Specific ribosomal DNA sequences from diverse environmental settings correlate with experimental contaminants

Impact of root canal preparation using two single-file systems on the intra-radicular microbiome of teeth with primary apical periodontitis

OBJECTIVES

This study aimed to describe the effects of two single-file systems on the diversity of the endodontic microbiome of teeth with primary asymptomatic apical periodontitis.

MATERIALS AND METHODS

The root canals from single-rooted teeth with apical periodontitis were prepared using either the Reciproc Blue (RB) or the XP-endo Shaper (XPS) instrument system. The latter was followed by a supplementary step with the XP-endo Finisher (XPF) instrument. For irrigation, 5.25% sodium hypochlorite was used. Root canal samples were taken at the baseline (S1), after preparation (S2), and after the supplementary step (S3). DNA was extracted and subjected to high-throughput sequencing using the MiSeq Illumina platform.

RESULTS

Samples from 10 teeth from the RB and 7 from the XPS group were subjected to DNA sequencing. Initial samples differed significantly from post-preparation samples in bacterial diversity, with no significant difference when comparing the two instrument systems. The most dominant phyla in S2 were Bacteroidetes, Proteobacteria, Firmicutes, Fusobacteria, and Actinobacteria. The same phyla were found to dominate baseline samples and samples taken after using XPF, but with differences in the ranking of the most dominant ones. At the genus level, the most dominant genera identified after RB instrumentation were Bacteroidaceae [G-1], Fusobacterium, and Staphylococcus, while the most dominant genera after XPS instrumentation were Fusobacterium and Porphyromonas. These genera were also dominant in the initial samples.

CONCLUSIONS

Both treatment protocols had measurable effects on the root canal microbial diversity, with no significant differences between them. Most of the dominant taxa involved in the primary infection and probably in the aetiology of apical periodontitis were eliminated or substantially reduced.

CLINICAL RELEVANCE

The most dominant taxa that persisted after instrumentation were Fusobacterium, Porphyromonas, Staphylococcus, and Bacteroidaceae [G-1].

Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data

BACKGROUND

Microbiome analysis is becoming a standard component in many scientific studies, but also requires extensive quality control of the 16S rRNA gene sequencing data prior to analysis. In particular, when investigating low-biomass microbial environments such as human skin, contaminants distort the true microbiome sample composition and need to be removed bioinformatically. We introduce MicrobIEM, a novel tool to bioinformatically remove contaminants using negative controls.

RESULTS

We benchmarked MicrobIEM against five established decontamination approaches in four 16S rRNA amplicon sequencing datasets: three serially diluted mock communities (108-103 cells, 0.4-80% contamination) with even or staggered taxon compositions and a skin microbiome dataset. Results depended strongly on user-selected algorithm parameters. Overall, sample-based algorithms separated mock and contaminant sequences best in the even mock, whereas control-based algorithms performed better in the two staggered mocks, particularly in low-biomass samples (≤ 106 cells). We show that a correct decontamination benchmarking requires realistic staggered mock communities and unbiased evaluation measures such as Youden's index. In the skin dataset, the Decontam prevalence filter and MicrobIEM's ratio filter effectively reduced common contaminants while keeping skin-associated genera.

CONCLUSIONS

MicrobIEM's ratio filter for decontamination performs better or as good as established bioinformatic decontamination tools. In contrast to established tools, MicrobIEM additionally provides interactive plots and supports selecting appropriate filtering parameters via a user-friendly graphical user interface. Therefore, MicrobIEM is the first quality control tool for microbiome experts without coding experience.

Gallbladder microbiota in healthy dogs and dogs with mucocele formation

To date studies have not investigated the culture-independent microbiome of bile from dogs, a species where aseptic collection of bile under ultrasound guidance is somewhat routine. Despite frequent collection of bile for culture-based diagnosis of bacterial cholecystitis, it is unknown whether bile from healthy dogs harbors uncultivable bacteria or a core microbiota. The answer to this question is critical to understanding the pathogenesis of biliary infection and as a baseline to exploration of other biliary diseases in dogs where uncultivable bacteria could play a pathogenic role. A pressing example of such a disease would be gallbladder mucocele formation in dogs. This prevalent and deadly condition is characterized by excessive secretion of abnormal mucus by the gallbladder epithelium that can eventually lead to rupture of the gallbladder or obstruction of bile flow. The cause of mucocele formation is unknown as is whether uncultivable, and therefore unrecognized, bacteria play any systematic role in pathogenesis. In this study we applied next-generation 16S rRNA gene sequencing to identify the culture-negative bacterial community of gallbladder bile from healthy dogs and gallbladder mucus from dogs with mucocele formation. Integral to our study was the use of 2 separate DNA isolations on each sample using different extraction methods and sequencing of negative control samples enabling recognition and curation of contaminating sequences. Microbiota findings were validated by simultaneous culture-based identification, cytological examination of bile, and fluorescence in-situ hybridization (FISH) performed on gallbladder mucosa. Using culture-dependent, cytological, FISH, and 16S rRNA sequencing approaches, results of our study do not support existence of a core microbiome in the bile of healthy dogs or gallbladder mucus from dogs with mucocele formation. Our findings further document how contaminating sequences can significantly contribute to the results of sequencing analysis when performed on samples with low bacterial biomass.

[Transcriptome analysis of tissue microbiota diversity in tumor and non-tumor lymph nodes]

BACKGROUND

Metagenomic studies in recent years have demonstrated that all tissues of the human body studied by genomic and transcriptomic sequencing methods, both in pathological processes and in normality, contain fragments of DNA and RNA from a variety of microorganisms. The composition of tissue microbiota and its relationship with development of pathological changes are still poorly understood, despite increasing number of studies in this area every year. In this study, gene expression of the lymph node microbiome in reactive follicular hyperplasia and follicular lymphoma was investigated.

OBJECTIVE

To study expression of lymph node microbiome genes in reactive follicular hyperplasia and follicular lymphoma.

MATERIAL AND METHODS

The work included 38 biopsy samples of lymph nodes with follicular lymphoma of different cytological subtypes and 10 biopsy samples of lymph nodes with reactive follicular hyperplasia. Verification of diagnosis was carried out using standard histological, histochemical and immunohistochemical methods. Using sequencing method, the transcriptome was examined. Statistical analysis and data visualization were performed using the R programming language (version 4.2.1).

RESULTS

Tumor lymph nodes are characterized by large Simpson and Shannon alpha diversity values (p-value = 0.026465 and p-value = 0.007122, respectively). Two clusters were discovered, characterized by different levels of relative abundance of microorganisms.

CONCLUSION

It has been proven that diversity of microorganisms present in tumor tissue and their number are statistically significantly higher than corresponding indicators in the lymph nodes with follicular hyperplasia.

Contamination detection and microbiome exploration with GRIMER

BACKGROUND

Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.

RESULTS

We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.

CONCLUSION

GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.

Plasma cfDNA predictors of established bacteraemic infection

Introduction. Increased plasma cell-free DNA (cfDNA) has been reported for various diseases in which cell death and tissue/organ damage contribute to pathogenesis, including sepsis.

Gap Statement. While several studies report a rise in plasma cfDNA in bacteraemia and sepsis, the main source of cfDNA has not been identified.

Aim. In this study, we wanted to determine which of nuclear, mitochondrial or bacterial cfDNA is the major contributor to raised plasma cfDNA in hospital subjects with bloodstream infections and could therefore serve as a predictor of bacteraemic disease severity.

