STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies

Diagnostic Stewardship for Next-Generation Sequencing Assays in Clinical Microbiology: An Appeal for Thoughtful Collaboration

Next-generation sequencing (NGS)-based assays are primarily available from reference laboratories for diagnostic use. These tests can provide helpful diagnostic data but also can be overused by ordering providers not fully understanding their limitations. At present, there are few best practice guidelines for use. NGS-based assays can carry a high cost to institutions and individual patients, requiring thoughtful use through application of diagnostic stewardship principles. This article provides an overview of diagnostic stewardship approaches as applied to these assays, focusing on principles of collaboration, differential diagnosis formation, and seeking the best patient, syndrome, sample, timing, and test for improved patient care.

The Report Says What?: How the Medical Microbiologist can aid in the Interpretation of Next-Generation Sequencing Results

The applications of next-generation sequencing (NGS) in the clinical microbiology laboratory are expanding at a rapid pace. The medical microbiologist thus plays a key role in translating the results of these emerging technologies to the practicing clinician. Here we discuss the factors to consider to successfully develop standardized reporting for microbial targeted or metagenomic NGS testing in the clinical laboratory.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

Case report: Metagenomics next-generation sequencing in the diagnosis of septic shock due to Fusobacterium necrophorum in a 6-year-old child

Fusobacterium necrophorum (F. necrophorum) infection is rare in pediatrics. In addition, the detection time of F. necrophorum by blood culture is long, and the positive rate is low. Infection with F. necrophorum bacilli usually follows rapid disease progression, resulting in high mortality. In previous reports of F. necrophorum-related cases, the most dangerous moment of the disease occurred after the appearance of Lemierre's syndrome. We report an atypical case of a 6-year-old female patient who developed septic shock within 24 h of admission due to F. necrophorum infection in the absence of Lemierre's syndrome. F. necrophorum was identified in a blood sample by metagenomics next-generation sequencing (mNGS) but not by standard blood culture. The patient was finally cured and discharged after receiving timely and effective targeted anti-infection treatment. In the present case study, it was observed that the heightened virulence and invasiveness of F. necrophorum contribute significantly to its role as a primary pathogen in pediatric septic shock. This can precipitate hemodynamic instability and multiple organ failure, even in the absence of Lemierre's syndrome. The use of mNGS can deeply and rapidly identify infectious pathogens, guide the use of targeted antibiotics, and greatly improve the survival rate of patients.

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.

Performance of clinical metagenomics in France: a prospective observational study

BACKGROUND

Metagenomic next-generation sequencing (mNGS) allows untargeted identification of a broad range of pathogens, including rare or novel microorganisms. Despite the recognition of mNGS as a valuable diagnostic tool for infections, the most relevant indications for this innovative strategy remain poorly defined. We aimed to assess the determinants of positivity and clinical utility of mNGS.

METHODS

In this observational study, we prospectively performed short-read shotgun metagenomics analysis as a second-line test (in cases of negative first-line test or when the symptoms were not fully explained by initial positive results) or as a first-line test in life-threatening situations requiring urgent non-targeted pathogen identification at the Necker-Enfants Malades Hospital (Paris, France). All sample types, clinical indications, and patient populations were included. Samples were accompanied by a mandatory form completed by the senior clinician or pathologist, on which the clinical level of suspected infection (defined as high or low) was indicated. We assessed the variables (gender, age, immune status, initial suspicion of infection, indication, and sample type) associated with mNGS pathogen detection using odds ratios (ORs) from multivariate logistic regression. Additional investigations were carried out using specific PCR or culture techniques, to confirm positive mNGS results, or when infectious suspicion was particularly high despite a negative mNGS result.

