Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation

Case report: isolated prevotella intermedia causing intracranial infection detected using metagenomic next generation sequencing

BACKGROUND

Isolated Prevotella intermedia, a rare gram-negative, rod-shaped, anaerobic bacterium, is rarely detected in clinical practice. It has been associated with infections of the oral cavity and female genital tract, but has never been detected in cerebrospinal fluid (CSF) of patients in China. Accurate detection of causative pathogens is still an arduous task owing to the difficult conditions of anaerobic bacterial culture. Isolated Prevotella intermedia can be detected by metagenomic next generation sequencing (mNGS) of the CSF. Correct diagnosis and antibiotic treatment can help patients avoid life-threatening events.

CASE PRESENTATION

Herein, we describe the case of a 64-year-old Chinese woman who presented with typical features of meningoencephalitis. Routine CSF culture failed to identify the causative pathogen. Isolated Prevotella intermedia was detected by mNGS, and the patient was treated with antibacterial agents including ceftriaxone, vancomycin, moxifloxacin, meropenem, metronidazole, and linezolid. The patient underwent surgical treatment for abscess of left frontal parietal lobe, which was observed on magnetic resonance imaging (MRI) and was suspected to be caused by Prevotella intermedia. It was further confirmed that it was a secondary infection from the oral cavity, and the possible etiology might have been dental surgery. Treatment was rendered to the patient based on metagenomic test result, and her condition improved after two months.

CONCLUSIONS

This case highlights the role of mNGS in accurate diagnosis of patients with central nervous system infection. In particular, mNGS can be used to identify rare pathogens and confirm the diagnosis in patients with unknown etiology.

Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis

The multi-batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision-making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene-derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome-based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome-specific methods for accounting for or correcting them.

Addressing antibiotic resistance: computational answers to a biological problem?

The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance.

Chlamydia psittaci pneumonia: a clinical analysis of 12 patients

Background

We conducted a retrospective analysis to explore the clinical characteristics, laboratory examination, imaging features, treatment outcomes, and prognosis of the Chlamydia psittaci (C. psittaci) pneumonia, aiming to improve early diagnosis and treatment.

Methods

The clinical data of 12 patients with C. psittaci pneumonia diagnosed by metagenomic next-generation sequencing (mNGS) in our hospital were retrospectively analyzed. These data included baseline information, epidemiological history, clinical symptoms and signs, laboratory and chest computed tomography (CT) examination findings, treatment schemes, and prognosis.

Results

The average age of the 12 patients was 58.25±13.27 years, and there were 7 (58.3%) males and 5 (41.7%) females in this cohort. Five patients had clear exposure to poultry or birds. The main clinical manifestations included fever (12/12, 100.0%), cough (12/12, 100.0%), expectoration (10/12, 83.3%), and dyspnea (10/12, 83.3%). Laboratory examination showed marked elevation of the total white blood cell (WBC) count, neutrophil (NEUT) count, C-reactive protein (CRP), procalcitonin (PCT), D-dimer, aspartate aminotransferase (AST), alanine aminotransferase (ALT), serum creatinine, and creatine kinase (CK) levels; as well as decreased hemoglobin (HGB), blood platelet (PLT), and albumin (ALB) levels. Arterial blood gas analysis showed that the average value of the oxygenation index (PO₂/FiO₂) was 290.9±83.1, which was less than 300 in 6 cases (50.0%). The main chest CT features were patchy or consolidation in the bilateral or unilateral lungs, and the boundary was not clear but showed a bronchial inflation sign. Also, some of the cases were accompanied by pleural effusion. Once the etiology was obtained, the patients were quickly treated with doxycycline combined with other antibiotics. All 12 patients improved and were discharged from the hospital. However, two severe patients were admitted to the intensive care unit (ICU) and received ventilation and monitoring treatment. There were no deaths.

Conclusions

C. psittaci pneumonia is an atypical community-acquired pneumonia (CAP) caused by C. psittaci infection, with its own laboratory and imaging characteristics. In this study, diagnosis was established based on the application of mNGS owing to the absence of easily available conventional pathogenic evidence. In addition, an aggressive and precise treatment strategy can help achieve a favorable prognosis for patients.

Metagenomic next-generation sequencing for the etiological diagnosis of rabies virus in cerebrospinal fluid

Background

Rabies is a highly fatal disease. Once symptoms develop, death usually occurs within days. Survivors were occasionally reported in the literatures. Ante-mortem diagnosis remains a challenge in most rabies endemic countries. A novel, accurate diagnostic assay is highly desirable.

Methods

We used metagenomic next-generation sequencing (mNGS) to examine the cerebrospinal fluid (CSF) samples of a 49-year-old patient with rabies and validated the results by TaqMan PCR and RT-PCR/Sanger sequencing.

Results

Metagenomic next-generation sequencing identified sequence reads uniquely aligned to the rabies virus (RABV). PCR confirmed the presence of the partial RABV N gene in the CSF. Phylogenetic analysis showed that the RABV grouped as an Asian clade, which is the most broadly distributed clade in China.

Conclusion

Metagenomic next-generation sequencing may be a useful screening tool for the etiological diagnosis of rabies, especially in the absence of timely rabies laboratory testing or in patients with no exposure history.

Metagenomic next-generation sequencing in diagnosing Pneumocystis jirovecii pneumonia: A case report

It remains a huge challenge for clinicians to diagnose Pneumocystis jirovecii pneumonia (PJP) by a conventional method, which leads to delay in diagnosing PJP, accounting for higher mortality in patients with rheumatoid arthritis (RA). A 69-year-old woman, who suffered from RA for years, developed acute respiratory failure. The computed tomography scan showed diffused effusion and ground glass opacity in both lungs, which could not be differentiated from interstitial pneumonia. Metagenomic next-generation sequencing (mNGS) revealed P. jirovecii in both serum and bronchoalveolar lavage fluid with reads per million (RPM) of 17 and 437, while other diagnostic tests did not detect any pathogenic microorganism. The results were verified by quantitative polymerase chain reaction (mtSSU region) against the same samples. The DNA RPM of P. jirovecii declined notably after treatment with trimethoprim/sulfamethoxazole. The patient was discharged without treatment and finally passed away. This case fully highlights the sensitivity of mNGS in early diagnosis of PJP, which is of great significance for prognosis and treatment. Nonetheless, the clinical application of mNGS is worth further standardization and normalization.

Trends and Developments in the Detection of Pathogens in Central Nervous System Infections: A Bibliometric Study

Introduction

Rapid, sensitive, and specific laboratory assays are critical for the diagnosis and management of central nervous system (CNS) infections. The purpose of this study is to explore the intellectual landscape of research investigating methods for the detection of pathogens in patients with CNS infections and to identify the development trends and research frontier in this field.

Methods

A bibliometric study is conducted by analyzing literature retrieved from the Web of Science (WoS) Core Collection Database for the years 2000 to 2021. CiteSpace software is used for bibliometric analysis and network visualization, including co-citation analysis of references, co-occurrence analysis of keywords, and cooperation network analysis of authors, institutions, and countries/regions.

