Contamination in Low Microbial Biomass Microbiome Studies: Issues and Recommendations

Bacterial signatures and their inflammatory potentials associated with prostate cancer

Chronic inflammation can create a microenvironment that can contribute to the formation of prostate pathologies. Far less well understood is the origin of inflammation in the prostate. One potential source is microbial infections of the prostate. This review summarizes recent findings regarding the presence of bacteria in the prostate and the dysbiosis of bacterial populations in the urinary tract and the gastrointestinal tract related to prostate cancer, thereby focusing on next-generation sequencing (NGS)-generated data. The current limitations regarding NGS-based detection methods and other difficulties in the quest for a microbial etiology for prostate cancer are discussed. We then focus on a few bacterial species, including Cutibacterium acnes and Escherichia coli that are often NGS-detected in prostatic tissue specimens, and discuss their possible contribution as initiator or enhancer of prostate inflammation and prostate carcinogenesis.

The composition of the perinatal intestinal microbiota in horse

The establishment of the intestinal microbiota is critical for the digestive and immune systems. We studied the early development of the rectal microbiota in horse, a hindgut fermenter, from birth until 7 days of age, by qPCR and 16S rRNA gene amplicon sequencing. To evaluate initial sources of the foal microbiota, we characterised dam fecal, vaginal and oral microbiotas. We utilised an amplicon sequence variant (ASV) pipeline to maximise resolution and reproducibility. Stringent ASV filtering based on prevalence and abundance in samples and controls purged contaminants while preserving intestinal taxa. Sampled within 20 minutes after birth, rectal meconium contained small amounts of diverse bacterial DNA, with a profile closer to mare feces than mouth. 24 hours after birth, rectum was colonised by Firmicutes and Proteobacteria, some foals dominated by single genera. At day 7, the rectal genera were still different from adult feces. The mare vaginal microbiota contributed to 24 h and 7 day microbiotas. It contained few lactobacilli, with Corynebacterium, Porphyromonas, Campylobacter and Helcococcus as the most abundant genera. In the oral mucosa, Gemella was extremely abundant. Our observations indicate that bacteria or bacterial components are present in the intestine immediately after birth, but the newborn microbiota changes rapidly.

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.

Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research

BACKGROUND

Aerosol microbiome research advances our understanding of bioaerosols, including how airborne microorganisms affect our health and surrounding environment. Traditional microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, which are challenging when studying low biomass air environments, and puts high requirements on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have consequently adopted various mitigation strategies, including long-duration sampling, sample pooling, and whole genome amplification, each associated with some inherent drawbacks/limitations.

RESULTS

Here, we demonstrate a new custom, multi-component DNA isolation method optimized for SMS-based aerosol microbiome research. The method achieves improved DNA yields from filter-collected air samples by isolating DNA from the entire filter extract, and ensures a more comprehensive microbiome representation by combining chemical, enzymatic and mechanical lysis. Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock microbial community and real-world air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway samples, we demonstrate that supernatant inclusion results in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall similar taxonomic composition but also identified differences that could bias the microbiome profile, emphasizing the importance of processing the entire filter extract.

CONCLUSIONS

By demonstrating and benchmarking a new DNA isolation method optimized for SMS-based aerosol microbiome research with both a mock microbial community and real-world air samples, this study contributes to improved selection, harmonization, and standardization of DNA isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity and using methods with well-defined performance characteristics. Taken together, the demonstrated performance characteristics suggest the new method could be used to improve the quality of SMS-based aerosol microbiome research in low biomass air environments.

DNA extraction approaches substantially influence the assessment of the human breast milk microbiome

In addition to providing nutritional and bioactive factors necessary for infant development, human breast milk contains bacteria that contribute to the establishment of commensal microbiota in the infant. However, the composition of this bacterial community differs considerably between studies. We hypothesised that bacterial DNA extraction methodology from breast milk samples are a substantial contributor to these inter-study differences. We tested this hypothesis by applying five widely employed methodologies to a mock breast milk sample and four individual human breast milk samples. Significant differences in DNA yield and purity were observed between methods (P < 0.05). Microbiota composition, assessed by 16S rRNA gene amplicon sequencing, also differed significantly with extraction methodology (P < 0.05), including in the contribution of contaminant signal. Concerningly, many of the bacterial taxa identified here as contaminants have been reported as components of the breast milk microbiome in other studies. These findings highlight the importance of using stringent, well-validated, DNA extraction methodologies for analysis of the breast milk microbiome, and exercising caution interpreting microbiota data from low-biomass contexts.