Methodology. The total plasma concentration of double-stranded cfDNA was determined using a fluorometric assay. The presence of bacterial DNA was identified by PCR and DNA sequencing. The copy numbers of human genes, nuclear β globin and mitochondrial MTATP8, were determined by droplet digital PCR. The presence, size and concentration of apoptotic DNA from human cells were established using lab-on-a-chip technology.

Results. We observed a significant difference in total plasma cfDNA from a median of 75 ng ml⁻¹ in hospitalised subjects without bacteraemia to a median of 370 ng ml⁻¹ (P=0.0003) in bacteraemic subjects. The copy numbers of nuclear DNA in bacteraemic also differed between a median of 1.6 copies µl⁻¹ and 7.3 copies µl⁻¹ (P=0.0004), respectively. In contrast, increased mitochondrial cfDNA was not specific for bacteraemic subjects, as shown by median values of 58 copies µl⁻¹ in bacteraemic subjects, 55 copies µl⁻¹ in other hospitalised subjects and 5.4 copies µl⁻¹ in healthy controls. Apoptotic nucleosomal cfDNA was detected only in a subpopulation of bacteraemic subjects with documented comorbidities, consistent with elevated plasma C-reactive protein (CRP) levels in these subjects. No bacterial cfDNA was reliably detected by PCR in plasma of bacteraemic subjects over the course of infection with several bacterial pathogens.

Conclusions. Our data revealed distinctive plasma cfDNA signatures in different groups of hospital subjects. The total cfDNA was significantly increased in hospital subjects with laboratory-confirmed bloodstream infections comprising nuclear and apoptotic, but not mitochondrial or bacterial cfDNAs. The apoptotic cfDNA, potentially derived from blood cells, predicted established bacteraemia. These findings deserve further investigation in different hospital settings, where cfDNA measurement could provide simple and quantifiable parameters for monitoring a disease progression.

New Paradigms for Familiar Diseases: Lessons Learned on Circulatory Bacterial Signatures in Cardiometabolic Diseases

Despite the strongly accumulating evidence for microbial signatures in metabolic tissues, including the blood, suggesting a novel paradigm for metabolic disease development, the notion of a core blood bacterial signature in health and disease remains a contentious concept. Recent studies clearly demonstrate that under a strict contamination-free environment, methods such as 16 S rRNA gene sequencing, fluorescence in-situ hybridization, transmission electron microscopy, and several more, allied with advanced bioinformatics tools, allow unambiguous detection and quantification of bacteria and bacterial DNA in human tissues. Bacterial load and compositional changes in the blood have been reported for numerous disease states, suggesting that bacteria and their components may partially induce systemic inflammation in cardiometabolic disease. This concept has been so far primarily based on measurements of surrogate parameters. It is now highly desirable to translate the current knowledge into diagnostic, prognostic, and therapeutic approaches.This review addresses the potential clinical relevance of a blood bacterial signature pertinent to cardiometabolic diseases and outcomes and new avenues for translational approaches. It discusses pitfalls related to research in low bacterial biomass while proposing mitigation strategies for future research and application approaches.

Comprehensive human amniotic fluid metagenomics supports the sterile womb hypothesis

As metagenomic approaches for detecting infectious agents have improved, each tissue that was once thought to be sterile has been found to harbor a variety of microorganisms. Controversy still exists over the status of amniotic fluid, which is part of an immunologically privileged zone that is required to prevent maternal immune system rejection of the fetus. Due to this privilege, the exclusion of microbes has been proposed to be mandatory, leading to the sterile womb hypothesis. Since nucleic acid yields from amniotic fluid are very low, contaminating nucleic acid found in water, reagents and the laboratory environment frequently confound attempts to address this hypothesis. Here we present metagenomic criteria for microorganism detection and a metagenomic method able to be performed with small volumes of starting material, while controlling for exogenous contamination, to circumvent these and other pitfalls. We use this method to show that human mid-gestational amniotic fluid has no detectable virome or microbiome, supporting the sterile womb hypothesis.

Bovine milk microbiota: Evaluation of different DNA extraction protocols for challenging samples

The use of an adequate protocol that accurately extracts microbial DNA from bovine milk samples is of importance for downstream analysis such as 16S ribosomal RNA gene sequencing. Although sequencing platforms such as Illumina are very common, there are reservations concerning reproducibility in challenging samples that combine low bacterial loads with high amounts of host DNA. The objective of this study was to evaluate six different DNA extraction protocols applied to four different prototype milk samples (low/high level of colony‐forming units [cfu] and somatic cells). DNA extracts were sequenced on Illumina MiSeq with primers for the hypervariable regions V1V2 and V3V4. Different protocols were evaluated by analyzing the yield and purity of DNA extracts and the number of clean reads after sequencing. Three protocols with the highest median number of clean reads were selected. To assess reproducibility, these extraction replicates were resequenced in triplicates (n = 120). The most reproducible results for α‐ and β‐diversity were obtained with the modified DNeasy Blood & Tissue kit after a chemical pretreatment plus resuspension of the cream fraction. The unmodified QIAamp DNA Mini kit performed particularly weak in the sample representing unspecific mastitis. These results suggest that pretreatment in combination with the modified DNeasy Blood & Tissue kit is useful in extracting microbial DNA from challenging milk samples. To increase reproducibility, we recommend that duplicates, if not triplicates, should be sequenced. We showed that high counts of somatic cells challenged DNA extraction, which shapes the need to apply modified extraction protocols.

First encounters of the microbial kind: perinatal factors direct infant gut microbiome establishment

The human gut microbiome harbors a diverse range of microbes that play a fundamental role in the health and well-being of their host. The early-life microbiome has a major influence on human development and long-term health. Perinatal factors such as maternal nutrition, antibiotic use, gestational age and mode of delivery influence the initial colonization, development, and function of the neonatal gut microbiome. The perturbed early-life gut microbiome predisposes infants to diseases in early and later life. Understanding how perinatal factors guide and shape the composition of the early-life microbiome is essential to improving infant health. The following review provides a synopsis of perinatal factors with the most decisive influences on initial microbial colonization of the infant gut.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

Advancements in next-generation sequencing technology have dramatically reduced the cost and increased the ease of microbial whole genome sequencing. This approach is revolutionizing the identification and analysis of foodborne microbial pathogens, facilitating expedited detection and mitigation of foodborne outbreaks, improving public health outcomes, and limiting costly recalls. However, next-generation sequencing is still anchored in the traditional laboratory practice of the selection and culture of a single isolate. Metagenomic-based approaches, including metabarcoding and shotgun and long-read metagenomics, are part of the next disruptive revolution in food safety diagnostics and offer the potential to directly identify entire microbial communities in a single food, ingredient, or environmental sample. In this review, metagenomic-based approaches are introduced and placed within the context of conventional detection and diagnostic techniques, and essential considerations for undertaking metagenomic assays and data analysis are described. Recent applications of the use of metagenomics for food safety are discussed alongside current limitations and knowledge gaps and new opportunities arising from the use of this technology.