Results

A total of 2,282 publications are eventually screened, with an upward trend in the number of publications per year. The majority of papers are attributed to the disciplines of MICROBIOLOGY, INFECTIOUS DISEASES, IMMUNOLOGY, NEUROSCIENCES & NEUROLOGY, and VIROLOGY. The co-citation analysis of references shows that recent research has focused on the largest cluster “metagenomic next-generation sequencing”; the results of the analysis of the highest-cited publications and the citation burst of publications reveal that there is a strong interest stimulated in metagenomic next-generation sequencing. The co-occurrence analysis of keywords indicates that “infection”, “pathogen”, “diagnosis”, “gene”, “virus”, “polymerase chain reaction”, “cerebrospinal fluid”, “epidemiology”, and “metagenomic next-generation sequencing” are the main research priorities in the field of pathogen detection for CNS infections, and the keyword with the highest strength of burst is “metagenomic next-generation sequencing”. Collaborative network analysis reveals that the USA, the Centers for Disease Control and Prevention of USA, and XIN WANG and JENNIFER DIEN BARD are the most influential country, institution, and researchers, respectively.

Conclusions

Exploring more advanced laboratory assays to improve the diagnostic accuracy of pathogens is essential for CNS infection research. Metagenomic next-generation sequencing is emerging as a novel useful unbiased approach for diagnosing infectious diseases of the CNS.

What Does 16S rRNA Gene-Targeted Next Generation Sequencing Contribute to the Study of Infective Endocarditis in Heart-Valve Tissue?

Infective endocarditis (IE) is a severe and life-threatening disease. Identification of infectious etiology is essential for establishing the appropriate antimicrobial treatment and decreasing mortality. The aim of this study was to explore the potential utility of metataxonomics for improving microbiological diagnosis of IE. Here, next-generation sequencing (NGS) of the V3-V4 region of the 16S rRNA gene was performed in 27 heart valve tissues (18 natives, 5 intravascular devices, and 4 prosthetics) from 27 patients diagnosed with IE (4 of them with negative blood cultures). Metataxonomics matched with conventional diagnostic techniques in 24/27 cases (88.9%). The same bacterial family was assigned to 24 cases; the same genus, to 23 cases; and the same species, to 13 cases. In 22 of them, the etiological agent was represented by percentages > 99% of the reads and in two cases, by ~70%. Staphylococcus aureus was detected in a previously microbiological undiagnosed patient. Thus, microbiological diagnosis with 16S rRNA gene targeted-NGS was possible in one more sample than using traditional techniques. The remaining two patients showed no coincidence between traditional and 16S rRNA gene-targeted NGS microbiological diagnoses. In addition, 16S rRNA gene-targeted NGS allowed us to suggest coinfections that were supported by clinical data in one patient, and minority records also verified mixed infections in three cases. In our series, metataxonomics was valid for the identification of the causative agents, although more studies are needed before implementation of 16S rRNA gene-targeted NGS for the diagnosis of IE.

Bacterial keratitis: identifying the areas of clinical uncertainty

Bacterial keratitis is a common corneal infection that is treated with topical antimicrobials. By the time of presentation there may already be severe visual loss from corneal ulceration and opacity, which may persist despite treatment. There are significant differences in the associated risk factors and the bacterial isolates between high income and low- or middle-income countries, so that general management guidelines may not be appropriate. Although the diagnosis of bacterial keratitis may seem intuitive there are multiple uncertainties about the criteria that are used, which impacts the interpretation of investigations and recruitment to clinical studies. Importantly, the concept that bacterial keratitis can only be confirmed by culture ignores the approximately 50% of cases clinically consistent with bacterial keratitis in which investigations are negative. The aetiology of these culture-negative cases is unknown. Currently, the estimation of bacterial susceptibility to antimicrobials is based on data from systemic administration and achievable serum or tissue concentrations, rather than relevant corneal concentrations and biological activity in the cornea. The provision to the clinician of minimum inhibitory concentrations of the antimicrobials for the isolated bacteria would be an important step forward. An increase in the prevalence of antimicrobial resistance is a concern, but the effect this has on disease outcomes is yet unclear. Virulence factors are not routinely assessed although they may affect the pathogenicity of bacteria within species and affect outcomes. New technologies have been developed to detect and kill bacteria, and their application to bacterial keratitis is discussed. In this review we present the multiple areas of clinical uncertainty that hamper research and the clinical management of bacterial keratitis, and we address some of the assumptions and dogma that have become established in the literature.

The Application of Metagenomic Next-Generation Sequencing in Detection of Pathogen in Bronchoalveolar Lavage Fluid and Sputum Samples of Patients with Pulmonary Infection

Objective

To uncover the application value of metagenomic next-generation sequencing (mNGS) in the detection of pathogen in bronchoalveolar lavage fluid (BALF) and sputum samples.

Methods

Totally, 32 patients with pulmonary infection were included. Pathogens in BALF and sputum samples were tested simultaneously by routine microbial culture and mNGS. Main infected pathogens (bacteria, fungi, and viruses) and their distribution in BALF and sputum samples were analyzed. Moreover, the diagnostic performance of mNGS in paired BALF and sputum samples was assessed.

Results

The pathogen culture results were positive in 9 patients and negative in 13 patients. No statistical differences were recorded on the sensitivity (78.94% vs. 63.15%, p = 0.283) and specificity (62.50% vs. 75.00%, p = 0.375) of mNGS diagnosis in bacteria and fungus in two types of samples. As shown in mNGS detection, 10 patients' two samples were both positive, 13 patients' two samples were both negative, 7 patients were only positive in BALF samples, and 2 patients' sputum samples were positive. Main viruses mNGS detected were EB virus, human adenovirus 5, herpes simplex virus type 1, and human cytomegalovirus. Kappa consensus analysis indicated that mNGS showed significant consistency in detecting pathogens in two samples, no matter bacteria (p < 0.001), fungi (p = 0.026), or viruses (p = 0.008).

Conclusion

mNGS showed no statistical differences in sensitivity and specificity of pathogen detection in BALF and sputum samples. Under certain conditions, sputum samples might be more suitable for pathogen detection because of invasiveness of BALF samples.

Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples

OBJECTIVES

The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2.

METHODS

We performed mNGS on clinical samples and designed a diagnostic classifier that corrects for barcode crosstalk between specimens. Phylogenetic analysis was performed on genome assemblies.

RESULTS

Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-PCR cycle threshold value less than 30. We assembled 10 complete, and one near-complete genomes from 20 specimens that were classified as positive by mNGS. Phylogenetic analysis revealed that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. We found 100% concordance between phylogenetic lineage assignment and Variant of Concern (VOC) PCR results. Our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with the current standard VOC PCR being used in British Columbia.

CONCLUSIONS

This study supports future work examining the broader feasibility of nanopore mNGS as a diagnostic strategy for the detection and characterization of viral pathogens.