Integrative description of bisexual Paramacrobiotus experimentalis sp. nov. (Macrobiotidae) from republic of Madagascar (Africa) with microbiome analysis

In a moss samples collected on Madagascar two populations of Paramacrobiotus experimentalis sp. nov. were found. Paramacrobiotus experimentalis sp. nov. with the presence of a microplacoid and areolatus type of eggs is similar to Pam. danielae, Pam. garynahi, Pam. hapukuensis, Pam. peteri, Pam. rioplatensis and Pam. savai, but it differs from them by some morphological and morphometric characters of the eggs. The p-distance between two COI haplotypes of Pam. experimentalis sp. nov. was 0.17%. In turn, the ranges of uncorrected genetic p-distances of all Paramacrobiotus species available in GenBank was from 18.27% (for Pam. lachowskae) to 25.26% (for Pam. arduus) with an average distance of 20.67%. We also found that Pam. experimentalis sp. nov. is bisexual. This observation was congruent on three levels: (i) morphological - specimen size dimorphism; (ii) structural (primary sexual characteristics) - females have an unpaired ovary while males have an unpaired testis and (iii) molecular - heterozygous and homozygous strains of the ITS-2 marker. Although symbiotic associations of hosts with bacteria (including endosymbiotic bacteria) are common in nature and these interactions exert various effects on the evolution, biology and reproductive ecology of hosts, there is still very little information on the bacterial community associated with tardigrades. To fill this gap and characterise the bacterial community of Pam. experimentalis sp. nov. populations and microbiome of its microhabitat, high throughput sequencing of the V3-V4 hypervariable regions in the bacterial 16S rRNA gene fragment was performed. The obtained 16S rRNA gene sequences ranged from 92,665 to 131,163. In total, 135 operational taxonomic units (OTUs) were identified across the rarefied dataset. Overall, both Pam. experimentalis sp. nov. populations were dominated by OTUs ascribed to the phylum Proteobacteria (89-92%) and Firmicutes (6-7%). In the case of samples from tardigrades' laboratory habitat, the most abundant bacterial phylum was Proteobacteria (51-90%) and Bacteroides (9-48%). In all compared microbiome profiles, only 16 of 137 OTUs were shared. We found also significant differences in beta diversity between the partly species-specific microbiome of Pam. experimentalis sp. nov. and its culturing environment. Two OTUs belonging to a putative bacterial endosymbiont were identified - Rickettsiales and Polynucleobacter. We also demonstrated that each bacterial community was rich in genes involved in membrane transport, amino acid metabolism, and carbohydrate metabolism.

Ear mite infection is associated with altered microbial communities in genetically depauperate Santa Catalina Island foxes (Urocyon littoralis catalinae)

The host-associated microbiome is increasingly recognized as a critical player in health and immunity. Recent studies have shown that disruption of commensal microbial communities can contribute to disease pathogenesis and severity. Santa Catalina Island foxes (Urocyon littoralis catalinae) present a compelling system in which to examine microbial dynamics in wildlife due to their depauperate genomic structure and extremely high prevalence of ceruminous gland tumors. Although the precise cause is yet unknown, infection with ear mites (Otodectes cynotis) has been linked to chronic inflammation, which is associated with abnormal cell growth and tumor development. Given the paucity of genomic variation in these foxes, other dimensions of molecular diversity, such as commensal microbes, may be critical to host response and disease pathology. We characterized the host-associated microbiome across six body sites of Santa Catalina Island foxes, and performed differential abundance testing between healthy and mite-infected ear canals. We found that mite infection was significantly associated with reduced microbial diversity and evenness, with the opportunistic pathogen Staphylococcus pseudintermedius dominating the ear canal community. These results suggest that secondary bacterial infection may contribute to the sustained inflammation associated with tumor development. As the emergence of antibiotic resistant strains remains a concern of the medical, veterinary, and conservation communities, uncovering high relative abundance of S. pseudintermedius provides critical insight into the pathogenesis of this complex system. Through use of culture-independent sequencing techniques, this study contributes to the broader effort of applying a more inclusive understanding of molecular diversity to questions within wildlife disease ecology.