HIGHLIGHTS

Maternal and early life exposures and their potential to influence development of the microbiome

At the dawn of the twentieth century, the medical care of mothers and children was largely relegated to family members and informally trained birth attendants. As the industrial era progressed, early and key public health observations among women and children linked the persistence of adverse health outcomes to poverty and poor nutrition. In the time hence, numerous studies connecting genetics ("nature") to public health and epidemiologic data on the role of the environment ("nurture") have yielded insights into the importance of early life exposures in relation to the occurrence of common diseases, such as diabetes, allergic and atopic disease, cardiovascular disease, and obesity. As a result of these parallel efforts in science, medicine, and public health, the developing brain, immune system, and metabolic physiology are now recognized as being particularly vulnerable to poor nutrition and stressful environments from the start of pregnancy to 3 years of age. In particular, compelling evidence arising from a diverse array of studies across mammalian lineages suggest that modifications to our metagenome and/or microbiome occur following certain environmental exposures during pregnancy and lactation, which in turn render risk of childhood and adult diseases. In this review, we will consider the evidence suggesting that development of the offspring microbiome may be vulnerable to maternal exposures, including an analysis of the data regarding the presence or absence of a low-biomass intrauterine microbiome.

Endometrial microbiota composition is associated with reproductive outcome in infertile patients

BACKGROUND

Previous evidence indicates associations between the female reproductive tract microbiome composition and reproductive outcome in infertile patients undergoing assisted reproduction. We aimed to determine whether the endometrial microbiota composition is associated with reproductive outcomes of live birth, biochemical pregnancy, clinical miscarriage or no pregnancy.

METHODS

Here, we present a multicentre prospective observational study using 16S rRNA gene sequencing to analyse endometrial fluid and biopsy samples before embryo transfer in a cohort of 342 infertile patients asymptomatic for infection undergoing assisted reproductive treatments.

RESULTS

A dysbiotic endometrial microbiota profile composed of Atopobium, Bifidobacterium, Chryseobacterium, Gardnerella, Haemophilus, Klebsiella, Neisseria, Staphylococcus and Streptococcus was associated with unsuccessful outcomes. In contrast, Lactobacillus was consistently enriched in patients with live birth outcomes.

CONCLUSIONS

Our findings indicate that endometrial microbiota composition before embryo transfer is a useful biomarker to predict reproductive outcome, offering an opportunity to further improve diagnosis and treatment strategies. Video Abstract.

Freeze-Thaw Pretreatment Can Improve Efficiency of Bacterial DNA Extraction From Meconium

Although the presence of live microbes in utero remains under debate, newborn gastrointestinal bacteria are undoubtedly important to infant health. Measuring bacteria in meconium is an ideal strategy to understand this issue; however, the low efficiency of bacterial DNA extraction from meconium has limited its utilization. This study aims to improve the efficiency of bacterial DNA extraction from meconium, which generally has low levels of microflora but high levels of PCR inhibitors in the viscous matrix. The research was approved by the ethical committee of the Xiamen Maternity and Child Health Care Hospital, Xiamen, China. All the mothers delivered naturally, and their newborns were healthy. Meconium samples passed by the newborns within 24 h were collected. Each sample was scraped off of a sterile diaper, transferred to a 5-ml sterile tube, and stored at −80°C. For the assay, a freeze-thawing sample preparation protocol was designed, in which a meconium-InhibitEX buffer mixture was intentionally frozen 1–3 times at −20°C, −80°C, and (or) in liquid nitrogen. Then, DNA was extracted using a commercial kit and sequenced by 16S rDNA to verify the enhanced bacterial DNA extraction efficiency. Ultimately, we observed the following: (1) About 30 mg lyophilized meconium was the optimal amount for DNA extraction. (2) Freezing treatment for 6 h improved DNA extraction at −20°C. (3) DNA extraction efficiency was significantly higher with the immediate thaw strategy than with gradient thawing at −20°C, −80°C, and in liquid nitrogen. (4) Among the conditions of −20°C, −80°C, and liquid nitrogen, −20°C was the best freezing condition for both improving DNA extraction efficiency and preserving microbial species diversity in meconium, while liquid nitrogen was the worst condition. (5) Three freeze-thaw cycles could markedly enhance DNA extraction efficiency and preserve the species diversity of meconium microflora. We developed a feasible freeze-thaw pretreatment protocol to improve the extraction of microbial DNA from meconium, which may be beneficial for newborn bacterial colonization studies.

Bacteria in the amniotic fluid without inflammation: early colonization vs. contamination

OBJECTIVES

Intra-amniotic infection, defined by the presence of microorganisms in the amniotic cavity, is often accompanied by intra-amniotic inflammation. Occasionally, laboratories report the growth of bacteria or the presence of microbial nucleic acids in amniotic fluid in the absence of intra-amniotic inflammation. This study was conducted to determine the clinical significance of the presence of bacteria in amniotic fluid samples in the absence of intra-amniotic inflammation.

METHODS

A retrospective cross-sectional study included 360 patients with preterm labor and intact membranes who underwent transabdominal amniocentesis for evaluation of the microbial state of the amniotic cavity as well as intra-amniotic inflammation. Cultivation techniques were used to isolate microorganisms, and broad-range polymerase chain reaction coupled with electrospray ionization mass spectrometry (PCR/ESI-MS) was utilized to detect the nucleic acids of bacteria, viruses, and fungi.

RESULTS

Patients whose amniotic fluid samples evinced microorganisms but did not indicate inflammation had a similar perinatal outcome to those without microorganisms or inflammation [amniocentesis-to-delivery interval (p=0.31), spontaneous preterm birth before 34 weeks (p=0.83), acute placental inflammatory lesions (p=1), and composite neonatal morbidity (p=0.8)].

CONCLUSIONS

The isolation of microorganisms from a sample of amniotic fluid in the absence of intra-amniotic inflammation is indicative of a benign condition, which most likely represents contamination of the specimen during the collection procedure or laboratory processing rather than early colonization or infection.

A critical analysis of research methods and experimental models to study the root canal microbiome

Endodontic microbiology deals with the study of the microbial aetiology and pathogenesis of pulpal and periradicular inflammatory diseases. Research in endodontic microbiology started almost 130 years ago and since then has mostly focussed on establishing and confirming the infectious aetiology of apical periodontitis, identifying the microbial species associated with the different types of endodontic infections and determining the efficacy of treatment procedures in eradicating or controlling infection. Diverse analytical methods have been used over the years, each one with their own advantages and limitations. In this review, the main features and applications of the most used technologies are discussed, and advice is provided to improve study designs in order to properly address the scientific questions and avoid setbacks that can compromise the results. Finally, areas of future research are described.

The Role of Endogenous Metal Nanoparticles in Biological Systems

The blood and tissues of vertebrate animals and mammals contain small endogenous metal nanoparticles. These nanoparticles were observed to be composed of individual atoms of iron, copper, zinc, silver, gold, platinum, and other metals. Metal nanoparticles can bind proteins and produce proteinaceous particles called proteons. A small fraction of the entire pool of nanoparticles is usually linked with proteins to form proteons. These endogenous metal nanoparticles, along with engineered zinc and copper nanoparticles at subnanomolar levels, were shown to be lethal to cultured cancer cells. These nanoparticles appear to be elemental crystalline metal nanoparticles. It was discovered that zinc nanoparticles produce no odor response but increase the odor reaction if mixed with an odorant. Some other metal nanoparticles, including copper, silver, gold, and platinum nanoparticles, do not affect the responses to odorants. The sources of metal nanoparticles in animal blood and tissues may include dietary plants and gut microorganisms. The solid physiological and biochemical properties of metal nanoparticles reflect their importance in cell homeostasis and disease.

Bacterial Invasion of Pulp Blood Vessels in Teeth with Symptomatic Irreversible Pulpitis

INTRODUCTION

This study described the degenerative changes and infection patterns of the pulp tissue associated with symptomatic irreversible pulpitis.