Case Report: Metagenomics Next-Generation Sequencing Can Be Performed for the Diagnosis of Disseminated Mucormycosis

Mucormycosis is an infection caused by a group of filamentous molds with in the order Mucorales. In developing countries, most cases of mucormycosis occur in persons with poorly controlled diabetes mellitus or subjects with normal post-traumatic immune function. Mucormycosis exhibits a marked propensity for invading blood vessels. The mortality rate of invasive mucormycosis is very high (>30-50%), and 90% of mortality is related to disseminated diseases. We report a 62-year-old man with underlying diseases, such as diabetes and psoriatic arthritis, with a history of trauma before admission. Chest CT showed multiple cavities. Based on the suspected clinical manifestation of mucormycosis infection, the patient received a microbiological culture of bronchoalveolar lavage fluid, and metagenomics next generation sequencing (mNGS) was performed. The results suggested Klebsiella pneumoniae infection. However, Rhizopus microsporus strains were shown by the mNGS of transpulmonary puncture tissue. Therefore, we report a case in which rare pathogens are identified by mNGS.

Towards Real-Time and Affordable Strain-Level Metagenomics-Based Foodborne Outbreak Investigations Using Oxford Nanopore Sequencing Technologies

The current routine laboratory practices to investigate food samples in case of foodborne outbreaks still rely on attempts to isolate the pathogen in order to characterize it. We present in this study a proof of concept using Shiga toxin-producing Escherichia coli spiked food samples for a strain-level metagenomics foodborne outbreak investigation method using the MinION and Flongle flow cells from Oxford Nanopore Technologies, and we compared this to Illumina short-read-based metagenomics. After 12 h of MinION sequencing, strain-level characterization could be achieved, linking the food containing a pathogen to the related human isolate of the affected patient, by means of a single-nucleotide polymorphism (SNP)-based phylogeny. The inferred strain harbored the same virulence genes as the spiked isolate and could be serotyped. This was achieved by applying a bioinformatics method on the long reads using reference-based classification. The same result could be obtained after 24-h sequencing on the more recent lower output Flongle flow cell, on an extract treated with eukaryotic host DNA removal. Moreover, an alternative approach based on in silico DNA walking allowed to obtain rapid confirmation of the presence of a putative pathogen in the food sample. The DNA fragment harboring characteristic virulence genes could be matched to the E. coli genus after sequencing only 1 h with the MinION, 1 h with the Flongle if using a host DNA removal extraction, or 5 h with the Flongle with a classical DNA extraction. This paves the way towards the use of metagenomics as a rapid, simple, one-step method for foodborne pathogen detection and for fast outbreak investigation that can be implemented in routine laboratories on samples prepared with the current standard practices.

Integrons, a predictive biomarker for antibiotic resistance in acute sepsis: the IRIS study

BACKGROUND

Considering the increase in MDR Gram-negative bacteria (GNB), the choice of empirical antibiotic therapy is challenging. In parallel, use of broad-spectrum antibiotics should be avoided to decrease antibiotic selection pressure. Accordingly, clinicians need rapid diagnostic tools to narrow antibiotic therapy. Class 1-3 integrons, identified by intI1-3 genes, are genetic elements that play a major role in antibiotic resistance in GNB.

OBJECTIVES

The objective of the IRIS study was to evaluate the negative and positive predictive values (NPVs and PPVs, respectively) of intI1-3 as markers of antibiotic resistance.

METHODS

The IRIS study was an observational cross-sectional multicentre study that enrolled adult subjects with suspected urinary tract or intra-abdominal infections. intI1-3 were detected directly from routinely collected biological samples (blood, urine or intra-abdominal fluid) using real-time PCR. A patient was considered 'MDR positive' if at least one GNB, expressing acquired resistance to at least two antibiotic families among β-lactams, aminoglycosides, fluoroquinolones and/or co-trimoxazole, was isolated from at least one biological sample.

RESULTS

Over a 2 year period, 513 subjects were enrolled and 409 had GNB documentation, mostly Enterobacterales. intI1 and/or intI2 were detected in 31.8% of patients and 24.4% of patients were considered 'MDR positive'. The NPV of intI1 and/or intI2 as a marker of acquired antibiotic resistances was estimated at 92.8% (89.1%-95.5%). The NPVs for first-line antibiotics were all above 92%, notably >96% for resistance to third-generation cephalosporins.

CONCLUSIONS

The IRIS study strongly suggests that the absence of intI1 and intI2 in biological samples from patients with GNB-related infections is predictive of the absence of acquired resistances.

Metagenomics of black grains: new highlights in the understanding of eumycetoma

BACKGROUND

Eumycetoma is a chronic subcutaneous granulomatous disease that is endemic in Sudan and other countries. It can be caused by eight different fungal orders. The gold standard diagnostic test is culture, however, culture-independent methods such as imaging, histopathological and molecular techniques can support diagnosis, especially in cases of negative cultures.

METHODS

The amplicon-based internal transcribed spacer 2 metagenomic technique was used to study black grains isolated from 14 tissue biopsies from patients with mycetoma. Furthermore, mycological culture and surgical biopsy histopathological examinations of grains were performed.

RESULTS

Madurella mycetomatis (n=5) and Falciformispora spp. (n=4) organisms were identified by culture and confirmed by metagenomics. Metagenomics recognised, at the species level, Falciformispora as Falciformispora tompkinsii (n=3) and Falciformispora senegalensis (n=1), while in culture-negative cases (n=5), Madurella mycetomatis (n=3), Falciformispora senegalensis (n=1) and Fusarium spp. (n=1) were identified. Interestingly, the metagenomics results showed a 'consortium' of different fungi in each sample, mainly Ascomycota phylum, including various species associated with eumycetoma. The microbial co-occurrence in eumycetoma showed the co-presence of Madurella with Trichoderma, Chaetomium, Malasseziales and Sordariales spp., while Falciformispora co-presented with Inocybe and Alternaria and was in mutual exclusion with Subramaniula, Aspergillus and Trichothecium.

CONCLUSION

Metagenomics provides new insights into the aetiology of eumycetoma in samples with negative culture and into the diversity and complexity of grains mycobiota, calling into question the accuracy of traditional culture for the identification of causative agents.

Microbial diagnosis of endophthalmitis using nanopore amplicon sequencing

OBJECTIVES

We investigated whether nanopore amplicon sequencing of aqueous humor was capable of rapid pathogen identification in infectious endophthalmitis.

METHODS

5 cases of culture-positive bacterial endophthalmitis and 3 cases of fungal endophthalmitis (1 culture-positive and 2 presumed) were included. DNA was extracted from the aqueous humor and vitreous specimen, and PCR of bacterial rDNA (16S) and fungal rDNA (ITS1 and D1/2/3) was performed. Then, nanopore amplicon sequencing was performed for 2 h. The results of amplicon sequencing were compared to those of conventional culture studies.

RESULTS

In all cases, pathogens were identified by amplicon sequencing of aqueous humor specimens. In 3 cases of bacterial endophthalmitis, the identified microbes were confirmed by culture studies of both aqueous humor and vitreous specimens. In 2 cases of bacterial and 1 case of fungal endophthalmitis, the identified pathogens were confirmed only by culture studies of vitreous specimens. In all cases, amplicon sequencing identified pathogen in a shorter turnaround time than culture studies. In 2 cases with negative culture results, amplicon sequencing of aqueous humor identified fungal pathogens.

CONCLUSIONS

Our data demonstrates the potential of amplicon nanopore sequencing using aqueous humor to enable rapid, sensitive and less invasive microbial diagnosis of endophthalmitis.