Clinical metagenomics for infectious corneal ulcers: Rags to riches?

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

Understanding and interpreting community sequencing measurements of the vaginal microbiome

Community-wide high-throughput sequencing has transformed the study of the vaginal microbiome, and clinical applications are on the horizon. Here we outline the three main community sequencing methods: (1) amplicon sequencing, (2) shotgun metagenomic sequencing, and (3) metatranscriptomic sequencing. We discuss the advantages and limitations of community sequencing generally, and the unique strengths and weaknesses of each method. We briefly review the contributions of community sequencing to vaginal microbiome research and practice. We develop suggestions for critically interpreting research results and potential clinical applications based on community sequencing of the vaginal microbiome. TWEETABLE ABSTRACT: We review the advantages and limitations of amplicon sequencing, metagenomics, and metatranscriptomics methods for the study of the vaginal microbiome.

A Calcium-Rich Multimineral Intervention to Modulate Colonic Microbial Communities and Metabolomic Profiles in Humans: Results from a 90-Day Trial

Aquamin is a calcium-, magnesium-, and multiple trace element-rich natural product with colon polyp prevention efficacy based on preclinical studies. The goal of this study was to determine the effects of Aquamin on colonic microbial community and attendant metabolomic profile. Thirty healthy human participants were enrolled in a 90-day trial in which Aquamin (delivering 800 mg of calcium per day) was compared with calcium alone or placebo. Before and after the intervention, colonic biopsies and stool specimens were obtained. All 30 participants completed the study without serious adverse event or change in liver and renal function markers. Compared with pretreatment values, intervention with Aquamin led to a reduction in total bacterial DNA (P = 0.0001) and a shift in the microbial community measured by thetaYC (θYC; P = 0.0087). Treatment with calcium also produced a decline in total bacteria, but smaller than seen with Aquamin, whereas no reduction was observed with placebo in the colon. In parallel with microbial changes, a reduction in total bile acid levels (P = 0.0375) and a slight increase in the level of the short-chain fatty acid (SCFA) acetate in stool specimens (P < 0.0001) from Aquamin-treated participants were noted. No change in bile acids or SCFAs was observed with calcium or placebo. We conclude that Aquamin is safe and tolerable in healthy human participants and may produce beneficial alterations in the colonic microbial community and the attendant metabolomic profile. Because the number of participants was small, the findings should be considered preliminary.

Capturing the Resistome: a Targeted Capture Method To Reveal Antibiotic Resistance Determinants in Metagenomes

Identification of the nucleotide sequences encoding antibiotic resistance elements and determination of their association with antibiotic resistance are critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, both of which are heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the sequences in the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2,000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probe set on DNA libraries generated from multidrug-resistant bacteria to selectively capture resistance genes reproducibly produced higher numbers of reads on target at a greater length of coverage than shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables a sensitive means of gene detection in diverse environments where genes encoding antibiotic resistance represent less than 0.1% of the metagenome.

The subway microbiome: seasonal dynamics and direct comparison of air and surface bacterial communities

BACKGROUND

Mass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats.

METHODS

We performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses.

RESULTS

There were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature.

CONCLUSIONS

The results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world. Video abstract.

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.

Spatial structure of the microbiome in the gut of Pomacea canaliculata

Background

Gut microbes can contribute to their hosts in food digestion, nutrient absorption, and inhibiting the growth of pathogens. However, only limited studies have focused on the gut microbiota of freshwater snails. Pomacea canaliculata is considered one of the worst invasive alien species in the world. Elucidating the diversity and composition of the microbiota in the gut of P. canaliculata snails may be helpful for better understanding the widespread invasion of this snail species. In this study, the buccal masses, stomachs, and intestines were isolated from seven P. canaliculata snails. The diversity and composition of the microbiota in the three gut sections were then investigated based on high-throughput Illumina sequencing targeting the V3-V4 regions of the 16S rRNA gene.