METHODS

The material consisted of 32 extracted teeth with untreated deep caries that were clinically and histologically diagnosed with irreversible pulpitis and were part of the histopathologic collection of 1 of the authors. The controls consisted of intact teeth with normal uninflamed pulps and teeth with reversible pulpitis. Teeth were processed for histopathologic and histobacteriologic analyses.

RESULTS

All teeth with irreversible pulpitis showed areas of severe acute inflammation, necrosis, microabscesses, and bacterial infection in the pulp chamber. These areas were surrounded by a chronic inflammatory infiltrate, and, at the distance, the pulp tissue was often uninflamed. Bacteria were also observed in the areas surrounding the necrotic foci, both as scattered cells through the extravascular space and at varying numbers within the blood vessel lumen. The number of bacteria and the density of the intravascular bacterial aggregations varied considerably. In one third of the cases, bacteria occurred in the lumen of venules in areas at a considerable distance from the necrotic focus in the coronal third of the root. No intravascular bacteria were noted in the middle and apical segments of the canal. No bacteria were found in the pulps of any of the control specimens.

CONCLUSIONS

Bacterial invasion and colonization of necrotic areas were observed in the pulp of all teeth with caries exposure and symptomatic irreversible pulpitis. Bacterial penetration of blood vessels occurred in all cases, suggesting that this may be an important mechanism of spread of bacterial infection through the pulp tissue in an endodontic infection.

Gut dsDNA virome shows diversity and richness alterations associated with childhood obesity and metabolic syndrome

Changes in the human gut microbiome are associated with obesity and metabolic syndrome, but the role of the gut virome in both diseases remains largely unknown. We characterized the gut dsDNA virome of 28 school-aged children with healthy normal-weight (NW, n = 10), obesity (O, n = 10), and obesity with metabolic syndrome (OMS, n = 8), using metagenomic sequencing of virus-like particles (VLPs) from fecal samples. The virome classification confirmed the bacteriophages' dominance, mainly composed of Caudovirales. Notably, phage richness and diversity of individuals with O and OMS tended to increase, while the VLP abundance remained the same among all groups. Of the 4,611 phage contigs composing the phageome, 48 contigs were highly prevalent in ≥80% of individuals, suggesting high inter-individual phage diversity. The abundance of several contigs correlated with gut bacterial taxa; and with anthropometric and biochemical parameters altered in O and OMS. To our knowledge, this gut phageome represents one of the largest datasets and suggests disease-specific phage alterations.

Paenibacillus infection with frequent viral coinfection contributes to postinfectious hydrocephalus in Ugandan infants

Postinfectious hydrocephalus (PIH), which often follows neonatal sepsis, is the most common cause of pediatric hydrocephalus worldwide, yet the microbial pathogens underlying this disease remain to be elucidated. Characterization of the microbial agents causing PIH would enable a shift from surgical palliation of cerebrospinal fluid (CSF) accumulation to prevention of the disease. Here, we examined blood and CSF samples collected from 100 consecutive infant cases of PIH and control cases comprising infants with non-postinfectious hydrocephalus in Uganda. Genomic sequencing of samples was undertaken to test for bacterial, fungal, and parasitic DNA; DNA and RNA sequencing was used to identify viruses; and bacterial culture recovery was used to identify potential causative organisms. We found that infection with the bacterium Paenibacillus, together with frequent cytomegalovirus (CMV) coinfection, was associated with PIH in our infant cohort. Assembly of the genome of a facultative anaerobic bacterial isolate recovered from cultures of CSF samples from PIH cases identified a strain of Paenibacillus thiaminolyticus This strain, designated Mbale, was lethal when injected into mice in contrast to the benign reference Paenibacillus strain. These findings show that an unbiased pan-microbial approach enabled characterization of Paenibacillus in CSF samples from PIH cases, and point toward a pathway of more optimal treatment and prevention for PIH and other proximate neonatal infections.

DOE JGI Metagenome Workflow

The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751–D763, 2021, https://doi.org/10.1093/nar/gkaa939) comparative analysis system and provided for download via the JGI data portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723–D733, 2021, https://doi.org/10.1093/nar/gkaa983).

IMPORTANCE The DOE JGI Metagenome Workflow is designed for processing metagenomic data sets starting from Illumina fastq files. It performs data preprocessing, error correction, assembly, structural and functional annotation, and binning. The results of processing are provided in several standard formats, such as fasta and gff, and can be used for subsequent integration into the Integrated Microbial Genomes and Microbiomes (IMG/M) system where they can be compared to a comprehensive set of publicly available metagenomes. As of 30 July 2020, 7,155 JGI metagenomes have been processed by the DOE JGI Metagenome Workflow. Here, we present a metagenome workflow developed at the JGI that generates rich data in standard formats and has been optimized for downstream analyses ranging from assessment of the functional and taxonomic composition of microbial communities to genome-resolved metagenomics and the identification and characterization of novel taxa. This workflow is currently being used to analyze thousands of metagenomic data sets in a consistent and standardized manner.

Standardization of microbiome studies for urolithiasis: an international consensus agreement

Numerous metagenome-wide association studies (MWAS) for urolithiasis have been published, leading to the discovery of potential interactions between the microbiome and urolithiasis. However, questions remain about the reproducibility, applicability and physiological relevance of these data owing to discrepancies in experimental technique and a lack of standardization in the field. One barrier to interpreting MWAS is that experimental biases can be introduced at every step of the experimental pipeline, including sample collection, preservation, storage, processing, sequencing, data analysis and validation. Thus, the introduction of standardized protocols that maintain the flexibility to achieve study-specific objectives is urgently required. To address this need, the first international consortium for microbiome in urinary stone disease - MICROCOSM - was created and consensus panel members were asked to participate in a consensus meeting to develop standardized protocols for microbiome studies if they had published an MWAS on urolithiasis. Study-specific protocols were revised until a consensus was reached. This consensus group generated standardized protocols, which are publicly available via a secure online server, for each step in the typical clinical microbiome-urolithiasis study pipeline. This standardization creates the benchmark for future studies to facilitate consistent interpretation of results and, collectively, to lead to effective interventions to prevent the onset of urolithiasis, and will also be useful for investigators interested in microbiome research in other urological diseases.

Methods for exploring the faecal microbiome of premature infants: a review

The premature infant gut microbiome plays an important part in infant health and development, and recognition of the implications of microbial dysbiosis in premature infants has prompted significant research into these issues. The approaches to designing investigations into microbial populations are many and varied, each with its own benefits and limitations. The technique used can influence results, contributing to heterogeneity across studies. This review aimed to describe the most common techniques used in researching the preterm infant microbiome, detailing their various limitations. The objective was to provide those entering the field with a broad understanding of available methodologies, so that the likely effects of their use can be factored into literature interpretation and future study design. We found that although many techniques are used for characterising the premature infant microbiome, 16S rRNA short amplicon sequencing is the most common. 16S rRNA short amplicon sequencing has several benefits, including high accuracy, discoverability and high throughput capacity. However, this technique has limitations. Each stage of the protocol offers opportunities for the injection of bias. Bias can contribute to variability between studies using 16S rRNA high throughout sequencing. Thus, we recommend that the interpretation of previous results and future study design be given careful consideration.