Targeted metagenomics using next generation sequencing in laboratory diagnosis of culture negative endophthalmitis

To study the feasibility of 16S rRNA metagenomics using next generation sequencing (NGS) along with broad range PCR assay for 762 bp region of 16S rRNA gene with Sanger's sequencing, in microbial diagnosis of culture negative endophthalmitis. Vitreous fluid from 16 culture negative and one culture positive endophthalmitis patients, admitted to a tertiary care hospital were processed for targeted metagenomics. NGS of 7 variable regions of 16S rRNA gene was done using Ion Torrent Personal Genome Machine (PGM). Sequence data were analyzed using Ion Reporter software using QIIME and BLSATN tools and Greengenes and NCBI–Genbank databases. Bacterial genome sequences were detected in 15 culture negative and culture positive vitreous specimens. The sequence reads varied between 25,245–540,916 with read length between 142bp–228bp and coverage depth was 41.0X and 81.2X. Operational taxonomic unit (OTUs) of multiple bacterial genera and species were detected in 13 culture negative vitreous specimens and OTUs of a single bacterial species were detected in 2 culture negative and 1 culture positive specimens; one negative specimen had no bacterial DNA. Maximum numbers of OTUs detected by NGS for a bacterial species from any vitreous specimen was the one which was detected and identified by Sanger's sequencing in broad range PCR. All the bacteria were belonging to clinically relevant species. Broad range PCR with sequencing failed to identify bacteria from 5 of the 16 (31.25%) culture negative vitreous specimens. Metagenomics could detect and identify bacterial pathogens in 15 of the 16 culture negative vitreous specimen's up to species level. With rapidly decreasing cost, metagenomics has a potential to be used widely in endophthalmitis diagnosis, in which culture negativity is usually high.

Clinical Analysis of Metagenomic Next-Generation Sequencing Confirmed Chlamydia psittaci Pneumonia: A Case Series and Literature Review

Introduction

Chlamydia psittaci infection is a zoonotic infectious disease, which mainly inhaled through the lungs when exposed to the secretions of poultry that carry pathogenic bacteria. The traditional respiratory specimens or serological antibody testing is slow, and the false-negative rate is high. Metagenomic next-generation sequencing (mNGS) gives a promising rapid diagnosis tool.

Methods

We retrospectively summarized the clinical characteristics of five C. psittaci pneumonia patients diagnosed by mNGS, conducted a literature review summarizing the clinical characteristics of patients with C. psittaci pneumonia reported since 2010.

Results

Five C. psittaci pneumonia patients confirmed by mNGS aged from 36 to 66 years with three males. About 60% of patients had a history of contact with avian or poultry. All patients had a high fever over 38.5 °C, cough, hypodynamia, hypoxemia, and dyspnea on admission. Two patients had invasive ventilator support and extracorporeal membrane oxygenation support. Inflammatory index levels on admission and follow-up were all higher than normal values. Doxycycline or moxifloxacin and their combination therapy were used in patients. Four patients improved and were discharged, and one patient died due to multiple organ failures and disseminated intravascular coagulation. We summarized 19 articles including 69 C. psittaci pneumonia patients and patients in 11 publications were identified by mNGS, and most patients are treated with tetracycline and quinolone with good outcomes.

Conclusion

mNGS is a promising rapid diagnosis tool, which may increase the detection rate and shorten the diagnosis time of C. psittaci pneumonia. Further case-control studies are needed to confirm.

A proof-of-concept study of an automated solution for clinical metagenomic next-generation sequencing

AIMS

Metagenomic next-generation sequencing (mNGS) has been utilized for diagnosing infectious diseases. It is a culture-free and hypothesis-free nucleic acid test for diagnosing all pathogens with known genomic sequences, including bacteria, fungi, viruses and parasites. While this technique greatly expands the clinical capacity of pathogen detection, it is a second-line choice due to lengthy procedures and microbial contaminations introduced from wet-lab processes. As a result, we aimed to reduce the hands-on time and exogenous contaminations in mNGS.

METHODS AND RESULTS

We developed a device (NGSmaster) that automates the wet-lab workflow, including nucleic acid extraction, PCR-free library preparation and purification. It shortens the sample-to-results time to 16 and 18·5 h for DNA and RNA sequencing respectively. We used it to test cultured bacteria for validation of the workflow and bioinformatic pipeline. We also compared PCR-free with PCR-based library prep and discovered no differences in microbial reads. Moreover we analysed results by automation and manual testing and found that automation can significantly reduce microbial contaminations. Finally, we tested artificial and clinical samples and showed mNGS results were concordant with traditional culture.

CONCLUSION

NGSmaster can fulfil the microbiological diagnostic needs in a variety of sample types.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study opens up an opportunity of performing in-house mNGS to reduce turnaround time and workload, instead of transferring potentially contagious specimen to a third-party laboratory.

Cost-effectiveness analysis of whole-genome sequencing during an outbreak of carbapenem-resistant Acinetobacter baumannii

Background:

Whole-genome sequencing (WGS) shotgun metagenomics (metagenomics) attempts to sequence the entire genetic content straight from the sample. Diagnostic advantages lie in the ability to detect unsuspected, uncultivatable, or very slow-growing organisms.

Objective:

To evaluate the clinical and economic effects of using WGS and metagenomics for outbreak management in a large metropolitan hospital.

Design:

Cost-effectiveness study.

Setting:

Intensive care unit and burn unit of large metropolitan hospital.

Patients:

Simulated intensive care unit and burn unit patients.

Methods:

We built a complex simulation model to estimate pathogen transmission, associated hospital costs, and quality-adjusted life years (QALYs) during a 32-month outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB). Model parameters were determined using microbiology surveillance data, genome sequencing results, hospital admission databases, and local clinical knowledge. The model was calibrated to the actual pathogen spread within the intensive care unit and burn unit (scenario 1) and compared with early use of WGS (scenario 2) and early use of WGS and metagenomics (scenario 3) to determine their respective cost-effectiveness. Sensitivity analyses were performed to address model uncertainty.

Results:

On average compared with scenario 1, scenario 2 resulted in 14 fewer patients with CRAB, 59 additional QALYs, and $75,099 cost savings. Scenario 3, compared with scenario 1, resulted in 18 fewer patients with CRAB, 74 additional QALYs, and $93,822 in hospital cost savings. The likelihoods that scenario 2 and scenario 3 were cost-effective were 57% and 60%, respectively.

Conclusions:

The use of WGS and metagenomics in infection control processes were predicted to produce favorable economic and clinical outcomes.

The Next Generation of Ocular Pathogen Detection

ABSTRACT

Metagenomic next-generation sequencing is a powerful method for pathogen detection that combines advanced genome sequencing technology with cutting-edge bioinformatics to analyze microbial populations. Metagenomic next-generation sequencing has the potential to identify uncommon, unculturable, and even previously unidentified pathogens from a clinical isolate. Of particular interest to ophthalmology, this robust data extraction can occur from very small volume clinical samples. Here we discuss the opportunities and limitations of this technique and their current and future application to ophthalmic diagnostics.

Tuberculosis Diagnosis by Metagenomic Next-generation Sequencing on Bronchoalveolar Lavage Fluid: a cross-sectional analysis

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is an effective diagnostic method for infectious diseases, however, its clinical utility for tuberculosis (TB) diagnosis remains to be demonstrated.