Results

The diversity of the microbiota was highest in the intestine but lowest in the buccal mass. A total of 29 phyla and 111 genera of bacteria were identified in all of the samples. In general, Ochrobactrum, a genus of putative cellulose-degrading bacteria, was the most abundant (overall relative abundance: 13.6%), followed by Sediminibacterium (9.7%), Desulfovibrio (7.8%), an unclassified genus in the family Aeromonadaceae (5.4%), and Cloacibacterium (5.4%). The composition of the microbiota was diverse among the different gut sections. Ochrobactrum (relative abundance: 23.15% ± 7.92%) and Sediminibacterium (16.95 ± 5.70%) were most abundant in the stomach, an unclassified genus in the family Porphyromonadaceae (14.28 ± 7.29%) and Leptotrichia (8.70 ± 4.46%) were highest in the buccal mass, and two genera in the families Aeromonadaceae (7.55 ± 4.53%) and Mollicutes (13.47 ± 13.03%) were highest in the intestine.

Conclusions

The diversity and composition of the microbiome vary among different gut sections of P. canaliculata snails. Putative cellulose-degrading bacteria are enriched in the gut of P. canaliculata.

Guidelines for Transparency on Gut Microbiome Studies in Essential and Experimental Hypertension

Hypertension is a complex and modifiable condition in which environmental factors contribute to both onset and progression. Recent evidence has accumulated for roles of diet and the gut microbiome as environmental factors in blood pressure regulation. However, this is complex because gut microbiomes are a unique feature of each individual reflecting that individual’s developmental and environmental history creating caveats for both experimental models and human studies. Here, we describe guidelines for conducting gut microbiome studies in experimental and clinical hypertension. We provide a complete guide for authors on proper design, analyses, and reporting of gut microbiota/microbiome and metabolite studies and checklists that can be used by reviewers and editors to support robust reporting and interpretation. We discuss factors that modulate the gut microbiota in animal (eg, cohort, controls, diet, developmental age, housing, sex, and models used) and human studies (eg, blood pressure measurement and medication, body mass index, demographic characteristics including age, cultural identification, living structure, sex and socioeconomic environment, and exclusion criteria). We also provide best practice advice on sampling, storage of fecal/cecal samples, DNA extraction, sequencing methods (including metagenomics and 16S rRNA), and computational analyses. Finally, we discuss the measurement of short-chain fatty acids, metabolites produced by the gut microbiota, and interpretation of data. These guidelines should support better transparency, reproducibility, and translation of findings in the field of gut microbiota/microbiome in hypertension and cardiovascular disease.

Investigation of direct and indirect transfer of microbiomes between individuals

The human microbiome encompasses the fungi, bacteria and viruses that live on, within, and immediately surrounding the body. Microbiomes have potential utility in forensic science as an evidentiary tool to link or exclude persons of interest associated with criminal activities. Research has shown the microbiome is individualised, and that personal microbial signatures can be recovered from surfaces such as phones, shoes and fabrics. Before the human microbiome may be used as an investigative tool, further research is required to investigate the utility and potential limitations surrounding microbial profiling. This includes the detectability of microbial transfer between individuals or items, the associated risks (such as contamination events) and the applicability of microbial profiling for forensic purposes. This research aimed to identify whether an individual's distinguishable microbiome could be transferred to another individual and onto substrates, and vice versa. Paper, cotton, and glass surfaces were chosen to represent a range of substrate matrices. The study involved six participants placed into three pairs; participants took part in two modes of transfer. Transfer Mode 1 involved the pair shaking hands, followed by rubbing a substrate in their right hand. Transfer Mode 2 involved individuals rubbing a substrate in their left hand, swapping substrates with their partner and then rubbing the swapped substrate in their left hand. 16S rRNA sequencing was performed on the extracted microbial DNA from participant and substrate samples. Quantitative Insights into Microbial Ecology 2 (QIIME 2) was used for sequence quality control and beta (between-sample) diversity analyses and taxonomic assignment. Principal Coordinate Analysis (PCoA) based on Jaccard distances was visualised through Emperor software to determine the phylogenetic similarity of bacterial communities between participants and among participant pairs. Statistical testing through PERMANOVA revealed significant differences in the Jaccard distances between each participant pair (P < 0.001), highlighting not only the potential distinguishability of skin microbiomes among individuals, but also the clustering effect observed between participant pairs due to the potential transfer of hand-associated microbiomes between individuals. The study demonstrated that transfer of the human skin microbiome had occurred between all participant pairs, regardless of substrate type or mode of transfer.