Differential response of digesta- and mucosa-associated intestinal microbiota to dietary insect meal during the seawater phase of Atlantic salmon

Background

Intestinal digesta is commonly used for studying responses of microbiota to dietary shifts, yet evidence is accumulating that it represents an incomplete view of the intestinal microbiota. The present work aims to investigate the differences between digesta- and mucosa-associated intestinal microbiota in Atlantic salmon (Salmo salar) and how they may respond differently to dietary perturbations. In a 16-week seawater feeding trial, Atlantic salmon were fed either a commercially-relevant reference diet or an insect meal diet containing ~ 15% black soldier fly (Hermetia illucens) larvae meal. The digesta- and mucosa-associated distal intestinal microbiota were profiled by 16S rRNA gene sequencing.

Results

Regardless of diet, we observed substantial differences between digesta- and mucosa-associated intestinal microbiota. Microbial richness and diversity were much higher in the digesta than the mucosa. The insect meal diet altered the distal intestinal microbiota resulting in higher microbial richness and diversity. The diet effect, however, depended on the sample origin. Digesta-associated intestinal microbiota showed more pronounced changes than the mucosa-associated microbiota. Multivariate association analyses identified two mucosa-enriched taxa, Brevinema andersonii and Spirochaetaceae, associated with the expression of genes related to immune responses and barrier function in the distal intestine, respectively.

Conclusions

Our data show that salmon intestinal digesta and mucosa harbor microbial communities with clear differences. While feeding insects increased microbial richness and diversity in both digesta- and mucosa-associated intestinal microbiota, mucosa-associated intestinal microbiota seems more resilient to variations in the diet composition. To fully unveil the response of intestinal microbiota to dietary changes, concurrent profiling of digesta- and mucosa-associated intestinal microbiota is recommended whenever feasible. Specific taxa enriched in the intestinal mucosa are associated to gene expression related to immune responses and barrier function. Detailed studies are needed on the ecological and functional significance of taxa associated to intestinal microbiota dwelling on the mucosa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-020-00071-3.

The importance of airway and lung microbiome in the critically ill

During critical illness, there are a multitude of forces such as antibiotic use, mechanical ventilation, diet changes and inflammatory responses that could bring the microbiome out of balance. This so-called dysbiosis of the microbiome seems to be involved in immunological responses and may influence outcomes even in individuals who are not as vulnerable as a critically ill ICU population. It is therefore probable that dysbiosis of the microbiome is a consequence of critical illness and may, subsequently, shape an inadequate response to these circumstances.Bronchoscopic studies have revealed that the carina represents the densest site of bacterial DNA along healthy airways, with a tapering density with further bifurcations. This likely reflects the influence of micro-aspiration as the primary route of microbial immigration in healthy adults. Though bacterial DNA density grows extremely sparse at smaller airways, bacterial signal is still consistently detectable in bronchoalveolar lavage fluid, likely reflecting the fact that lavage via a wedged bronchoscope samples an enormous surface area of small airways and alveoli. The dogma of lung sterility also violated numerous observations that long predated culture-independent microbiology.The body's resident microbial consortia (gut and/or respiratory microbiota) affect normal host inflammatory and immune response mechanisms. Disruptions in these host-pathogen interactions have been associated with infection and altered innate immunity.In this narrative review, we will focus on the rationale and current evidence for a pathogenic role of the lung microbiome in the exacerbation of complications of critical illness, such as acute respiratory distress syndrome and ventilator-associated pneumonia.

Maternal and infant factors that shape neonatal gut colonization by bacteria

INTRODUCTION

Early life is a critical developmental window coinciding with the establishment of a community of neonatal gut microbes which are vitally important for immune development. The composition of this microbial community is affected by multiple factors.

AREAS COVERED

The effect of pre-pregnancy and pregnancy maternal health, maternal nutrition, pregnancy disorders such as gestational diabetes, maternal antibiotic usage, delivery mode, infant feeding, and infant antibiotic usage on gut microbial composition are outlined along with the potential impact of associated microbiota differences on infant health.

EXPERT OPINION

Recent developments in understanding what shapes our microbiota indicates that the greatest impact on infant gut microbiota composition during the first year of life is seen with the mode of delivery, infant diet, and infant antibiotic usage. Current data is insufficient to fully establish the role of apparently less important factors such as maternal health on microbiota development although their impact is likely smaller. Technological advances will allow for improved understanding of underlying mechanisms by which specific microbes impact on infant health, which in time will enable full appreciation of the role of the gut microbiota in early life development.

Tailoring plant-associated microbial inoculants in agriculture: a roadmap for successful application

Plants are now recognized as metaorganisms which are composed of a host plant associated with a multitude of microbes that provide the host plant with a variety of essential functions to adapt to the local environment. Recent research showed the remarkable importance and range of microbial partners for enhancing the growth and health of plants. However, plant-microbe holobionts are influenced by many different factors, generating complex interactive systems. In this review, we summarize insights from this emerging field, highlighting the factors that contribute to the recruitment, selection, enrichment, and dynamic interactions of plant-associated microbiota. We then propose a roadmap for synthetic community application with the aim of establishing sustainable agricultural systems that use microbial communities to enhance the productivity and health of plants independently of chemical fertilizers and pesticides. Considering global warming and climate change, we suggest that desert plants can serve as a suitable pool of potentially beneficial microbes to maintain plant growth under abiotic stress conditions. Finally, we propose a framework for advancing the application of microbial inoculants in agriculture.

Microbial Residents of the Atlantis Massif's Shallow Serpentinite Subsurface

The International Ocean Discovery Program Expedition 357—“Serpentinization and Life”—utilized seabed drills to collect rocks from the oceanic crust. The recovered rock cores represent the shallow serpentinite subsurface of the Atlantis Massif, where reactions between uplifted mantle rocks and water, collectively known as serpentinization, produce environmental conditions that can stimulate biological activity and are thought to be analogous to environments that were prevalent on the early Earth and perhaps other planets. The methodology and results of this project have implications for life detection experiments, including sample return missions, and provide a window into the diversity of microbial communities inhabiting subseafloor serpentinites.

The Atlantis Massif rises 4,000 m above the seafloor near the Mid-Atlantic Ridge and consists of rocks uplifted from Earth’s lower crust and upper mantle. Exposure of the mantle rocks to seawater leads to their alteration into serpentinites. These aqueous geochemical reactions, collectively known as the process of serpentinization, are exothermic and are associated with the release of hydrogen gas (H₂), methane (CH₄), and small organic molecules. The biological consequences of this flux of energy and organic compounds from the Atlantis Massif were explored by International Ocean Discovery Program (IODP) Expedition 357, which used seabed drills to collect continuous sequences of shallow (<16 m below seafloor) marine serpentinites and mafic assemblages. Here, we report the census of microbial diversity in samples of the drill cores, as measured by environmental 16S rRNA gene amplicon sequencing. The problem of contamination of subsurface samples was a primary concern during all stages of this project, starting from the initial study design, continuing to the collection of samples from the seafloor, handling the samples shipboard and in the lab, preparing the samples for DNA extraction, and analyzing the DNA sequence data. To distinguish endemic microbial taxa of serpentinite subsurface rocks from seawater residents and other potential contaminants, the distributions of individual 16S rRNA gene sequences among all samples were evaluated, taking into consideration both presence/absence and relative abundances. Our results highlight a few candidate residents of the shallow serpentinite subsurface, including uncultured representatives of the Thermoplasmata, Acidobacteria, Acidimicrobia, and Chloroflexi.