METHODS

A total of 322 bronchoalveolar lavage fluid (BALF) samples were collected from 311 suspected and confirmed pulmonary TB patients and tested by mNGS, acid-fast bacillus (AFB) smear by microscopy, Xpert® MTB/RIF (Xpert), mycobacterium culture and bacterial/fungal culture. Diagnostic performance of mNGS was compared with conventional methods for detection of Mycobacterium tuberculosis complex (MTBC) and other pathogens in BALF. Underlying factors associated with positive detection in pulmonary TB patients were investigated.

RESULTS

mNGS, Xpert and culture presented a high proportion of complete matching for MTBC detection (244/322, 75.8%). In pulmonary TB patients pre-treatment the sensitivity of MTBC detection by mNGS, Xpert, culture and smear was 59.9% (85/142), 69.0% (98/142), 59.9% (85/142) and 24.6% (35/142), respectively, and 79.6% overall; MTBC was detected by mNGS in 33.2% (5/34) Xpert and culture negative samples. Positive MTBC detection by mNGS was affected by Vitamin D, erythrocyte sedimentation rate, TB initial treatment/retreatment, and cavity in chest imaging (χ² = 37.42, P < 0.001), but not by prior anti-TB therapy within 3 months. mNGS was able to detect new potential pathogens in 8.7% (28/322) of samples.

CONCLUSIONS

Combining mNGS with conventional detection methods could increase the detection rate for MTBC. Additionally, mNGS could identify pathogens in a non-targeted approach for better diagnosis of coinfection.

A high-efficiency phenanthrene-degrading Diaphorobacter sp. isolated from PAH-contaminated river sediment

Polycyclic aromatic hydrocarbons (PAHs) are typical persistent organic pollutants that accumulate in the environment, mainly from anthropogenic activities. Microbial degradation is the main pathway of PAHs degradation in the natural environment. Therefore, the widen of the available bank of microbial resources and exploration of the molecular degradation mechanisms of PAHs are crucial to the proper management of PAHs-polluted sites. In this work, a bacterial strain, YM-6, which has a high ability to utilize phenanthrene (PHE) as its sole source of carbon and energy, was isolated from sediment contaminated with PAHs. The strain YM-6 was found to degrade 96.3% of 100 mg/L of PHE in liquid cultures within 52 h. The strain was identified as Diaphorobacter sp. by 16S rDNA sequencing. The optimum growth conditions of the YM-6 strain were studied, and the results indicated that the optimum growth temperature of the strain was 30 °C, and the optimum growth pH was 7. The stain is well-suited for high-temperature stress (40 °C), and it could withstand 400 mg/L of PHE. The strain's PHE metabolism was assayed using GC-MS analyses. The results revealed that the YM-6 strain metabolized PHE via the phthalic acid pathway because the intermediates, such as phthalic acid, diethyl ester and phthalaldehydic acid, methyl ester, were detected. The use of this strain may be an attractive alternative for the bioremediation of polycyclic aromatic hydrocarbons in an aquatic environment.

Mini Review: Clinical Routine Microbiology in the Era of Automation and Digital Health

Clinical microbiology laboratories are the first line to combat and handle infectious diseases and antibiotic resistance, including newly emerging ones. Although most clinical laboratories still rely on conventional methods, a cascade of technological changes, driven by digital imaging and high-throughput sequencing, will revolutionize the management of clinical diagnostics for direct detection of bacteria and swift antimicrobial susceptibility testing. Importantly, such technological advancements occur in the golden age of machine learning where computers are no longer acting passively in data mining, but once trained, can also help physicians in making decisions for diagnostics and optimal treatment administration. The further potential of physically integrating new technologies in an automation chain, combined to machine-learning-based software for data analyses, is seducing and would indeed lead to a faster management in infectious diseases. However, if, from one side, technological advancement would achieve a better performance than conventional methods, on the other side, this evolution challenges clinicians in terms of data interpretation and impacts the entire hospital personnel organization and management. In this mini review, we discuss such technological achievements offering practical examples of their operability but also their limitations and potential issues that their implementation could rise in clinical microbiology laboratories.

Whole blood genome-wide transcriptome profiling and metagenomics next-generation sequencing in young infants with suspected sepsis in a low-and middle-income country: A study protocol

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

Metagenomics Reveals a Core Macrolide Resistome Related to Microbiota in Chronic Respiratory Disease

Rationale: Long-term antibiotic use for managing chronic respiratory disease is increasing; however, the role of the airway resistome and its relationship to host microbiomes remains unknown.Objectives: To evaluate airway resistomes and relate them to host and environmental microbiomes using ultradeep metagenomic shotgun sequencing.Methods: Airway specimens from 85 individuals with and without chronic respiratory disease (severe asthma, chronic obstructive pulmonary disease, and bronchiectasis) were subjected to metagenomic sequencing to an average depth exceeding 20 million reads. Respiratory and device-associated microbiomes were evaluated on the basis of taxonomical classification and functional annotation including the Comprehensive Antibiotic Resistance Database to determine airway resistomes. Co-occurrence networks of gene-microbe association were constructed to determine potential microbial sources of the airway resistome. Paired patient-inhaler metagenomes were compared (n = 31) to assess for the presence of airway-environment overlap in microbiomes and/or resistomes.Measurements and Main Results: Airway metagenomes exhibit taxonomic and metabolic diversity and distinct antimicrobial resistance patterns. A "core" airway resistome dominated by macrolide but with high prevalence of β-lactam, fluoroquinolone, and tetracycline resistance genes exists and is independent of disease status or antibiotic exposure. Streptococcus and Actinomyces are key potential microbial reservoirs of macrolide resistance including the ermX, ermF, and msrD genes. Significant patient-inhaler overlap in airway microbiomes and their resistomes is identified where the latter may be a proxy for airway microbiome assessment in chronic respiratory disease.Conclusions: Metagenomic analysis of the airway reveals a core macrolide resistome harbored by the host microbiome.

Myocarditis and inflammatory cardiomyopathy: current evidence and future directions

Inflammatory cardiomyopathy, characterized by inflammatory cell infiltration into the myocardium and a high risk of deteriorating cardiac function, has a heterogeneous aetiology. Inflammatory cardiomyopathy is predominantly mediated by viral infection, but can also be induced by bacterial, protozoal or fungal infections as well as a wide variety of toxic substances and drugs and systemic immune-mediated diseases. Despite extensive research, inflammatory cardiomyopathy complicated by left ventricular dysfunction, heart failure or arrhythmia is associated with a poor prognosis. At present, the reason why some patients recover without residual myocardial injury whereas others develop dilated cardiomyopathy is unclear. The relative roles of the pathogen, host genomics and environmental factors in disease progression and healing are still under discussion, including which viruses are active inducers and which are only bystanders. As a consequence, treatment strategies are not well established. In this Review, we summarize and evaluate the available evidence on the pathogenesis, diagnosis and treatment of myocarditis and inflammatory cardiomyopathy, with a special focus on virus-induced and virus-associated myocarditis. Furthermore, we identify knowledge gaps, appraise the available experimental models and propose future directions for the field. The current knowledge and open questions regarding the cardiovascular effects associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are also discussed. This Review is the result of scientific cooperation of members of the Heart Failure Association of the ESC, the Heart Failure Society of America and the Japanese Heart Failure Society.