FINDINGS

Between Oct 29, 2019, and Nov 7, 2022, we analysed 742 samples collected from 523 patients. The initial suspicion of infection was either high (n=470, 63%) or low (n=272, 37%). Causative or possibly causative pathogens were detected in 117 (25%) samples from patients with high initial suspicion of infection, versus nine (3%) samples analysed to rule out infection (OR 9·1, 95% CI 4·6-20·4; p<0·0001). We showed that mNGS had higher odds of detecting a causative or possibly causative pathogenic virus on CNS biopsies than CSF samples (4·1, 1·7-10·7; p=0·0025) and in samples from immunodeficient compared with immunocompetent individuals (2·4, 1·4-4·1; p=0·0013). Concordance with conventional confirmatory tests results was 103 (97%) of 106, when mNGS detected causative or possibly causative pathogens. Altogether, among 231 samples investigated by both mNGS and subsequent specific tests, discordant results were found in 69 (30%) samples, of which 58 (84%) were mNGS positive and specific tests negative, and 11 (16%) mNGS negative and specific tests positive.

INTERPRETATION

Major determinants of pathogen detection by mNGS are immune status and initial level of suspicion of infection. These findings will contribute, along with future studies, to refining the positioning of mNGS in diagnostic and treatment decision-making algorithms.

FUNDING

Necker-Enfants Malades Hospital and Institut Pasteur.

TRANSLATION

For the French translation of the abstract see Supplementary Materials section.

The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes

BACKGROUND

Metagenomic data can shed light on animal-microbiome relationships and the functional potential of these communities. Over the past years, the generation of metagenomics data has increased exponentially, and so has the availability and reusability of data present in public repositories. However, identifying which datasets and associated metadata are available is not straightforward. We created the Animal-Associated Metagenome Metadata Database (AnimalAssociatedMetagenomeDB - AAMDB) to facilitate the identification and reuse of publicly available non-human, animal-associated metagenomic data, and metadata. Further, we used the AAMDB to (i) annotate common and scientific names of the species; (ii) determine the fraction of vertebrates and invertebrates; (iii) study their biogeography; and (iv) specify whether the animals were wild, pets, livestock or used for medical research.

RESULTS

We manually selected metagenomes associated with non-human animals from SRA and MG-RAST.  Next, we standardized and curated 51 metadata attributes (e.g., host, compartment, geographic coordinates, and country). The AAMDB version 1.0 contains 10,885 metagenomes associated with 165 different species from 65 different countries. From the collected metagenomes, 51.1% were recovered from animals associated with medical research or grown for human consumption (i.e., mice, rats, cattle, pigs, and poultry). Further, we observed an over-representation of animals collected in temperate regions (89.2%) and a lower representation of samples from the polar zones, with only 11 samples in total. The most common genus among invertebrate animals was Trichocerca (rotifers).

CONCLUSION

Our work may guide host species selection in novel animal-associated metagenome research, especially in biodiversity and conservation studies. The data available in our database will allow scientists to perform meta-analyses and test new hypotheses (e.g., host-specificity, strain heterogeneity, and biogeography of animal-associated metagenomes), leveraging existing data. The AAMDB WebApp is a user-friendly interface that is publicly available at https://webapp.ufz.de/aamdb/ .

Untargeted metagenomics protocol for the diagnosis of infection from CSF and tissue from sterile sites

Metagenomic next-generation sequencing (mNGS) is an untargeted technique capable of detecting all microbial nucleic acid within a sample. This protocol outlines our wet laboratory method for mNGS of cerebrospinal fluid (CSF) specimens and tissues from sterile sites. We use this method routinely in our clinical service, processing 178 specimens over the past 2.5 years in a laboratory that adheres to ISO:15189 standards. We have successfully used this protocol to diagnose multiple cases of encephalitis and hepatitis.