IMPORTANCE The International Ocean Discovery Program Expedition 357—“Serpentinization and Life”—utilized seabed drills to collect rocks from the oceanic crust. The recovered rock cores represent the shallow serpentinite subsurface of the Atlantis Massif, where reactions between uplifted mantle rocks and water, collectively known as serpentinization, produce environmental conditions that can stimulate biological activity and are thought to be analogous to environments that were prevalent on the early Earth and perhaps other planets. The methodology and results of this project have implications for life detection experiments, including sample return missions, and provide a window into the diversity of microbial communities inhabiting subseafloor serpentinites.

Profiling of Oral Bacterial Communities

The profiling of bacterial communities by the sequencing of housekeeping genes such as that encoding the small subunit ribosomal RNA has revealed the extensive diversity of bacterial life on earth. Standard protocols have been developed and are widely used for this application, but individual habitats may require modification of methods. This review discusses the sequencing and analysis methods most appropriate for the study of the bacterial component of the human oral microbiota. If possible, DNA should be extracted from samples soon after collection. If samples have to be stored for practical reasons, precautions to avoid DNA degradation on freezing should be taken. A critical aspect of profiling oral bacterial communities is the choice of region of the 16S rRNA gene for sequencing. The V1-V2 region provides the best discrimination between species of the genus Streptococcus, the most common genus in the mouth and important in health and disease. The MiSeq platform is most commonly used for sequencing, but long-read technologies are now becoming available that should improve the resolution of analyses. There are a variety of well-established data analysis pipelines available, including mothur and QIIME, which identify sequence reads as phylotypes by comparing them to reference data sets or grouping them into operational taxonomic units. DADA2 has improved sequence error correction capabilities and resolves reads to unique variants. Two curated oral 16S rRNA databases are available: HOMD and CORE. Expert interpretation of community profiles is required, both to detect the presence of contaminating DNA, which is commonly present in the reagents used in analysis, and to differentiate oral and nonoral bacteria and determine the significance of findings. Despite advances in shotgun whole-genome metagenomic methods, oral bacterial community profiling via 16S rRNA sequence analysis remains a valuable technique for the characterization of oral bacterial populations.

Evaluation of reported sediment samples from 20 Ma using a molecular phylogenetic approach: comment on Liu et al. (2017)

Liu et al. reported the cultivation and DNA sequencing of 69 fungal isolates (Ascomycota and Basidiomycota) from ancient subseafloor sediments, suggesting that they represent living fungal populations that have persisted for over 20 million years. Because these findings could bring about a paradigm shift in our understanding of the spatial breadth of the deep subsurface biosphere as well as the longevity of ancient DNA, it is extremely important to verify that their samples represent pure ancient fungi from 20 million years ago without contamination by modern species. For this purpose, we estimated the divergence times of Dikarya (Ascomycota + Basidiomycota) and Mucoromycota fungi assuming that the fungal isolates were actually sampled from 20 Ma (mega-annum) sediments and evaluated the validity of the sample ages. Using this approach, we estimate that the age of the last common ancestor of Dikarya and Mucoromycota fungi greatly exceeds the age of the Earth. Our finding emphasizes the importance of using reliable approaches to confirm the dating of ancient samples.

Microbiome applications for pathology: challenges of low microbial biomass samples during diagnostic testing

The human microbiome can play key roles in disease, and diagnostic testing will soon have the ability to examine these roles in the context of clinical applications. Currently, most diagnostic testing in pathology applications focuses on a small number of disease‐causing microbes and dismisses the whole microbial community that causes or is modulated by disease. Microbiome modifications have already provided clinically relevant insights in gut and oral diseases, such as irritable bowel disease, but there are currently limitations when clinically examining microbiomes outside of these body sites. This is critical, as the majority of microbial samples used in pathology originate from body sites that contain low concentrations of microbial DNA, including skin, tissue, blood, and urine. These samples, also known as low microbial biomass samples, are difficult to examine without careful consideration and precautions to mitigate contamination and biases. Here, we present the limitations when analysing low microbial biomass samples using current protocols and techniques and highlight the advantages that microbiome testing can offer diagnostics in the future, if the proper precautions are implemented. Specifically, we discuss the sources of contamination and biases that may result in false assessments for these sample types. Finally, we provide recommendations to mitigate contamination and biases from low microbial biomass samples during diagnostic testing, which will be especially important to effectively diagnose and treat patients using microbiome analyses.

Revealing the secret life of skin - with the microbiome you never walk alone

The human skin microbiome has recently become a focus for both the dermatological and cosmetic fields. Understanding the skin microbiota, that is the collection of vital microorganisms living on our skin, and how to maintain its delicate balance is an essential step to gain insight into the mechanisms responsible for healthy skin and its appearance. Imbalances in the skin microbiota composition (dysbiosis) are associated with several skin conditions, either pathological such as eczema, acne, allergies or dandruff or non‐pathological such as sensitive skin, irritated skin or dry skin. Therefore, the development of approaches which preserve or restore the natural, individual balance of the microbiota represents a novel target not only for dermatologists but also for skincare applications. This review gives an overview on the current knowledge on the skin microbiome, the currently available sampling and analysis techniques as well as a description of current approaches undertaken in the skincare segment to help restoring and balancing the structure and functionality of the skin microbiota.

Technical pitfalls that bias comparative microbial community analyses of aquatic disease Ian Hewson

The accessibility of high-throughput DNA sequencing technologies has attracted the application of comparative microbial analyses to study diseases. These studies present a window into host microbiome diversity and composition that can be used to address ecological theory in the context of host biology and behavior. Recently, comparative microbiome studies have been used to study non-vertebrate aquatic diseases to elucidate microorganisms potentially involved in disease processes or in disease prevention. These investigations suffer from many well-described biases, especially prior to sequence analyses, that could lead to misleading conclusions. Microbiome-focused studies of aquatic metazoan diseases provide valuable documentation of microbial ecology, although, they are only a starting point for establishing disease etiology, which demands quantitative validation through targeted approaches. The microbiome approach to understanding disease is most useful after laboratory diagnostics guided by pathology have failed to identify a causative agent. This opinion piece presents several technical pitfalls which may affect wider interpretation of microbe-host interactions through comparative microbial community analyses and provides recommendations, based on studies in non-aquatic systems, for incorporation into future aquatic disease research.

Fungal Community Composition and Potential Depth-Related Driving Factors Impacting Distribution Pattern and Trophic Modes from Epi- to Abyssopelagic Zones of the Western Pacific Ocean

Fungi play an important role in cycling organic matter and nutrients in marine ecosystems. However, the distribution of fungal communities in the ocean, especially the vertical distribution along depth in the water column, remained poorly understood. Here, we assess the depth-related distribution pattern of fungal communities along the water column from epi- to abyssopelagic zones of the Western Pacific Ocean using internal transcribed spacer 2 (ITS2) metabarcoding. Majority of the assigned OTUs were affiliated to Ascomycota, followed by three other minor phyla (Basidiomycota, Chytridiomycota, and Mucoromycota). The epipelagic zone harbored a higher OTU richness with distinct fungal communities as compared with meso-, bathy-, and abyssopelagic zones. Across the whole water column, depth appears as a key parameter for both fungal α- and β-diversity. However, when the dataset was split into the upper (5-500 m) and deeper (below 500 m) layers, no significant correlation was observed between depth and community compositions. In the upper layer, temperature and dissolved oxygen were recognized as the primary environmental factors shaping fungal α- and β- diversity. By parsing fungal OTUs into ecological categories, multi-trophic mode of nutrition was found to be more prevalent with increasing depth, suggesting a potential adaptation to the extreme conditions of the deep sea. This study provides new and meaningful information on the depth-stratified fungal diversity, community structure, and putative ecological roles in the open sea.