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

The term metagenomics refers to the use of sequencing methods to simultaneously identify genomic material from all organisms present in a sample, with the advantage of greater taxonomic resolution than culture or other methods. Applications include pathogen detection and discovery, species characterisation, antimicrobial resistance detection, virulence profiling, and study of the microbiome and microecological factors affecting health. However, metagenomics involves complex and multistep processes and there are important technical and methodological challenges that require careful consideration to support valid inference. We co-ordinated a multidisciplinary, international expert group to establish reporting guidelines that address specimen processing, nucleic acid extraction, sequencing platforms, bioinformatics considerations, quality assurance, limits of detection, power and sample size, confirmatory testing, causality criteria, cost, and ethical issues. The guidance recognises that metagenomics research requires pragmatism and caution in interpretation, and that this field is rapidly evolving.

Next-generation sequencing in the diagnosis of viral encephalitis: sensitivity and clinical limitations

Identification of pathogens causing viral encephalitis remains challenging, and in over 50% of cases the etiologic factor remains undetermined. Next-generation sequencing (NGS) based metagenomics has been successfully used to detect novel and rare infections, but its value for routine diagnosis of encephalitis remains unclear. The aim of the present study was to determine the sensitivity of shotgun metagenomic sequencing protocols, which include preamplification, and testing it against cerebrospinal fluid (CSF) samples from encephalitis patients. For sensitivity testing HIV and HBV positive sera were serially diluted in CSF from an uninfected patient. NGS repeatedly detected HIV and HBV sequences present at concentrations from 10⁵ to 10² and from 10⁵ to 10 viral copies/reaction, respectively. However, when the same protocols were applied to RT-PCR/PCR positive CSF samples from 6 patients with enteroviral encephalitis (median viral load 47 copies/ml) and 15 patients with HSV, CMV or VZV encephalitis (median viral load 148 copies/ml), only 7 (28.6%) were identified as positive. In conclusions, while NGS has the advantage of being able to identify a wide range of potential pathogens it seems to be less sensitive compared to the standard amplification-based assays in the diagnosis of encephalitis, where low viral loads are common.

Point-Of-Care or Point-Of-Need Diagnostic Tests: Time to Change Outbreak Investigation and Pathogen Detection

In the recent years, the progress of international trade and travel has led to an increased risk of emerging infections. Around 75 percent of the pathogens causing these infections are of animal origin. Point-of-care tests (POCT) and point-of-need tests (PONT) have been established in order to directly provide accurate and rapid diagnostics at field level, the patient bed-side or at the site of outbreaks. These assays can help physicians and decision makers to take the right action without delay. Typically, POCT and PONT rely on genomic identification of pathogens or track their immunological fingerprint. Recently, protocols for metagenomic diagnostics in the field have been developed. In this review, we give an overview of the latest developments in portable diagnostic methods. In addition, four mobile platforms for the implementation of these techniques at point-of-care and point-of-need are described. These approaches can provide reliable diagnostics and surveillance, especially in low resource settings as well as at the level of one health.

Whole blood genome-wide transcriptome profiling and metagenomics next-generation sequencing in young infants with suspected sepsis in low-and middle-income countries: A study protocol

Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes. The protocol includes a detailed clinical assessment with vital sign measurements, strict aseptic blood culture protocol with state-of-the-art microbial analyses and RNA-sequencing and metagenomics evaluations of host responses and pathogens, respectively. We also discuss the directions of a brief analysis plan for RNA sequencing data. This study will provide robust epidemiological data for sepsis in neonates and young infants in a setting where sepsis confers an inordinate burden of disease.

Evaluation of Extraction Methods for Clinical Metagenomic Assay

(1) Background: Clinical metagenomics is a promising approach that helps to identify etiological agents in cases of unknown infections. For the efficient detection of an unknown pathogen, the extraction method must be carefully selected for the maximum recovery of nucleic acid from different microorganisms. The aim of this study was to evaluate different extraction methods that have the ability to isolate nucleic acids from different types of pathogens with good quality and quantity for efficient use in clinical metagenomic identification. (2) Methods: A mock sample spiked with five different pathogens was used for the comparative evaluation of different commercial extraction kits. Extracted samples were subjected to library preparation and run on MiSeq. The selected extraction method based on the outcome of the comparative evaluation was used subsequently for the nucleic acid isolation of all infectious agents in clinical respiratory samples with multiple infections. (3) Results: The protocol using the PowerViral^® Environmental RNA-DNA Isolation Kit with a 5-min bead beating step achieved the best results with a low starting volume. The analysis of the tested clinical specimens showed the ability to successfully identify different types of pathogens. (4) Conclusions: The optimized extraction protocol in this study is recommended for clinical metagenomics application in specimens with multiple infections from different taxa.

Shotgun-Metagenomics on Positive Blood Culture Bottles Inoculated With Prosthetic Joint Tissue: A Proof of Concept Study

Clinical metagenomics is actively moving from research to clinical laboratories. It has the potential to change the microbial diagnosis of infectious diseases, especially when detection and identification of pathogens can be challenging, such as in prosthetic joint infection (PJI). The application of metagenomic sequencing to periprosthetic joint tissue (PJT) specimens is often challenged by low bacterial load in addition to high level of inhibitor and contaminant host DNA, limiting pathogen recovery. Shotgun-metagenomics (SMg) performed directly on positive blood culture bottles (BCBs) inoculated with PJT may be a convenient approach to overcome these obstacles. The aim was to test if it is possible to perform SMg on PJT inoculated into BCBs for pathogen identification in PJI diagnosis. Our study was conducted as a laboratory method development. For this purpose, spiked samples (positive controls), negative control and clinical tissue samples (positive BCBs) were included to get a comprehensive overview. We developed a method for preparation of bacterial DNA directly from PJT inoculated in BCBs. Samples were processed using MolYsis5 kit for removal of human DNA and DNA extracted with BiOstic kit. High DNA quantity/quality was obtained, and no inhibition was observed during the library preparation, allowing further sequencing process. DNA sequencing reads obtained from the BCBs, presented a low proportion of human reads (<1%) improving the sensitivity of bacterial detection. We detected a 19-fold increase in the number of reads mapping to human in a sample untreated with MolYsis5. Taxonomic classification of clinical samples identified a median of 96.08% (IQR, 93.85-97.07%; range 85.7-98.6%) bacterial reads. Shotgun-metagenomics results were consistent with the results from a conventional BCB culture method, validating our approach. Overall, we demonstrated a proof of concept that it is possible to perform SMg directly on BCBs inoculated with PJT, with potential of pathogen identification in PJI diagnosis. We consider this a first step in research efforts needed to face the challenges presented in PJI diagnoses.