Targeting the 16S rRNA Gene by Reverse Complement PCR Next-Generation Sequencing: Specific and Sensitive Detection and Identification of Microbes Directly in Clinical Samples

The detection and accurate identification of bacterial species in clinical samples are crucial for diagnosis and appropriate antibiotic treatment. To date, sequencing of the 16S rRNA gene has been widely used as a complementary molecular approach when identification by culture fails. The accuracy and sensitivity of this method are highly affected by the selection of the 16S rRNA gene region targeted. In this study, we assessed the clinical utility of 16S rRNA reverse complement PCR (16S RC-PCR), a novel method based on next-generation sequencing (NGS), for the identification of bacterial species. We investigated the performance of 16S RC-PCR on 11 bacterial isolates, 2 polymicrobial community samples, and 59 clinical samples from patients suspected of having a bacterial infection. The results were compared to culture results, if available, and to the results of Sanger sequencing of the 16S rRNA gene (16S Sanger sequencing). By 16S RC-PCR, all bacterial isolates were accurately identified to the species level. Furthermore, in culture-negative clinical samples, the rate of identification increased from 17.1% (7/41) to 46.3% (19/41) when comparing 16S Sanger sequencing to 16S RC-PCR. We conclude that the use of 16S RC-PCR in the clinical setting leads to an increased sensitivity of detection of bacterial pathogens, resulting in a higher number of diagnosed bacterial infections, and thereby can improve patient care. IMPORTANCE The identification of the causative infectious pathogen in patients suspected of having a bacterial infection is essential for diagnosis and the start of appropriate treatment. Over the past 2 decades, molecular diagnostics have improved the ability to detect and identify bacteria. However, novel techniques that can accurately detect and identify bacteria in clinical samples and that can be implemented in clinical diagnostics are needed. Here, we demonstrate the clinical utility of bacterial identification in clinical samples by a novel method called 16S RC-PCR. Using 16S RC-PCR, we reveal a significant increase in the number of clinical samples in which a potentially clinically relevant pathogen is identified compared to the commonly used 16S Sanger method. Moreover, RC-PCR allows automation and is well suited for implementation in a diagnostic laboratory. In conclusion, the implementation of this method as a diagnostic tool is expected to result in an increased number of diagnosed bacterial infections, and in combination with adequate treatment, this could improve clinical outcomes for patients.

Realising respiratory microbiomic meta-analyses: time for a standardised framework

In microbiome fields of study, meta-analyses have proven to be a valuable tool for identifying the technical drivers of variation among studies and results of investigations in several diseases, such as those of the gut and sinuses. Meta-analyses also represent a powerful and efficient approach to leverage existing scientific data to both reaffirm existing findings and generate new hypotheses within the field. However, there are currently limited data in other fields, such as the paediatric respiratory tract, where extension of original data becomes even more critical due to samples often being difficult to obtain and process for a range of both technical and ethical reasons. Performing such analyses in an evolving field comes with challenges related to data accessibility and heterogeneity. This is particularly the case in paediatric respiratory microbiomics - a field in which best microbiome-related practices are not yet firmly established, clinical heterogeneity abounds and ethical challenges can complicate sharing of patient data. Having recently conducted a large-scale, individual participant data meta-analysis of the paediatric respiratory microbiota (n = 2624 children from 20 studies), we discuss here some of the unique barriers facing these studies and open and invite a dialogue towards future opportunities. Video Abstract.

A case for investment in clinical metagenomics in low-income and middle-income countries

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

The oropharynx of men using HIV pre-exposure prophylaxis is enriched with antibiotic resistance genes: A cross-sectional observational metagenomic study

BACKGROUND

Phenotypic studies have found high levels of antimicrobial resistance to cephalosporins, macrolides and fluoroquinolones in commensal Neisseria species in the oropharynx of men who have sex with men (MSM) using HIV pre-exposure prophylaxis (PrEP). These species include Neisseria subflava and Neisseria mucosa. This may represent a risk to pathogens like Neisseria gonorrhoeae which tend to take up antibiotic resistance genes (ARGs) from other bacteria. We aimed to explore to what extent the oropharyngeal resistome of MSM using PrEP differed from the general population.

METHODS

We collected oropharyngeal swabs from 32 individuals of the general population and from 64 MSM using PrEP. Thirty-two MSM had consumed antibiotics in the previous six months, whereas none of the other participants had. Samples underwent shotgun metagenomic sequencing. Sequencing reads were mapped against MEGARes 2.0 to estimate ARG abundance. ARG abundance was compared between groups by zero-inflated negative binomial regression.

