Conducting metagenomic studies in microbiology and clinical research

Metagenomics for Pathogen Detection During a Mass Mortality Event in Songbirds

Mass mortality events in wildlife can be indications of an emerging infectious disease. During the spring and summer of 2021, hundreds of dead passerines were reported across the eastern US. Birds exhibited a range of clinical signs including swollen conjunctiva, ocular discharge, ataxia, and nystagmus. As part of the diagnostic investigation, high-throughput metagenomic next-generation sequencing was performed across three molecular laboratories on samples from affected birds. Many potentially pathogenic microbes were detected, with bacteria forming the largest proportion; however, no singular agent was consistently identified, with many of the detected microbes also found in unaffected (control) birds and thus considered to be subclinical infections. Congruent results across laboratories have helped drive further investigation into alternative causes, including environmental contaminants and nutritional deficiencies. This work highlights the utility of metagenomic approaches in investigations of emerging diseases and provides a framework for future wildlife mortality events.

Microbiota-Based Live Biotherapeutic Products for Clostridioides Difficile Infection- The Devil is in the Details

Clostridioides difficile infection (CDI) remains a significant contributor to healthcare costs and morbidity due to high rates of recurrence. Currently, available antibiotic treatment strategies further disrupt the fecal microbiome and do not address the alterations in commensal flora (dysbiosis) that set the stage for CDI. Advances in microbiome-based research have resulted in the development of new agents, classified as live biotherapeutic products (LBPs), for preventing recurrent CDI (rCDI) by restoring eubiosis. Prior to the LBPs, fecal microbiota transplantation (FMT) was available for this purpose; however, lack of large-scale availability and safety concerns have remained barriers to its widespread use. The LBPs are an exciting development, but questions remain. Some are derived directly from human stool while other developmental products contain a defined microbial consortium manufactured ex vivo, and they may be composed of either living bacteria or their spores, making it difficult to compare members of this heterogenous drug class to one another. None have been studied head-to head or against FMT in preventing rCDI. As a class, they have considerable variability in their biologic composition, biopharmaceutic science, route of administration, stages of development, and clinical trial data. This review will start by explaining the role of dysbiosis in CDI, then give the details of the biopharmaceutical components for the LBPs which are approved or in development including how they differ from FMT and from one another. We then discuss the clinical trials of the LBPs currently approved for rCDI and end with the future clinical directions of LBPs beyond C. difficile.

Microbiome Alteration in Lung Tissues of Tuberculosis Patients Revealed by Metagenomic Next-Generation Sequencing and Immune-Related Transcriptional Profile Identified by Transcriptome Sequencing

This study explored alterations in the respiratory microbiome and transcriptome after Mycobacterium tuberculosis infection in tuberculosis (TB) patients. Metagenomic next-generation sequencing (mNGS) was adopted to reveal the microbiome in lung tissues from 110 TB and 25 nontuberculous (NonTB) patients. Transcriptome sequencing was performed in TB tissues (n = 3), tissues adjacent to TB (ParaTB, n = 3), and NonTB tissues (n = 3) to analyze differentially expressed genes (DEGs) and functional pathways. The microbial β diversity (p = 0.01325) in TB patients differed from that in the NonTB group, with 17 microbial species distinctively distributed. Eighty-three co-up-regulated DEGs were identified in the TB versus NonTB and the TB versus ParaTB comparison groups, and six were associated with immune response to Mtb. These DEGs were significantly enriched in the signaling pathways such as immune response, NF-κB, and B cell receptor. Data in the lung tissue microbiome and transcriptome in TB patients offer a sufficient understanding of the pathogenesis of TB.

Etiologic characteristics revealed by mNGS-mediated ultra-early and early microbiological identification in airway secretions from lung transplant recipients

Background

Post-operative etiological studies are critical for infection prevention in lung transplant recipients within the first year. In this study, mNGS combined with microbial culture was applied to reveal the etiological characteristics within one week (ultra-early) and one month (early) in lung transplant recipients, and the epidemiology of infection occurred within one month.

Methods

In 38 lung transplant recipients, deep airway secretions were collected through bronchofiberscope within two hours after the operation and were subjected to microbial identification by mNGS and microbial culture. The etiologic characteristics of lung transplant recipients were explored. Within one month, the infection status of recipients was monitored. The microbial species detected by mNGS were compared with the etiological agents causing infection within one month.