Integrating multiple genomic technologies to investigate an outbreak of carbapenemase-producing Enterobacter hormaechei

Carbapenem-resistant Enterobacteriaceae (CRE) represent an urgent threat to human health. Here we report the application of several complementary whole-genome sequencing (WGS) technologies to characterise a hospital outbreak of bla_IMP-4 carbapenemase-producing E. hormaechei. Using Illumina sequencing, we determined that all outbreak strains were sequence type 90 (ST90) and near-identical. Comparison to publicly available data linked all outbreak isolates to a 2013 isolate from the same ward, suggesting an environmental source in the hospital. Using Pacific Biosciences sequencing, we resolved the complete context of the bla_IMP-4 gene on a large IncHI2 plasmid carried by all IMP-4-producing strains across different hospitals. Shotgun metagenomic sequencing of environmental samples also found evidence of ST90 E. hormaechei and the IncHI2 plasmid within the hospital plumbing. Finally, Oxford Nanopore sequencing rapidly resolved the true relationship of subsequent isolates to the initial outbreak. Overall, our strategic application of three WGS technologies provided an in-depth analysis of the outbreak.

Antibiotic-resistant bacteria are an urgent threat to human health. Here, Roberts et al. characterise and monitor an ongoing hospital outbreak of carbapenemase-producing Enterobacter hormaechei by integrating several technologies for whole-genome sequencing and shotgun metagenomics.

Etiology of Central Nervous System Infections in a Rural Area of Nepal Using Molecular Approaches

The etiology of infections of the central nervous system (CNS) in Nepal often remains unrecognized because of underdeveloped laboratory facilities. The aim of this study was to investigate the etiology of CNS infections in a rural area of Nepal using molecular methods. From November 2014 to February 2016, cerebrospinal fluid (CSF) was collected from 176 consecutive patients presenting at United Mission Hospital in Tansen, Nepal, with symptoms of possible CNS infection. After the CSF samples were stored and transported frozen, polymerase chain reaction (PCR) was performed in Sweden, targeting a total of 26 pathogens using the FilmArray^® ME panel (BioFire, bioMerieux, Salt Lake City, UT), the MeningoFinder^® 2SMART (PathoFinder, Maastricht, The Netherlands), and an in-house PCR test for dengue virus (DENV), Japanese encephalitis virus (JEV), and Nipah virus (NiV). The etiology could be determined in 23%. The bacteria detected were Haemophilus influenzae (n = 5), Streptococcus pneumoniae (n = 4), and Neisseria meningitidis (n = 1). The most common virus was enterovirus detected in eight samples, all during the monsoon season. Other viruses detected were cytomegalovirus (n = 6), varicella zoster virus (n = 5), Epstein–Barr virus (n = 3), herpes simplex virus (HSV) type 1 (HSV-1) (n = 3), HSV-2 (n = 3), human herpes virus (HHV) type 6 (HHV-6) (n = 3), and HHV-7 (n = 2). Cryptococcus neoformans/gatti was found in four samples. None of the samples were positive for DENV, JEV, or NiV. Of the patients, 67% had been exposed to antibiotics before lumbar puncture. In conclusion, the etiology could not be found in 77% of the samples, indicating that the commercial PCR panels used are not suitable in this setting. Future studies on the etiology of CNS infections in Nepal could include metagenomic techniques.

Clinical metagenomics for infectious corneal ulcers: Rags to riches?

The emergence of clinical metagenomics as an unbiased, hypothesis-free approach to diagnostic testing is set to fundamentally alter the way infectious diseases are detected. Long envisioned as the solution to the limitations of culture-based conventional microbiology, next generation sequencing methods will soon mature, and our attention will inevitably turn to how they can be applied to areas of medicine which need it most urgently. In ophthalmology, the demand for this technology is particularly pressing for the care of infectious corneal ulcers, where current diagnostic tests may fail to identify a causative organism in over half of cases. However, the optimism found in the budding discourse surrounding clinical metagenomics belies the reality that clinicians and scientists will soon be inundated by oppressive volumes of sequencing data, much of which will be foreign and unfamiliar. Therefore, our success in translating clinical metagenomics is likely to hinge on how we make sense of these data, and understanding its implications for the interpretation and implementation of sequencing into routine clinical care. In this consortium-led review, we provide an outline of these data-related issues and how they may be used to inform technical workflows, with the hope that we may edge closer to realizing the potential of clinical metagenomics for this important unmet need.

mNGS in clinical microbiology laboratories: on the road to maturity

Metagenomic next-generation sequencing (mNGS) is increasingly being applied in clinical laboratories for unbiased culture-independent diagnosis. Whether it can be a next routine pathogen identification tool has become a topic of concern. We review the current implementation of this new technology for infectious disease diagnostics and discuss the feasibility of transforming mNGS into a routine diagnostic test. Since 2008, numerous studies from over 20 countries have revealed the practicality of mNGS in the work-up of undiagnosed infectious diseases. mNGS performs well in identifying rare, novel, difficult-to-detect and coinfected pathogens directly from clinical samples and presents great potential in resistance prediction by sequencing the antibiotic resistance genes, providing new diagnostic evidence that can be used to guide treatment options and improve antibiotic stewardship. Many physicians recognized mNGS as a last resort method to address clinical infection problems. Although several hurdles, such as workflow validation, quality control, method standardisation, and data interpretation, remain before mNGS can be implemented routinely in clinical laboratories, they are temporary and can be overcome by rapidly evolving technologies. With more validated workflows, lower cost and turnaround time, and simplified interpretation criteria, mNGS will be widely accepted in clinical practice. Overall, mNGS is transforming the landscape of clinical microbiology laboratories, and to ensure that it is properly utilised in clinical diagnosis, both physicians and microbiologists should have a thorough understanding of the power and limitations of this method.

Shotgun metagenomics for microbiome and resistome detection in septic patients with urinary tract infection

In sepsis, early and appropriate antibiotic therapy is key but is frequently challenging due to the increasing incidence of multidrug-resistant bacteria. The feasibility of shotgun metagenomics (SM) has been scarcely assessed in urinary tract infections (UTIs). In this study, the feasibility of SM to detect both the microbiome and the resistome in patients with confirmed UTI-related sepsis was evaluated. Urine samples were obtained from 40 adult patients with UTI-related sepsis. Conventional culture was used as a reference. Following total DNA extraction and depletion of human DNA, SM was performed using Ion Proton^TM technology. Bioinformatics analysis was conducted using Geneious^Ⓡ software as well as online tools from the Center for Genomic Epidemiology. For the microbiome, SM was consistently concordant when urine culture was positive with only one bacterium (mainly Escherichia coli). For the resistome, results were in agreement with antimicrobial susceptibility testing with no major discrepancies. SM consistently identified bla_CTX-M genes responsible for resistance to third-generation cephalosporins. Resistance to aminoglycosides and fluoroquinolones was identified in all patients. This pilot study confirms that SM can provide clinically relevant information both on the microbiome and the resistome from urine samples of patients with UTI-related sepsis.

Metagenomics in ophthalmology: Hypothesis or real prospective?

Metagenomic analysis was originally associated with the studies of genetic material from environmental samples. But, with the advent of the Human Microbiome Project, it has now been applied in clinical practices. The ocular surface (OS) is the most exposed part of the eye, colonized by several microbial communities (both, OS and environmental) that contribute to the maintenance of the physiological state. Limited knowledge has been acquired on these microbes due to the limitations of conventional diagnostic methods. Emerging fields of research are focusing on Next Generation Sequencing (NGS) technologies to obtain reliable information on the OS microbiome. Currently only pre-specified pathogens can be detected by conventional culture-based techniques or Polymerase Chain Reaction (PCR), but there are conditions to state whether metagenomics could revolutionize the diagnosis of ocular diseases. The aim of this review is to provide an updated overview of the studies involving NGS technology for OS microbiome.

