection and identification of microorganisms in various biological systems and often revealed complex and unknown microbiomes. In many organisms, the microbiome outnumbers the host cells and greatly affects the host biology and fitness. Ticks are hematophagous ectoparasites with a wide host range. They vector a number of human and animal pathogens and also directly cause major economic losses in livestock. Although several reports on a tick midgut microbiota show a diverse bacterial community, in most cases the size of the bacterial population has not been determined. In this study, the microbiome was quantified in the midgut and ovaries of the ticks Ixodes ricinus and Rhipicephalus microplus before, during, and after blood feeding. Although the size of bacterial community in the midgut fluctuated with blood feeding, it was overall extremely low in comparison to that of other hematophagous arthropods. In addition, the tick ovarian microbiome of both tick species exceeded the midgut 16S rDNA copy numbers by several orders of magnitude. This indicates that the ratio of a tick midgut/ovary microbiome represents an exception to the general biology of other metazoans. In addition to the very low abundance, the tick midgut diversity in I. ricinus was variable and that is in contrast to that found in the tick ovary. The ovary of I. ricinus had a very low bacterial diversity and a very high and stable bacterial abundance with the dominant endosymbiont, Midichloria sp. The elucidation of this aspect of tick biology highlights a unique tissue-specific microbial-invertebrate host interaction.

CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data

There is an increasing demand for accurate and fast metagenome classifiers that can not only identify bacteria, but all members of a microbial community. We used a recently developed concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. The pipeline substantially outperforms other commonly used software in identifying bacteria and fungi and can efficiently use the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms. CCMetagen is user-friendly, and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.

Chronic Corynebacterium striatum Septic Arthritis in a Patient Referred for Total Knee Arthroplasty

BACKGROUND

While Corynebacterium striatum and other Corynebacterium species were historically considered contaminants, they are recently being identified as pathogens with increasing frequency. Case Summary. We report the case of a 78-year-old gentleman with a three-year history of knee pain and established diagnosis of osteoarthritis referred for consideration for total knee arthroplasty. He had no knee pain with passive range-of-motion. Plain films demonstrated bony erosions atypical for osteoarthritis. Joint aspiration white blood cell count was 30,548/mm3, but multiple cultures were positive for C. striatum. The infection was successfully treated with open irrigation and debridement, complete synovectomy, and six weeks of intravenous daptomycin.

CONCLUSION

To our knowledge, this is the first report of chronic C. striatum septic arthritis of a native joint and only the third case of C. striatum septic arthritis of the knee.C. striatum. The infection was successfully treated with open irrigation and debridement, complete synovectomy, and six weeks of intravenous daptomycin. C. striatum. The infection was successfully treated with open irrigation and debridement, complete synovectomy, and six weeks of intravenous daptomycin.

What human sperm RNA-Seq tells us about the microbiome

PURPOSE

The study was designed to assess the capacity of human sperm RNA-seq data to gauge the diversity of the associated microbiome within the ejaculate.

METHODS

Semen samples were collected, and semen parameters evaluated at time of collection. Sperm RNA was isolated and subjected to RNA-seq. Microbial composition was determined by aligning sequencing reads not mapped to the human genome to the NCBI RefSeq bacterial, viral and archaeal genomes following RNA-Seq. Analysis of microbial assignments utilized phyloseq and vegan.

RESULTS

Microbial composition within each sample was characterized as a function of microbial associated RNAs. Bacteria known to be associated with the male reproductive tract were present at similar levels in all samples representing 11 genera from four phyla with one exception, an outlier. Shannon diversity index (p < 0.001) and beta diversity (unweighted UniFrac distances, p = 9.99e-4; beta dispersion, p = 0.006) indicated the outlier was significantly different from all other samples. The outlier sample exhibited a dramatic increase in Streptococcus. Multiple testing indicated two operational taxonomic units, S. agalactiae and S. dysgalactiae (p = 0.009), were present.

CONCLUSION

These results provide a first look at the microbiome as a component of human sperm RNA sequencing that has sufficient sensitivity to identify contamination or potential pathogenic bacterial colonization at least among the known contributors.