FINDINGS

ARG abundance was significantly lower in the general population than in MSM (ratio 0.41, 95% CI 0.26-0.65). More specifically, this was the case for fluoroquinolones (0.33, 95% CI 0.15-0.69), macrolides (0.37, 95% CI 0.25-0.56), tetracyclines (0.41, 95% CI 0.25-0.69), and multidrug efflux pumps (0.11, 95% CI 0.03-0.33), but not for beta-lactams (1.38, 95% CI 0.73-2.61). There were no significant differences in ARG abundance between MSM who had used antibiotics and those that had not.

INTERPRETATION

The resistome of MSM using PrEP is enriched with ARGs, independent of recent antibiotic use. Stewardship campaigns should aim to reduce antibiotic consumption in populations at high risk for STIs.

Metagenomics by next-generation sequencing (mNGS) in the etiological characterization of neonatal and pediatric sepsis: A systematic review

Introduction

Pediatric and neonatal sepsis is one of the main causes of mortality and morbidity in these age groups. Accurate and early etiological identification is essential for guiding antibiotic treatment, improving survival, and reducing complications and sequelae. Currently, the identification is based on culture-dependent methods, which has many limitations for its use in clinical practice, and obtaining its results is delayed. Next-generation sequencing enables rapid, accurate, and unbiased identification of multiple microorganisms in biological samples at the same time. The objective of this study was to characterize the etiology of neonatal and pediatric sepsis by metagenomic techniques.

Methods

A systematic review of the literature was carried out using the PRISMA-2020 guide. Observational, descriptive, and case report studies on pediatric patients were included, with a diagnostic evaluation by clinical criteria of sepsis based on the systemic inflammatory response, in sterile and non-sterile biofluid samples. The risk of bias assessment of the observational studies was carried out with the STROBE-metagenomics instrument and the CARE checklist for case reports.

Results and Discussion

Five studies with a total of 462 patients were included. Due to the data obtained from the studies, it was not possible to perform a quantitative synthesis (meta-analysis). Based on the data from the included studies, the result identified that mNGS improves the etiological identification in neonatal and pediatric sepsis, especially in the context of negative cultures and in the identification of unusual microorganisms (bacteria that are difficult to grow in culture, viruses, fungi, and parasites). The number of investigations is currently limited, and the studies are at high risk of bias. Further research using this technology would have the potential to improve the rational use of antibiotics.

Probiotic supplementation for neonates with congenital gastrointestinal surgical conditions: guidelines for future research

Our pilot RCT found that probiotic supplementation with the three-strain bifidobacterial product (B. breve M-16V, B. longum subsp. infantis M-63 and B. longum subsp. longum BB536) attenuates gut dysbiosis, increases stool short-chain fatty acid (SCFA) levels and improves the growth of head circumference in neonates with congenital gastrointestinal surgical conditions (CGISC). In this article, we have provided guidelines for designing future multicentre RCTs based on the experience gained from our pilot RCT. The recommendations include advice about sample size, potential confounders, outcomes of interest, probiotic strain selection, storage, dose, duration and microbial quality assurance, collection of stool samples, storage and analysis and reporting. Following these guidelines will increase the validity of future RCTs in this area and hence confidence in their results. IMPACT: Probiotic supplementation attenuates gut dysbiosis, increases stool short-chain fatty acid (SCFA) levels and improves the growth of head circumference in neonates with congenital gastrointestinal surgical conditions. The current review provides evidence-based guidelines to conduct adequately powered RCTs in this field.