Results

The detection rate of mNGS in the 38 airway secretions specimens was significantly higher than that of the microbial culture (P<0.0001). MNGS identified 143 kinds of pathogenic microorganisms; bacterial pathogens account for more than half (72.73%), with gram-positive and -negative bacteria occupying large proportions. Fungi such as Candida are also frequently detected. 5 (50%) microbial species identified by microbial culture had multiple drug resistance (MDR). Within one month, 26 (68.42%) recipients got infected (with a median time of 9 days), among which 10 (38.46%) cases were infected within one week. In the infected recipients, causative agents were detected in advance by mNGS in 9 (34.62%) cases, and most of them (6, 66.67%) were infected within one week (ultra-early). In the infection that occurred after one week, the consistency between mNGS results and the etiological agents was decreased.

Conclusion

Based on the mNGS-reported pathogens in airway secretions samples collected within two hours, the initial empirical anti-infection regimes covering the bacteria and fungi are reasonable. The existence of bacteria with MDR forecasts the high risk of infection within 48 hours after transplant, reminding us of the necessity to adjust the antimicrobial strategy. The predictive role of mNGS performed within two hours in etiological agents is time-limited, suggesting continuous pathogenic identification is needed after lung transplant.

Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

The fecal and oropharyngeal eukaryotic viromes of healthy infants during the first year of life are personal

Using a metagenomic sequencing approach, we described and compared the diversity and dynamics of the oropharyngeal and fecal eukaryotic virome of nine asymptomatic children in a semi-rural community setting located in the State of Morelos, Mexico. Ninety oropharyngeal swabs and 97 fecal samples were collected starting 2 weeks after birth and monthly thereafter until 12 months of age. In both niches, more than 95% of the total sequence reads were represented by viruses that replicate either in humans or in plants. Regarding human viruses, three families were most abundant and frequent in the oropharynx: Herpesviridae, Picornaviridae, and Reoviridae; in fecal samples, four virus families predominated: Caliciviridae, Picornaviridae, Reoviridae, and Anelloviridae. Both niches showed a high abundance of plant viruses of the family Virgaviridae. Differences in the frequency and abundance of sequence reads and diversity of virus species were observed in both niches and throughout the year of study, with some viruses already present in the first months of life. Our results suggest that the children's virome is dynamic and likely shaped by the environment, feeding, and age. Moreover, composition analysis suggests that the virome composition is mostly individual. Whether this constant exposition to different viruses has a long-term impact on children's health or development remains to be studied.

Clinical application of metagenomic next-generation sequencing technology in the diagnosis and treatment of pulmonary infection pathogens: A prospective single-center study of 138 patients

Introduction

Rapid and accurate pathogen identification is essential for the treatment of pneumonia. Metagenomic next‐generation sequencing (mNGS) is a newly developed technology to obtain microbial nucleic acid sequence information quickly, efficiently, and without bias.

Methods

We performed shotgun metagenomic next‐generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) for pathogen identification in pneumonia in a prospective study with 138 patients from a single center. We compared the results of mNGS with standard methods including culture, staining, and targeted PCR and evaluated the clinical applicability of mNGS.

Results

Most of the patients (128/138, 92.75%) were cured or improved. One patient (1/138, 0.72%) died because of acute gastrointestinal bleeding, and 9 patients (9/138, 6.52%) showed no improvement. mNGS identified more bacteria (53 versus 27), fewer fungi (8 versus 31), and more viruses (16 versus 1) than standard methods. In total, treatment in 34 out of 138 cases (24.64%) was adjusted and optimized because of mNGS results. Positive mNGS results contributed to a definitive diagnosis in 23 cases (16.67%), which helped guide treatment decision by either adjusting the antibiotics without de‐escalation or continuing the empirical treatment. mNGS also confirmed no active infection in 11 cases (7.97%) allowed for antibiotic de‐escalation.

Conclusion

This prospective clinical study evaluated the clinical utility of mNGS for the diagnosis of pneumonia and showed that mNGS of BALF provides valuable information for effective treatment.