Re-assessing microbiomes in the low-biomass reproductive niche

The female reproductive tract represents a continuum between the vagina and the upper genital tract. New evidence from cultivation-independent studies suggests that the female upper genital tract is not sterile; however, the significance of this for reproductive health and disease remains to be elucidated fully. Further, diagnosis and treatment of infectious reproductive tract pathologies using cultivation-independent technologies represents a largely unchartered area of modern medical science. The challenge now is to design well-controlled experiments to account for the ease of contamination known to confound molecular-based studies of low-biomass niches, including the uterus and placenta. This will support robust assessment of the potential function of microorganisms, microbial metabolites, and cell-free bacterial DNA on reproductive function in health and disease. TWEETABLE ABSTRACT: Molecular microbial studies of low-biomass niches require stringent experimental controls to reveal causal relations in reproductive health and disease.

Progressive Multifocal Leukoencephalopathy Diagnosed by Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid in an HIV Patient

Metagenomic next-generation sequencing (mNGS) is a novel approach to identify pathogens undetected by conventional methods. Herein, we report a case in which mNGS was used to identify JC virus from the cerebrospinal fluid sample of an HIV positive patient with progressive multifocal leukoencephalopathy (PML).

Lower Circulating Branched-Chain Amino Acid Concentrations Among Vegetarians are Associated with Changes in Gut Microbial Composition and Function

SCOPE

Vegetarian diets confer health benefits to many cardiometabolic diseases, although whether and how gut microbiota in vegetarians contributes to host metabolism remains unclear. Thus, the aim is to explore the possible links between the gut microbiota and circulating gut microbiota-host co-metabolites among vegetarians and omnivores.

METHODS AND RESULTS

Fecal and serum samples from 36 adults following a vegan, lacto-ovo vegetarian, or omnivorous diet are collected. A 16S rRNA gene, metagenome, metatranscriptome, and metabolome integrated multi-omics approach is adopted to profile fecal microbial composition and functionality and circulating gut microbiota-host co-metabolites. 16S rRNA gene and metagenomic sequencing suggest a significant difference in gut microbial composition between the two vegetarian groups and the omnivorous group at the family, genus, and species level. Metabolomic analysis reveals that circulating branched-chain amino acids (BCAAs)-valine, leucine, and isoleucine-are significantly lower in the two vegetarian groups than those in the omnivorous group. In line with the lower concentrations of BCAAs, metatranscriptomic analysis shows that the gut microbial pathway for the degradation of BCAAs is significantly upregulated among vegetarians compared with the omnivores.

CONCLUSIONS

The results indicate that gut microbiota plays an important role in the modulation of circulating BCAAs among vegetarians.

The seminal microbiome in health and disease

Owing to the fact that there are more microbial than human cells in our body and that humans contain more microbial than human genes, the microbiome has huge potential to influence human physiology, both in health and in disease. The use of next-generation sequencing technologies has helped to elucidate functional, quantitative and mechanistic aspects of the complex microorganism-host interactions that underlie human physiology and pathophysiology. The microbiome of semen is a field of increasing scientific interest, although this microbial niche is currently understudied compared with other areas of microbiome research. However, emerging evidence is beginning to indicate that the seminal microbiome has important implications for the reproductive health of men, the health of the couple and even the health of offspring, owing to transfer of microorganisms to the partner and offspring. As this field expands, further carefully designed and well-powered studies are required to unravel the true nature and role of the seminal microbiome.

Abundance-occupancy distributions to prioritize plant core microbiome membership

Core microbiome members are consistent features of a dataset that are hypothesized to reflect underlying functional relationships with the host. A review of the recent plant-microbiome literature reveals a variety of study-specific approaches used to define the core, which presents a challenge to building a general plant-microbiome framework. Abundance-occupancy distributions, used in macroecology to describe changes in community diversity over space, offer an ecological approach for prioritizing core membership for both spatial and temporal studies. Additionally, neutral models fit to the abundance-occupancy distributions can provide insights into deterministically selected core members. We provide examples and code to systematically explore a core plant microbiome from abundance-occupancy distributions. Though we focus on examples from and discussions relevant to the plant microbiome, the abundance-occupancy method can be widely and generally applied to prioritize core membership for any microbiome.