The oral cancer microbiome contains tumor space-specific and clinicopathology-specific bacteria

The crosstalk between the oral microbiome and oral cancer has yet to be characterized. This study recruited 218 patients for clinicopathological data analysis. Multiple types of specimens were collected from 27 patients for 16S rRNA gene sequencing, including 26 saliva, 16 swabs from the surface of tumor tissues, 16 adjacent normal tissues, 22 tumor outer tissue, 22 tumor inner tissues, and 10 lymph nodes. Clinicopathological data showed that the pathogenic bacteria could be frequently detected in the oral cavity of oral cancer patients, which was positively related to diabetes, later T stage of the tumor, and the presence of cervical lymphatic metastasis. Sequencing data revealed that compared with adjacent normal tissues, the microbiome of outer tumor tissues had a greater alpha diversity, with a larger proportion of Fusobacterium, Prevotella, and Porphyromonas, while a smaller proportion of Streptococcus. The space-specific microbiome, comparing outer tumor tissues with inner tumor tissues, suggested minor differences in diversity. However, Fusobacterium, Neisseria, Porphyromonas, and Alloprevotella were more abundant in outer tumor tissues, while Prevotella, Selenomonas, and Parvimonas were enriched in inner tumor tissues. Clinicopathology-specific microbiome analysis found that the diversity was markedly different between negative and positive extranodal extensions, whereas the diversity between different T-stages and N-stages was slightly different. Gemella and Bacillales were enriched in T1/T2-stage patients and the non-lymphatic metastasis group, while Spirochaetae and Flavobacteriia were enriched in the extranodal extension negative group. Taken together, high-throughput DNA sequencing in combination with clinicopathological features facilitated us to characterize special patterns of oral tumor microbiome in different disease developmental stages.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Clinical characteristics of the host DNA-removed metagenomic next-generation sequencing technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology

BACKGROUND

Metagenomic next-generation sequencing (mNGS) technology has been central in detecting infectious diseases and helping to simultaneously reveal the complex interplay between invaders and their hosts immune response characteristics. However, it needs to be rigorously assessed for clinical utility. The present study is the first to evaluate the clinical characteristics of the host DNA-removed mNGS technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology.

METHODS

46 swab specimens collected from COVID-19 patients were assayed by two approved commercial RT-qPCR kits and mNGS. The evolutionary tree of SARS-CoV-2 was plotted using FigTree directly from one sample. The workflow of removing the host and retaining the host was compared to investigate the influence of host DNA removal on the performances of mNGS. Functional enrichment analysis of DEGs and xCell score were used to explore the characteristics of host local immune signaling.

RESULTS

The detection rate of mNGS achieved 92.9% (26/28) for 28 samples with a Ct value ≤ 35 and 81.1% (30/37) for all 46 samples. The genome coverage of SARS-CoV-2 could reach up to 98.9% when the Ct value is about 20 in swab samples. Removing the host could enhance the sensitivity of mNGS for detecting SARS-CoV-2 from the swab sample but does not affect the species abundance of microbes RNA. Improving the sequencing depth did not show a positive effect on improving the detection sensitivity of SARS-CoV-2. Cell type enrichment scores found multiple immune cell types were differentially expressed between patients with high and low viral load.

CONCLUSIONS

The host DNA-removed mNGS has great potential utility and superior performance on comprehensive identification of SARS-CoV-2 and rapid traceability, revealing the microbiome's transcriptional profiles and host immune responses.

The association between early-life gut microbiota and childhood respiratory diseases: a systematic review

Data from animal models suggest a role of early-life gut microbiota in lung immune development, and in establishing susceptibility to respiratory infections and asthma in humans. This systematic review summarises the association between infant (ages 0-12 months) gut microbiota composition measured by genomic sequencing, and childhood (ages 0-18 years) respiratory diseases (ie, respiratory infections, wheezing, or asthma). Overall, there was evidence that low α-diversity and relative abundance of particular gut-commensal bacteria genera (Bifidobacterium, Faecalibacterium, Ruminococcus, and Roseburia) are associated with childhood respiratory diseases. However, results were inconsistent and studies had important limitations, including insufficient characterisation of bacterial taxa to species level, heterogeneous outcome definitions, residual confounding, and small sample sizes. Large longitudinal studies with stool sampling during the first month of life and shotgun metagenomic approaches to improve bacterial and fungal taxa resolution are needed. Standardising follow-up times and respiratory disease definitions and optimising causal statistical approaches might identify targets for primary prevention of childhood respiratory diseases.