Complex interactions between the microbiome and cancer immune therapy

Immuno-oncology has rapidly grown in the last thirty years, and immunotherapeutic agents are now approved to treat many disparate cancers. Immune checkpoint inhibitors (ICIs) are employed to augment cytotoxic anti-cancer activity by inhibiting negative regulatory elements of the immune system. Modulating the immune system to target neoplasms has improved survivability of numerous cancers in many individuals, but forecasting outcomes post therapy is difficult due to insufficient predictive biomarkers. Recently, the tumor and gastrointestinal microbiome and immune milieu have been investigated as predictors and influencers of cancer immune therapy. In this review, we discuss: (1) ways to measure the microbiome including relevant bioinformatic analyses, (2) recent developments in animal studies and human clinical trials utilizing gut microbial composition and function as biomarkers of cancer immune therapy response and toxicity, and (3) using prebiotics, probiotics, postbiotics, antibiotics, and fecal microbiota transplant (FMT) to modulate immune therapy. We discuss the respective benefits of 16S ribosomal RNA (rRNA) gene and shotgun metagenomic sequencing including important considerations in obtaining samples and in designing and interpreting human and animal microbiome studies. We then focus on studies discussing the differences in response to ICIs in relation to the microbiome and inflammatory mediators. ICIs cause colitis in up to 25% of individuals, and colitis is often refractory to common immunosuppressive medications. Researchers have measured microbiota composition prior to ICI therapy and correlated baseline microbiota composition with efficacy and colitis. Certain bacterial taxa that appear to enhance therapeutic benefit are also implicated in increased susceptibility to colitis, alluding to a delicate balance between pro-inflammatory tumor killing and anti-inflammatory protection from colitis. Pre-clinical and clinical models have trialed probiotic administration, e.g. Bifidobacterium spp. or FMT, to treat colitis when immune suppressive agents fail. We are excited about the future of modulating the microbiome to predict and influence cancer outcomes. Furthermore, novel therapies employed for other illnesses including bacteriophage and genetically-engineered microbes can be adapted in the future to promote increased advancements in cancer treatment and side effect management.

Using QC-Blind for Quality Control and Contamination Screening of Bacteria DNA Sequencing Data Without Reference Genome

Quality control for next generation sequencing (NGS) has become increasingly important with the ever increasing importance of sequencing data for omics studies. Tools have been developed for filtering possible contaminants from species with known reference genome. Unfortunately, reference genomes for all the species involved, including the contaminants, are required for these tools to work. This precludes many real-life samples that have no information about the complete genome of the target species, and are contaminated with unknown microbial species. In this work we proposed QC-Blind, a novel quality control pipeline for removing contaminants without any use of reference genomes. The pipeline merely requires the information about a few marker genes of the target species. The entire pipeline consists of unsupervised read assembly, contig binning, read clustering, and marker gene assignment. When evaluated on in silico, ab initio and in vivo datasets, QC-Blind proved effective in removing unknown contaminants with high specificity and accuracy, while preserving most of the genomic information of the target bacterial species. Therefore, QC-Blind could serve well in situations where limited information is available for both target and contamination species.

A Lot on Your Plate? Well-to-Well Contamination as an Additional Confounder in Microbiome Sequence Analyses

DNA sequence-based microbiome studies can be impacted by a range of different methodological artefacts. Contamination originating from laboratory kits and reagents can lead to erroneous results, particularly in samples containing a low microbial biomass. Minich and colleagues (mSystems 4:e00186-19, 2019, https://doi.org/10.1128/mSystems.00186-19) report on a different form of contamination, cross-contamination between samples that are processed together. They find that transfer of material between samples in 96-well plates is a common occurrence. The DNA extraction step, particularly when carried out automatedly, is identified as the major source of this contamination type. Well-to-well contamination distorts diversity measures, with low-biomass samples particularly affected. This report has important implications for attempts to decontaminate microbiome sequencing results. As contamination is derived from both external sources and crossover between samples, it is not appropriate to simply remove sequence variants that are detected in negative-control blanks, and more-nuanced decontamination approaches may be required.

Controlling for Contaminants in Low-Biomass 16S rRNA Gene Sequencing Experiments

The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

Microbial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam, and (iv) predicting the sequence proportion arising from defined contaminant sources implemented in SourceTracker. As expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 80.1% of the most diluted sample arising from contaminant sequences. Inclusion of contaminant sequences led to overinflated diversity estimates and distorted microbiome composition. All methods for contaminant identification successfully identified some contaminant sequences, which varied depending on the method parameters used and contaminant prevalence. Notably, removing sequences present in a negative control erroneously removed >20% of expected sequences. SourceTracker successfully removed over 98% of contaminants when the experimental environments were well defined. However, SourceTracker misclassified expected sequences and performed poorly when the experimental environment was unknown, failing to remove >97% of contaminants. In contrast, the Decontam frequency method did not remove expected sequences and successfully removed 70 to 90% of the contaminants.

IMPORTANCE The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

Laboratory contamination over time during low-biomass sample analysis

Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g., skin swabs, tissue biopsies, ice, water, degraded forensic samples or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high‐throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no‐template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over 5 years to characterize long‐term contaminant diversity. We additionally compared the contaminant content within a home‐made silica‐based extraction method, commonly used to analyse low endogenous content samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to modern molecular biology laboratories, and changed over time according to researcher, month and season. The commercial kit also contained higher microbial diversity and several human‐associated taxa in comparison to the home‐made silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low‐biomass metagenomic studies: (a) extraction blank controls should be included and sequenced with every batch of extractions and (b) the contributions of laboratory contamination should be assessed and reported in each high‐throughput metagenomic study.

Detection of Aminoglycoside Resistant Bacteria in Sludge Samples From Norwegian Drinking Water Treatment Plants

Through a culture-based approach using sludge from drinking water treatment plants, this study reports on the presence of aminoglycoside resistant bacteria at 23 different geographical locations in Norway. Sludge samples are derived from a large environmental area including drinking water sources and their surrounding catchment areas. Aminoglycoside resistant bacteria were detected at 18 of the sample sites. Only five samples did not show any growth of isolates resistant to the selected aminoglycosides, kanamycin and gentamycin. There was a statistically significant correlation between the numbers of kanamycin and gentamycin resistant bacteria isolated from the 23 samples, perhaps suggesting common determinants of resistance. Based on 16S rRNA sequencing of 223 aminoglycoside resistant isolates, three different genera of Bacteroidetes were found to dominate across samples. These were Flavobacterium, Mucilaginibacter and Pedobacter. Further phenotypic and genotypic analyses showed that efflux pumps, reduced membrane permeability and four assayed genes coding for aminoglycoside modifying enzymes AAC(6′)-Ib, AAC(3′)-II, APH(3′)-II, APH(3′)-III, could only explain the resistance of a few of the isolates selected for testing. aph(3′)-II was detected in 1.6% of total isolates, aac(6′)-Ib and aph(3′)-III in 0.8%, while aac(3′)-II was not detected in any of the isolates. The isolates, for which potential resistance mechanisms were found, represented 13 different genera suggesting that aminoglycoside resistance is widespread in bacterial genera indigenous to sludge. The present study suggests that aminoglycoside resistant bacteria are present in Norwegian environments with limited anthropogenic exposures. However, the resistance mechanisms remain largely unknown, and further analyses, including culture-independent methods, could be performed to investigate other potential resistance mechanisms. This is, to our knowledge, the first large scale nationwide investigation of aminoglycoside resistance in the Norwegian environment.