Validating DNA Extraction Protocols for Bentonite Clay

Bentonite clay is an integral component of the engineered barrier system of deep geological repositories (DGRs) that are planned for the long-term storage of high-level radioactive waste. Although nucleic acid extraction and analysis can provide powerful qualitative and quantitative data reflecting the presence, abundance, and functional potential of microorganisms within DGR materials, extraction of microbial DNA from bentonite clay is challenging due to the low biomass and adsorption of nucleic acids to the charged clay matrix. In this study, we used quantitative PCR, gel fingerprinting, and high-throughput sequencing of 16S rRNA gene amplicons to assess DNA extraction efficiency from natural MX-80 bentonite and the same material "spiked" with Escherichia coli genomic DNA. Extraction protocols were tested without additives and with casein and phosphate as blocking agents. Although we demonstrate improved DNA recovery by blocking agents at relatively high DNA spiking concentrations, at relatively low spiking concentrations, we detected a high proportion of contaminant nucleic acids from blocking agents that masked sample-specific microbial profile data. Because bacterial genomic DNA associated with casein preparations was insufficiently removed by UV treatment, casein is not recommended as an additive for DNA extractions from low-biomass samples. Instead, we recommend a kit-based extraction protocol for bentonite clay without additional blocking agents, as tested here and validated with multiple MX-80 bentonite samples, ensuring relatively high DNA recoveries with minimal contamination.IMPORTANCE Extraction of microbial DNA from MX-80 bentonite is challenging due to low biomass and adsorption of nucleic acid molecules to the charged clay matrix. Blocking agents improve DNA recovery, but their impact on microbial community profiles from low-biomass samples has not been characterized well. In this study, we evaluated the effect of casein and phosphate as blocking agents for quantitative recovery of nucleic acids from MX-80 bentonite. Our data justify a simplified framework for analyzing microbial community DNA associated with swelling MX-80 bentonite samples within the context of a deep geological repository for used nuclear fuel. This study is among the first to demonstrate successful extraction of DNA from Wyoming MX-80 bentonite.

Studying the gut virome in the metagenomic era: challenges and perspectives

The human gut harbors a complex ecosystem of microorganisms, including bacteria and viruses. With the rise of next-generation sequencing technologies, we have seen a quantum leap in the study of human-gut-inhabiting bacteria, yet the viruses that infect these bacteria, known as bacteriophages, remain underexplored. In this review, we focus on what is known about the role of bacteriophages in human health and the technical challenges involved in studying the gut virome, of which they are a major component. Lastly, we discuss what can be learned from studies of bacteriophages in other ecosystems.

Comparison of DNA Extraction Methods for Optimal Recovery of Metagenomic DNA from Human and Environmental Samples

Metagenomics is the study of gene pool of an entire community in a particular niche. This provides valuable information about the functionality of host-microbe interaction in a biological ecosystem. Efficient metagenomic DNA extraction is a critical pre-requisite for a successful sequencing run in a metagenomic study. Although isolation of human stool metagenomic DNA is fairly standardized, the same protocol does not work as efficiently in fecal DNA from other organisms. In this study, we report a comparison of manual and commercial DNA extraction methods for diverse samples such as human stool, fish gut and soil. Fishes are known to have variable microbial diversity based on their food habits, so the study included two different varieties of fishes. A modified protocol for effective isolation of metagenomic DNA from human milk samples is also reported, highlighting critical precautions. Recent studies have emphasized the importance of studying functionality of human milk metagenome to understand its influence on infants' health. While manual method works well with most samples and therefore can be a method of choice for testing new samples, broad-range commercial kit offers advantage of high purity and quality. DNA extraction of different samples would go a long way in unraveling the unexplored association between microbes and host in a biological system.

DNA extraction for human microbiome studies: the issue of standardization

Among the laboratory and bioinformatic processing steps for human microbiome studies, a lack of consistency in DNA extraction methodologies is hindering the ability to compare results between studies and sometimes leading to errant conclusions. The purpose of this article is to highlight the issues related to DNA extraction methods and to suggest minimum standard requirements that should be followed to ensure consistency and reproducibility.

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

Consistent and correctable bias in metagenomic sequencing experiments

Marker-gene and metagenomic sequencing have profoundly expanded our ability to measure biological communities. But the measurements they provide differ from the truth, often dramatically, because these experiments are biased toward detecting some taxa over others. This experimental bias makes the taxon or gene abundances measured by different protocols quantitatively incomparable and can lead to spurious biological conclusions. We propose a mathematical model for how bias distorts community measurements based on the properties of real experiments. We validate this model with 16S rRNA gene and shotgun metagenomics data from defined bacterial communities. Our model better fits the experimental data despite being simpler than previous models. We illustrate how our model can be used to evaluate protocols, to understand the effect of bias on downstream statistical analyses, and to measure and correct bias given suitable calibration controls. These results illuminate new avenues toward truly quantitative and reproducible metagenomics measurements.