The rise to power of the microbiome: power and sample size calculation for microbiome studies

A priori power and sample size calculations are crucial to appropriately test null hypotheses and obtain valid conclusions from all clinical studies. Statistical tests to evaluate hypotheses in microbiome studies need to consider intrinsic features of microbiome datasets that do not apply to classic sample size calculation. In this review, we summarize statistical approaches to calculate sample sizes for typical microbiome study scenarios, including those that hypothesize microbiome features to be the outcome, the exposure or the mediator, and provide relevant R scripts to conduct some of these calculations. This review is intended to be a resource to facilitate the conduct of sample size calculations that are based on testable hypotheses across several dimensions of the microbiome. Implementation of these methods will improve the quality of human or animal microbiome studies, enabling reliable conclusions that will generalize beyond the study sample.

Campylobacter Species, Microbiological Source Tracking and Risk Assessment of Bacterial pathogens

Campylobacter species continue to remain critical pathogens of public health interest. They are responsible for approximately 500 million cases of gastroenteritis per year worldwide. Infection occurs through the consumption of contaminated food and water. Microbial risk assessment and source tracking are crucial epidemiological strategies to monitor the outbreak of campylobacteriosis effectively. Various methods have been proposed for microbial source tracking and risk assessment, most of which rely on conventional microbiological techniques such as detecting fecal indicator organisms and other novel microbial source tracking methods, including library-dependent microbial source tracking and library-independent source tracking approaches. However, both the traditional and novel methods have their setbacks. For example, while the conventional techniques are associated with a poor correlation between indicator organism and pathogen presence, on the other hand, it is impractical to interpret qPCR-generated markers to establish the exact human health risks even though it can give information regarding the potential source and relative human risk. Therefore, this article provides up-to-date information on campylobacteriosis, various approaches for source attribution, and risk assessment of bacterial pathogens, including next-generation sequencing approaches such as shotgun metagenomics, which effectively answer the questions of potential pathogens are there and in what quantities.

Beta-diversity distance matrices for microbiome sample size and power calculations - How to obtain good estimates

In microbiome studies, researchers often wish to compare the taxa count distributions between groups of samples. Commonly-used corresponding methods of analysis are built on examining distance matrices, where distances describe the beta-diversity between samples. Analyses then compare the distribution of distances within groups to the distributions between groups. However, when performing a priori sample size or power calculations for such study designs, appropriate within and between group distance distributions can be challenging to obtain. When available, pilot study data, or data from prior studies of similar design should provide realistic distance estimates. However, when these are not available, distances can be extracted from available studies where one can assume similar beta-diversity. Alternatively, distances can be generated by simulation methods. Here, we describe and illustrate these three strategies for obtaining realistic distance matrices. For simulation methods, we illustrate the procedures required starting from existing benchmark data, as well as how to simulate directly from population assumptions. Using data from the American Gut project, we provide tables of observed distances for use by researchers planning their own studies, as well as R codes for generating similar matrices in other datasets. Furthermore, for simulated data, we compare methods, provide R codes, and demonstrate how challenging it is to obtain realistic distance distributions without any benchmark data. This code and illustrative distance tables are provided by the IMPACTT Consortium as a resource to the microbiome research community.

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.

Metatranscriptomics Analysis Reveals Diverse Viral RNA in Cutaneous Papillomatous Lesions of Cattle

Bovine papillomavirus (BPV) is associated with bovine papillomatosis, a disease that forms benign warts in epithelial tissues, as well as malignant lesions. Previous studies have detected a co-infection between BPV and other viruses, making it likely that these co-infections could influence disease progression. Therefore, this study aimed to identify and annotate viral genes in cutaneous papillomatous lesions of cattle. Sequences were obtained from the GEO database, and an RNA-seq computational pipeline was used to analyze 3 libraries from bovine papillomatous lesions. In total, 25 viral families were identified, including Poxviridae, Retroviridae, and Herpesviridae. All libraries shared similarities in the viruses and genes found. The viral genes shared similarities with BPV genes, especially for functions as virion entry pathway, malignant progression by apoptosis suppression and immune system control. Therefore, this study presents relevant data extending the current knowledge regarding the viral microbiome in BPV lesions and how other viruses could affect this disease.