Metagenomic Approach to Characterizing Disease Epidemiology in a Disease-Endemic Environment in Northern Thailand

In this study, we used a metagenomic approach to analyze bacterial communities from diverse populations (humans, animals, and vectors) to investigate the role of these microorganisms as causative agents of disease in human and animal populations. Wild rodents and ectoparasites were collected from 2014 to 2018 in Nan province, Thailand where scrub typhus is highly endemic. Samples from undifferentiated febrile illness (UFI) patients were obtained from a local hospital. A total of 200 UFI patient samples were obtained and 309 rodents and 420 pools of ectoparasites were collected from rodents (n = 285) and domestic animals (n = 135). The bacterial 16S rRNA gene was amplified and sequenced with the Illumina. Real-time PCR and Sanger sequencing were used to confirm the next-generation sequencing (NGS) results and to characterize pathogen species. Several pathogens were detected by NGS in all populations studied and the most common pathogens identified included Bartonella spp., Rickettsia spp., Leptospira spp., and Orientia tsutsugamushi. Interestingly, Anaplasma spp. was detected in patient, rodent and tick populations, although they were not previously known to cause human disease from this region. Candidatus Neoehrlichia, Neorickettsia spp., Borrelia spp., and Ehrlichia spp. were detected in rodents and their associated ectoparasites. The same O. tsutsugamushi genotypes were shared among UFI patients, rodents, and chiggers in a single district indicating that the chiggers found on rodents were also likely responsible for transmitting to people. Serological testing using immunofluorescence assays in UFI samples showed high prevalence (IgM/IgG) of Rickettsia and Orientia pathogens, most notably among samples collected during September–November. Additionally, a higher number of seropositive samples belonged to patients in the working age population (20–60 years old). The results presented in this study demonstrate that the increased risk of human infection or exposure to chiggers and their associated pathogen (O. tsutsugamushi) resulted in part from two important factors; working age group and seasons for rice cultivation and harvesting. Evidence of pathogen exposure was shown to occur as there was seropositivity (IgG) in UFI patients for bartonellosis as well as for anaplasmosis. Using a metagenomic approach, this study demonstrated the circulation and transmission of several pathogens in the environment, some of which are known causative agents of illness in human populations.

Studying the microbiome and its complexities: an interview with Alan Walker

Alan Walker is a Senior Lecturer at the University of Aberdeen, UK, studying the intestinal microbiota and its interactions with the host’s diet. In this interview, Alan discusses his research interests, earlier studies of the ways contaminants can affect microbiome analyses, the excitement of experiments going well, and why science doesn’t need to be combative.

The natural environment as a reservoir of pathogenic and non-pathogenic Acinetobacter species

Acinetobacter is a genus of Gram-negative bacteria, which are oxidase-negative, exhibiting a twitching motility under a magnifying lens. Besides being important soil microorganisms, due to their contribution to the soil fertility, Acinetobacter species, particularly A. baumannii, hold a prominent place within the genus because, it is the most virulent among the other species, causing varying degrees of human infections in clinical environments. However, results of different research have shown that Acinetobacter species can be isolated from such natural environments as surface water, wastewater and sewage, healthy human skin, plant, animal and food material as well as domestic appliances. The presence of some other Acinetobacter species in the natural environment has been associated with beneficial roles including soil improvement, detoxification of oil spillages and as microflora in human and plant bodies. In this paper, we carried out an overview of various natural ecological niches as reservoirs of pathogenic and non-pathogenic Acinetobacter species.

Identification of Halophilic Microbes in Lung Fibrotic Tissue by Oligotyping

Idiopathic pulmonary fibrosis (IPF) is an incurable disease with poor prognosis and unknown etiology. The poor clinical outcome is associated with enhanced microbial burden in bronchoalveolar lavage fluid from IPF patients. However, whether microbes from the respiratory tract fluid cause the disease remains uncertain. Tissue-associated microbes can influence host physiology in health and disease development. The aim of this study was to evaluate the existence of microbes in lung fibrotic tissues. We evaluated the microbial community in lung tissues from IPF and from human transforming growth factor-β1 (TGF-β1) transgenic mice with lung fibrosis by oligotyping. We also evaluated the microbial population in non-tumor-bearing tissues from surgical specimens of lung cancer patients. The phyla Firmicutes and the genus Clostridium tended to be predominant in the lung tissue from IPF and lung cancer patients. Oligotyping analysis revealed a predominance of bacteria belonging to the genera Halomonas, Shewanella, Christensenella, and Clostridium in lung tissue from IPF and lung cancer. Evaluation of the microbial community in the lung tissue from mice revealed abundance of Proteobacteria in both wild-type (WT) littermates and transgenic mice. However, the genus Halomonas tended to be more abundant in TGF-β1 transgenic mice compared to WT mice. In conclusion, this study describes tissue-associated microbes in lung fibrotic tissues from IPF patients and from aging TGF-β1 transgenic mice.

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing

Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis since synovial fluid cultures are not universally positive and since synovial fluid is easily obtained preoperatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Genus- and species-level analyses of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analyses yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analyses of the 60 culture-negative aseptic failure cases yielded 53 (88%) and 56 (93%) cases with insignificant findings and 7 (12%) and 4 (7%) with potential clinically significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases.

Clean Low-Biomass Procedures and Their Application to Ancient Ice Core Microorganisms

Microorganisms in glacier ice provide tens to hundreds of thousands of years archive for a changing climate and microbial responses to it. Analyzing ancient ice is impeded by technical issues, including limited ice, low biomass, and contamination. While many approaches have been evaluated and advanced to remove contaminants on ice core surfaces, few studies leverage modern sequencing to establish in silico decontamination protocols for glacier ice. Here we sought to apply such “clean” sampling techniques with in silico decontamination approaches used elsewhere to investigate microorganisms archived in ice at ∼41 (D41, ∼20,000 years) and ∼49 m (D49, ∼30,000 years) depth in an ice core (GS3) from the summit of the Guliya ice cap in the northwestern Tibetan Plateau. Four “background” controls were established – a co-processed sterile water artificial ice core, two air samples collected from the ice processing laboratories, and a blank, sterile water sample – and used to assess contaminant microbial diversity and abundances. Amplicon sequencing revealed 29 microbial genera in these controls, but quantitative PCR showed that the controls contained about 50–100-times less 16S DNA than the glacial ice samples. As in prior work, we interpreted these low-abundance taxa in controls as “contaminants” and proportionally removed them in silico from the GS3 ice amplicon data. Because of the low biomass in the controls, we also compared prokaryotic 16S DNA amplicons from pre-amplified (by re-conditioning PCR) and standard amplicon sequencing, and found the resulting microbial profiles to be repeatable and nearly identical. Ecologically, the contaminant-controlled ice microbial profiles revealed significantly different microorganisms across the two depths in the GS3 ice core, which is consistent with changing climate, as reported for other glacier ice samples. Many GS3 ice core genera, including Methylobacterium, Sphingomonas, Flavobacterium, Janthinobacterium, Polaromonas, and Rhodobacter, were also abundant in previously studied ice cores, which suggests wide distribution across glacier environments. Together these findings help further establish “clean” procedures for studying low-biomass ice microbial communities and contribute to a baseline understanding of microorganisms archived in glacier ice.