Consistent and correctable bias in metagenomic sequencing experiments

Marker-gene and metagenomic sequencing have profoundly expanded our ability to measure biological communities. But the measurements they provide differ from the truth, often dramatically, because these experiments are biased toward detecting some taxa over others. This experimental bias makes the taxon or gene abundances measured by different protocols quantitatively incomparable and can lead to spurious biological conclusions. We propose a mathematical model for how bias distorts community measurements based on the properties of real experiments. We validate this model with 16S rRNA gene and shotgun metagenomics data from defined bacterial communities. Our model better fits the experimental data despite being simpler than previous models. We illustrate how our model can be used to evaluate protocols, to understand the effect of bias on downstream statistical analyses, and to measure and correct bias given suitable calibration controls. These results illuminate new avenues toward truly quantitative and reproducible metagenomics measurements.

Challenges in the construction of knowledge bases for human microbiome-disease associations

The last few years have seen tremendous growth in human microbiome research, with a particular focus on the links to both mental and physical health and disease. Medical and experimental settings provide initial sources of information about these links, but individual studies produce disconnected pieces of knowledge bounded in context by the perspective of expert researchers reading full-text publications. Building a knowledge base (KB) consolidating these disconnected pieces is an essential first step to democratize and accelerate the process of accessing the collective discoveries of human disease connections to the human microbiome. In this article, we survey the existing tools and development efforts that have been produced to capture portions of the information needed to construct a KB of all known human microbiome-disease associations and highlight the need for additional innovations in natural language processing (NLP), text mining, taxonomic representations, and field-wide vocabulary standardization in human microbiome research. Addressing these challenges will enable the construction of KBs that help identify new insights amenable to experimental validation and potentially clinical decision support.

Improved single-swab sample preparation for recovering bacterial and phage DNA from human skin and wound microbiomes

Background

Characterization of the skin and wound microbiome is of high biomedical interest, but is hampered by the low biomass of typical samples. While sample preparation from other microbiomes (e.g., gut) has been the subject of extensive optimization, procedures for skin and wound microbiomes have received relatively little attention. Here we describe an improved method for obtaining both phage and microbial DNA from a single skin or wound swab, characterize the yield of DNA in model samples, and demonstrate the utility of this approach with samples collected from a wound clinic.

Results

We find a substantial improvement when processing wound samples in particular; while only one-quarter of wound samples processed by a traditional method yielded sufficient DNA for downstream analysis, all samples processed using the improved method yielded sufficient DNA. Moreover, for both skin and wound samples, community analysis and viral reads obtained through deep sequencing of clinical swab samples showed significant improvement with the use of the improved method.

Conclusion

Use of this method may increase the efficiency and data quality of microbiome studies from low-biomass samples.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1586-4) contains supplementary material, which is available to authorized users.

Evolutionary and ecological consequences of gut microbial communities

Animals are distinguished by having guts: organs that must extract nutrients from food while barring invasion by pathogens. Most guts are colonized by non-pathogenic microorganisms, but the functions of these microbes, or even the reasons why they occur in the gut, vary widely among animals. Sometimes these microorganisms have co-diversified with hosts; sometimes they live mostly elsewhere in the environment. Either way, gut microorganisms often benefit hosts. Benefits may reflect evolutionary "addiction" whereby hosts incorporate gut microorganisms into normal developmental processes. But benefits often include novel ecological capabilities; for example, many metazoan clades exist by virtue of gut communities enabling new dietary niches. Animals vary immensely in their dependence on gut microorganisms, from lacking them entirely, to using them as food, to obligate dependence for development, nutrition, or protection. Many consequences of gut microorganisms for hosts can be ascribed to microbial community processes and the host's ability to shape these processes.

Microbial translocation into amniotic fluid of vervet monkeys is common and unrelated to adverse infant outcomes

Amniotic fluid was collected from pregnant female African green monkeys (n = 20). Analyses indicate microbial translocation into amniotic fluid during pregnancy is typical, and microbial load reduces across gestation. Microbial translocation does not relate to infant outcome or maternal factors. Lastly, we demonstrate that sample contamination is easily introduced and detectable.