Metagenomic Assessment of the Pathogenic Risk of Microorganisms in Sputum of Postoperative Patients With Pulmonary Infection

Respiratory infections are complicated biological processes associated with an unbalanced microbial community and a wide range of pathogens. To date, robust approaches are still required for distinguishing the pathogenic microorganisms from the colonizing ones in the clinical specimens with complex infection. In this study, we retrospectively analyzed the data of conventional culture testing and metagenomic next-generation sequencing (mNGS) of the sputum samples collected from 50 pulmonary infected patients after cardiac surgery from December 2020 and June 2021 in Ruijin Hospital. Taxonomic classification of the sputum metagenomes showed that the numbers of species belonging to bacteria, fungi, and viruses were 682, 58, and 21, respectively. The full spectrum of microorganisms present in the sputum microbiome covered all the species identified by culture, including 12 bacterial species and two fungal species. Based on species-level microbiome profiling, a reference catalog of microbial abundance detection limits was constructed to assess the pathogenic risks of individual microorganisms in the specimens. The proposed screening procedure detected 64 bacterial pathogens, 10 fungal pathogens, and three viruses. In particular, certain opportunistic pathogenic strains can be distinguished from the colonizing ones in the individual specimens. Strain-level identification and phylogenetic analysis were further performed to decipher molecular epidemiological characteristics of four opportunistic etiologic agents, including Klebsiella pneumoniae, Corynebacterium striatum, Staphylococcus aureus, and Candida albicans. Our findings provide a novel metagenomic insight into precision diagnosis for clinically relevant microbes, especially for opportunistic pathogens in the clinical setting.

Profiling temporal dynamics of acetogenic communities in anaerobic digesters using next-generation sequencing and T-RFLP

Acetogens play a key role in anaerobic degradation of organic material and in maintaining biogas process efficiency. Profiling this community and its temporal changes can help evaluate process stability and function, especially under disturbance/stress conditions, and avoid complete process failure. The formyltetrahydrofolate synthetase (FTHFS) gene can be used as a marker for acetogenic community profiling in diverse environments. In this study, we developed a new high-throughput FTHFS gene sequencing method for acetogenic community profiling and compared it with conventional terminal restriction fragment length polymorphism of the FTHFS gene, 16S rRNA gene-based profiling of the whole bacterial community, and indirect analysis via 16S rRNA profiling of the FTHFS gene-harbouring community. Analyses and method comparisons were made using samples from two laboratory-scale biogas processes, one operated under stable control and one exposed to controlled overloading disturbance. Comparative analysis revealed satisfactory detection of the bacterial community and its changes for all methods, but with some differences in resolution and taxonomic identification. FTHFS gene sequencing was found to be the most suitable and reliable method to study acetogenic communities. These results pave the way for community profiling in various biogas processes and in other environments where the dynamics of acetogenic bacteria have not been well studied.

Human OMICs and Computational Biology Research in Africa: Current Challenges and Prospects

Following the publication of the first human genome, OMICs research, including genomics, transcriptomics, proteomics, and metagenomics, has been on the rise. OMICs studies revealed the complex genetic diversity among human populations and challenged our understandings of genotype-phenotype correlations. Africa, being the cradle of the first modern humans, is distinguished by a large genetic diversity within its populations and rich ethnolinguistic history. However, the available human OMICs tools and databases are not representative of this diversity, therefore creating significant gaps in biomedical research. African scientists, students, and publics are among the key contributors to OMICs systems science. This expert review examines the pressing issues in human OMICs research, education, and development in Africa, as seen through a lens of computational biology, public health relevant technology innovation, critically-informed science governance, and how best to harness OMICs data to benefit health and societies in Africa and beyond. We underscore the disparities between North and Sub-Saharan Africa at different levels. A harmonized African ethnolinguistic classification would help address annotation challenges associated with population diversity. Finally, building on the existing strategic research initiatives, such as the H3Africa and H3ABioNet Consortia, we highly recommend addressing large-scale multidisciplinary research challenges, strengthening research collaborations and knowledge transfer, and enhancing the ability of African researchers to influence and shape national and international research, policy, and funding agendas. This article and analysis contribute to a deeper understanding of past and current challenges in the African OMICs innovation ecosystem, while also offering foresight on future innovation trajectories.