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.

Impact of gastrointestinal surgery upon the gut microbiome: A systematic review

BACKGROUND

There is evidence from preclinical models that the gut microbiome may impact outcomes from gastrointestinal surgery, and that surgery may alter the gut microbiome. However, the extent to which gastrointestinal surgery modulates the gut microbiome in clinical practice is currently poorly defined. This systematic review aims to evaluate the changes observed in the gut microbiome after gastrointestinal surgery.

METHODS

A systematic review and meta-analysis were conducted according to the PRISMA guidelines by screening EMBASE, MEDLINE/PubMed, Web of Science, and CENTRAL for comparative studies meeting the predetermined inclusion criteria. The primary outcome was the difference between pre and postoperative bacterial taxonomic composition and diversity metrics among patients receiving gastrointestinal surgery.

RESULTS

In total, 33 studies were identified including 6 randomized controlled trials and 27 prospective cohort studies reporting a total of 968 patients. Gastrointestinal surgery was associated with an increase in α diversity and a shift in β diversity postoperatively. Multiple bacterial taxa were identified to consistently trend toward an increase or decrease postoperatively. A difference in microbiota across geographic provenance was also observed. There was a distinct lack of studies showing correlation with clinical outcomes or performing microbiome functional analysis. Furthermore, there was a lack of standardization in sampling, analytical methodology, and reporting.

CONCLUSION

This review highlights changes in bacterial taxa associated with gastrointestinal surgery. There is a need for standardization of microbial analysis methods and reporting of results to allow interstudy comparison. Further adequately powered multicenter studies are required to better assess variation in microbial changes and its potential associations with clinical outcomes.

Metrological framework to support accurate, reliable, and reproducible nucleic acid measurements

Nucleic acid analysis is used in many areas of life sciences such as medicine, food safety, and environmental monitoring. Accurate, reliable measurements of nucleic acids are crucial for maximum impact, yet users are often unaware of the global metrological infrastructure that exists to support these measurements. In this work, we describe international efforts to improve nucleic acid analysis, with a focus on the Nucleic Acid Analysis Working Group (NAWG) of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology (CCQM). The NAWG is an international group dedicated to improving the global comparability of nucleic acid measurements; its primary focus is to support the development and maintenance of measurement capabilities and the dissemination of measurement services from its members: the National Metrology Institutes (NMIs) and Designated Institutes (DIs). These NMIs and DIs provide DNA and RNA measurement services developed in response to the needs of their stakeholders. The NAWG members have conducted cutting edge work over the last 20 years, demonstrating the ability to support the reliability, comparability, and traceability of nucleic acid measurement results in a variety of sectors.

Reporting guidelines for human microbiome research: the STORMS checklist

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

Tracing Viral Transmission and Evolution of Bovine Leukemia Virus through Long Read Oxford Nanopore Sequencing of the Proviral Genome

Bovine leukemia virus (BLV) causes Enzootic Bovine Leukosis (EBL), a persistent life-long disease resulting in immune dysfunction and shortened lifespan in infected cattle, severely impacting the profitability of the US dairy industry. Our group has found that 94% of dairy farms in the United States are infected with BLV with an average in-herd prevalence of 46%. This is partly due to the lack of clinical presentation during the early stages of primary infection and the elusive nature of BLV transmission. This study sought to validate a near-complete genomic sequencing approach for reliability and accuracy before determining its efficacy in characterizing the sequence identity of BLV proviral genomes collected from a pilot study made up of 14 animals from one commercial dairy herd. These BLV-infected animals were comprised of seven adult dam/daughter pairs that tested positive by ELISA and qPCR. The results demonstrate sequence identity or divergence of the BLV genome from the same samples tested in two independent laboratories, suggesting both vertical and horizontal transmission in this dairy herd. This study supports the use of Oxford Nanopore sequencing for the identification of viral SNPs that can be used for retrospective genetic contact tracing of BLV transmission.