Apparent performance of metagenomic next-generation sequencing in the diagnosis of cryptococcal meningitis: a descriptive study

INTRODUCTION

In recent years, metagenomic next-generation sequencing (mNGS) has become widely used in medical microbiology to detect pathogen infection.

AIM

We aimed to assess the diagnostic performance of mNGS of cerebrospinal fluid (CSF) for prediction of cryptococcal meningitis (CM).

METHODOLOGY

A comparative evaluation of mNGS (performed on CSF samples) and conventional methods, including India ink staining, culture for fungi and cryptococcal-antigen (CrAg) detection by enzyme immunoassay, was performed on 12 consecutive non-HIV-infected patients with chronic or subacute CM.

RESULTS

India ink staining and culture of the CSF were positive for Cryptococcus in 83.33 % (10/12) of the samples; 100 % (11/11) were positive via CrAg EIA. The mNGS results of the CSF identified DNA sequences corresponding to Cryptococcus in 75 % of samples (9/12). However, the DNA of both C. neoformans s.l. and C. gattii s.l. was detected concurrently in 33.33 % (4/12).

CONCLUSION

mNGS is helpful for identifying Cryptococcus species. The application of mNGS, together with India ink staining, culture methods, and CrAg, may significantly improve the diagnostic precision in CM, thereby informing choice of appropriate antifungal treatment courses.

Streaming histogram sketching for rapid microbiome analytics

BACKGROUND

The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research, allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome research and the looming era of clinical metagenomics, means there is an urgent need to develop analytics that can process huge amounts of data in a short amount of time. To address this need, we propose a new method for tyrhe compact representation of microbiome sequencing data using similarity-preserving sketches of streaming k-mer spectra. These sketches allow for dissimilarity estimation, rapid microbiome catalogue searching and classification of microbiome samples in near real time.

RESULTS

We apply streaming histogram sketching to microbiome samples as a form of dimensionality reduction, creating a compressed 'histosketch' that can efficiently represent microbiome k-mer spectra. Using public microbiome datasets, we show that histosketches can be clustered by sample type using the pairwise Jaccard similarity estimation, consequently allowing for rapid microbiome similarity searches via a locality sensitive hashing indexing scheme. Furthermore, we use a 'real life' example to show that histosketches can train machine learning classifiers to accurately label microbiome samples. Specifically, using a collection of 108 novel microbiome samples from a cohort of premature neonates, we trained and tested a random forest classifier that could accurately predict whether the neonate had received antibiotic treatment (97% accuracy, 96% precision) and could subsequently be used to classify microbiome data streams in less than 3 s.

CONCLUSIONS

Our method offers a new approach to rapidly process microbiome data streams, allowing samples to be rapidly clustered, indexed and classified. We also provide our implementation, Histosketching Using Little K-mers (HULK), which can histosketch a typical 2 GB microbiome in 50 s on a standard laptop using four cores, with the sketch occupying 3000 bytes of disk space. ( https://github.com/will-rowe/hulk ).

Application of Next-Generation Sequencing for Characterization of Surveillance and Clinical Trial Isolates: Analysis of the Distribution of β-lactamase Resistance Genes and Lineage Background in the United States

Background

Sequencing technologies and techniques have seen remarkable transformation and innovation that have significantly affected sequencing capability. Data analyses have replaced sequencing as the main challenge. This paper provides an overview on applying next-generation sequencing (NGS) and analysis and discusses the benefits and challenges. In addition, this document shows results from using NGS and bioinformatics tools to screen for β-lactamase genes and assess the epidemiological structure of Escherichia coli– and Klebsiella pneumoniae–causing bloodstream (BSIs) and urinary tract (UTIs) infections in patients hospitalized in the United States during the SENTRY Antimicrobial Surveillance Program for 2016.

Methods

A total of 3525 isolates (2751 E. coli and 774 K. pneumoniae) causing BSIs (n = 892) and UTIs (n = 2633) in hospitalized patients in the United States were included. Isolates were tested for susceptibility by broth microdilution, and those that met a minimum inhibitory concentration (MIC)–based screening criteria had their genomes sequenced and analyzed.

Results

A total of 11.6% and 16.1% of E. coli–causing UTIs and BSIs, respectively, met the MIC-based criteria, whereas 11.0% and 13.7% of K. pneumoniae isolates causing UTIs and BSIs, respectively, met the criteria. Among E. coli, bla_CTX-M variants (87.6% overall) prevailed (60.5% of CTX-M group 1 and 26.9% of group 9). A total of 60.3% of K. pneumoniae isolates carried bla_CTX-M variants (52.7% and 7.6% of groups 1 and 9, respectively). Two E. coli (0.6%) and 13 K. pneumoniae (12.9%) isolates harbored bla_KPC. Among KPC-producing K. pneumoniae (2 from BSIs and 11 from UTIs), 84.6% (11/13) were ST258 (CC258). Seventeen and 38 unique clonal complexes (CCs) were noted in E. coli that caused BSIs and UTIs, respectively, and CC131 (or ST131) was the most common CC among BSI (53.6%) and UTI (58.2%) isolates. Twenty-three and 26 CCs were noted among K. pneumoniae–causing BSIs and UTIs, respectively. CC258 (28.3%) prevailed in UTI pathogens, whereas CC307 (15.0%) was the most common CC among BSI isolates.

Conclusions

This study provides a benchmark for the distribution of β-lactamase genes and the population structure information for the most common Enterobacteriaceae species responsible for BSIs and UTIs in US medical centers during the 2016 SENTRY Program.

Do you cov me? Effect of coverage reduction on metagenome shotgun sequencing studies

Shotgun metagenomics sequencing is a powerful tool for the characterization of complex biological matrices, enabling analysis of prokaryotic and eukaryotic organisms and viruses in a single experiment, with the possibility of reconstructing de novo the whole metagenome or a set of genes of interest. One of the main factors limiting the use of shotgun metagenomics on wide scale projects is the high cost associated with the approach. We set out to determine if it is possible to use shallow shotgun metagenomics to characterize complex biological matrices while reducing costs. We used a staggered mock community to estimate the optimal threshold for species detection. We measured the variation of several summary statistics simulating a decrease in sequencing depth by randomly subsampling a number of reads. The main statistics that were compared are diversity estimates, species abundance, and ability of reconstructing de novo the metagenome in terms of length and completeness. Our results show that diversity indices of complex prokaryotic, eukaryotic and viral communities can be accurately estimated with 500,000 reads or less, although particularly complex samples may require 1,000,000 reads. On the contrary, any task involving the reconstruction of the metagenome performed poorly, even with the largest simulated subsample (1,000,000 reads). The length of the reconstructed assembly was smaller than the length obtained with the full dataset, and the proportion of conserved genes that were identified in the meta-genome was drastically reduced compared to the full sample. Shallow shotgun metagenomics can be a useful tool to describe the structure of complex matrices, but it is not adequate to reconstruct—even partially—the metagenome.