Current challenges and best-practice protocols for microbiome analysis

Analyzing the microbiome of diverse species and environments using next-generation sequencing techniques has significantly enhanced our understanding on metabolic, physiological and ecological roles of environmental microorganisms. However, the analysis of the microbiome is affected by experimental conditions (e.g. sequencing errors and genomic repeats) and computationally intensive and cumbersome downstream analysis (e.g. quality control, assembly, binning and statistical analyses). Moreover, the introduction of new sequencing technologies and protocols led to a flood of new methodologies, which also have an immediate effect on the results of the analyses. The aim of this work is to review the most important workflows for 16S rRNA sequencing and shotgun and long-read metagenomics, as well as to provide best-practice protocols on experimental design, sample processing, sequencing, assembly, binning, annotation and visualization. To simplify and standardize the computational analysis, we provide a set of best-practice workflows for 16S rRNA and metagenomic sequencing data (available at https://github.com/grimmlab/MicrobiomeBestPracticeReview).

Bacterial Metabolites of Human Gut Microbiota Correlating with Depression

Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders.

Harnessing the strategy of metagenomics for exploring the intestinal microecology of sable (Martes zibellina), the national first-level protected animal

Sable (Martes zibellina), a member of family Mustelidae, order Carnivora, is primarily distributed in the cold northern zone of Eurasia. The purpose of this study was to explore the intestinal flora of the sable by metagenomic library-based techniques. Libraries were sequenced on an Illumina HiSeq 4000 instrument. The effective sequencing data of each sample was above 6000 M, and the ratio of clean reads to raw reads was over 98%. The total ORF length was approximately 603,031, equivalent to 347.36 Mbp. We investigated gene functions with the KEGG database and identified 7140 KEGG ortholog (KO) groups comprising 129,788 genes across all of the samples. We selected a subset of genes with the highest abundances to construct cluster heat maps. From the results of the KEGG metabolic pathway annotations, we acquired information on gene functions, as represented by the categories of metabolism, environmental information processing, genetic information processing, cellular processes and organismal systems. We then investigated gene function with the CAZy database and identified functional carbohydrate hydrolases corresponding to genes in the intestinal microorganisms of sable. This finding is consistent with the fact that the sable is adapted to cold environments and requires a large amount of energy to maintain its metabolic activity. We also investigated gene functions with the eggNOG database; the main functions of genes included gene duplication, recombination and repair, transport and metabolism of amino acids, and transport and metabolism of carbohydrates. In this study, we attempted to identify the complex structure of the microbial population of sable based on metagenomic sequencing methods, which use whole metagenomic data, and to map the obtained sequences to known genes or pathways in existing databases, such as CAZy, KEGG, and eggNOG. We then explored the genetic composition and functional diversity of the microbial community based on the mapped functional categories.

Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Background

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

Methods

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

Results

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.

Issues and current standards of controls in microbiome research

Good scientific practice is important in all areas of science. In recent years this has gained more and more attention, especially considering the 'scientific reproducibility crisis'. While most researchers are aware of the issues with good scientific practice, not all of these issues are necessarily clear, and the details can be very complicated. For many years it has been accepted to perform and publish sequencing based microbiome studies without including proper controls. Although in recent years more scientists realize the necessity of implementing controls, this poses a problem due to the complexity of the field. Another concern is the inability to properly interpret the information gained from controls in microbiome studies. Here, we will discuss these issues and provide a comprehensive overview of problematic points regarding controls in microbiome research, and of the current standards in this area.

Advances in Clinical Sample Preparation for Identification and Characterization of Bacterial Pathogens Using Metagenomics

Whole genome sequencing (WGS) plays an increasing role in communicable disease control through high-resolution outbreak tracing, laboratory surveillance and diagnostics. However, WGS has traditionally relied on microbial culture in order to obtain pathogen specific DNA for sequencing. This has severely limited the application of whole genome sequencing on pathogens with fastidious culturing requirements. In addition, the widespread adoption of culture-independent diagnostic tests has reduced availability of cultured isolates for confirmatory testing and surveillance. These recent developments have created demand for the implementation of techniques enabling direct sequencing of microbial genomes in clinical samples without having to culture an isolate. However, sequencing of specific organisms from clinical samples can be affected by high levels of contaminating DNA from the host and other commensal microorganisms. Several methods have been introduced for selective lysis of host cells and/or separate specific organisms from a clinical sample. This review examines the different approaches for sample preparation that have been used in diagnostic and public health laboratories for metagenomic sequencing.