Metagenomic evidence for a polymicrobial signature of sepsis

Our understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterize the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera [area under the receiver operating characteristic (AUROC=0.995)], including after removal of species ‘culture-confirmed’ as the cause of sepsis through clinical testing (AUROC=0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls. While prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis, and ultimately support the development of clinical diagnostic or even prognostic tools.

The CRCbiome study: a large prospective cohort study examining the role of lifestyle and the gut microbiome in colorectal cancer screening participants

BACKGROUND

Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions.

METHODS

The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50-74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period.

DISCUSSION

The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01538550 .

Metagenomic Sequencing as a Pathogen-Agnostic Clinical Diagnostic Tool for Infectious Diseases: a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies

Metagenomic sequencing is frequently claimed to have the potential to revolutionize microbiology through rapid species identification and antimicrobial resistance (AMR) prediction. We assess the progress toward these developments. We perform a systematic review and meta-analysis of all published literature on culture-independent metagenomic sequencing for pathogen-agnostic infectious disease diagnostics up to 12 August 2020. Methodologic bias and applicability were assessed using the tool Quadas-2. (Prospero CRD42020163777). A total of 2,023 clinical samples from 13/21 eligible diagnostic test accuracy studies were included in the meta-analysis. Reference standards were culture, molecular testing, clinical decision, or a composite measure. Sensitivity and specificity in the most widely investigated sample types were 90% (95% confidence interval [CI], 78% to 96%) and 86% (45% to 98%) for blood, 75% (54% to 89%) and 96% (72% to 100%) for cerebrospinal fluid (CSF), and 84% (79% to 88%) and 67% (38% to 87%) for orthopedic samples, respectively. We identified a limited use of controls, especially negative controls which were used in only 62% (13/21) of studies. AMR prediction and comparison to phenotypic results were undertaken in four studies; categorical agreement was 88%(80% to 97%), and very major and major error rates were 24% (8% to 40%) and 5% (0% to 12%), respectively. Better human DNA depletion methods are required; a median 91% (interquartile range [IQR], 82% to 98%; range, 76% to 98%) of sequences was classified as human. The median (IQR; range) time from sample to result was 29 hours (24 to 94; 4 to 144 hours). The reported consumable cost per sample ranged from $130 to $685. There is scope for improving the quality of reporting in clinical metagenomic studies. Although our results are limited by the heterogeneity displayed, our results reflect a promising outlook for clinical metagenomics. Methodological improvements and convergence around protocols and best practices may improve performance in the future.

Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples

INTRODUCTION

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories.

METHODS

Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analyzed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analyzed.

RESULTS

Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection.

CONCLUSION

A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

Cross-correlation of virome-bacteriome-host-metabolome to study respiratory health

A comprehensive understanding of the microbiome-host relationship in respiratory diseases can be elucidated by exploring the landscape of virome-bacteriome-host metabolome data through unsupervised 'multi-omics' approaches. Here, we describe how the composition and function of airway and gut virome and bacteriome may contribute to pathogen establishment and propagation in airway districts and how the virome-bacteriome communities may react to respiratory diseases. A new systems medicine approach, including the characterization of respiratory and gut microbiome, may be crucial to demonstrate the likelihood and odds of respiratory disease pathophysiology, opening new avenues to the discovery of a chain of causation for key bacteria and viruses in disease severity.

Precision Pandemic Preparedness: Improving Diagnostics with Metagenomics

The threat posed by novel pandemics in the future remains active. Equipping our routine laboratory with clinical metagenomics to detect unknown threats early on offers a considerable advantage and may be feasible and scalable with the ability to identify complicated infectious diseases in routine care. Though several technical and regulatory challenges still exist, clinical metagenomics may improve individual patient outcomes and provide earlier warning signs to improve pandemic preparedness.