Crypt- and Mucosa-Associated Core Microbiotas in Humans and Their Alteration in Colon Cancer Patients

Due to the huge number of bacteria constituting the human colon microbiota, alteration in the balance of its constitutive taxa (i.e., dysbiosis) is highly suspected of being involved in colorectal oncogenesis. Indeed, bacterial signatures in association with CRC have been described. These signatures may vary if bacteria are identified in feces or in association with tumor tissues. Here, we show that bacteria colonize human colonic crypts in tissues obtained from patients with CRC and with normal colonoscopy results. Aerobic nonfermentative Proteobacteria previously identified as constitutive of the crypt-specific core microbiota in murine colonic samples are similarly prevalent in human colonic crypts in combination with other anaerobic taxa. We also show that bacterial signatures characterizing the crypts of colonic tumors vary depending whether right-side or left-side tumors are analyzed.

We have previously identified a crypt-specific core microbiota (CSCM) in the colons of healthy laboratory mice and related wild rodents. Here, we confirm that a CSCM also exists in the human colon and appears to be altered during colon cancer. The colonic microbiota is suggested to be involved in the development of colorectal cancer (CRC). Because the microbiota identified in fecal samples from CRC patients does not directly reflect the microbiota associated with tumor tissues themselves, we sought to characterize the bacterial communities from the crypts and associated adjacent mucosal surfaces of 58 patients (tumor and normal homologous tissue) and 9 controls with normal colonoscopy results. Here, we confirm that bacteria colonize human colonic crypts in both control and CRC tissues, and using laser-microdissected tissues and 16S rRNA gene sequencing, we further show that right and left crypt- and mucosa-associated bacterial communities are significantly different. In addition to Bacteroidetes and Firmicutes, and as with murine proximal colon crypts, environmental nonfermentative Proteobacteria are found in human colonic crypts. Fusobacterium and Bacteroides fragilis are more abundant in right-side tumors, whereas Parvimonas micra is more prevalent in left-side tumors. More precisely, Fusobacterium periodonticum is more abundant in crypts from cancerous samples in the right colon than in associated nontumoral samples from adjacent areas but not in left-side colonic samples. Future analysis of the interaction between these bacteria and the crypt epithelium, particularly intestinal stem cells, will allow deciphering of their possible oncogenic potential.

Full-length 16S rRNA gene classification of Atlantic salmon bacteria and effects of using different 16S variable regions on community structure analysis

Understanding fish-microbial relationships may be of great value for fish producers as fish growth, development and welfare are influenced by the microbial community associated with the rearing systems and fish surfaces. Accurate methods to generate and analyze these microbial communities would be an important tool to help improve understanding of microbial effects in the industry. In this study, we performed taxonomic classification and determination of operational taxonomic units on Atlantic salmon microbiota by taking advantage of full-length 16S rRNA gene sequences. Skin mucus was dominated by the genera Flavobacterium and Psychrobacter. Intestinal samples were dominated by the genera Carnobacterium, Aeromonas, Mycoplasma and by sequences assigned to the order Clostridiales. Applying Sanger sequencing on the full-length bacterial 16S rRNA gene from the pool of 46 isolates obtained in this study showed a clear assignment of the PacBio full-length bacterial 16S rRNA gene sequences down to the genus level. One of the bottlenecks in comparing microbial profiles is that different studies use different 16S rRNA gene regions. Comparisons of sequence assignments between full-length and in silico derived variable 16S rRNA gene regions showed different microbial profiles with variable effects between phylogenetic groups and taxonomic ranks.

Quantifying and Understanding Well-to-Well Contamination in Microbiome Research

Microbial sequences inferred as belonging to one sample may not have originated from that sample. Such contamination may arise from laboratory or reagent sources or from physical exchange between samples. This study seeks to rigorously assess the behavior of this often-neglected between-sample contamination. Using unique bacteria, each assigned a particular well in a plate, we assess the frequency at which sequences from each source appear in other wells. We evaluate the effects of different DNA extraction methods performed in two laboratories using a consistent plate layout, including blanks and low-biomass and high-biomass samples. Well-to-well contamination occurred primarily during DNA extraction and, to a lesser extent, in library preparation, while barcode leakage was negligible. Laboratories differed in the levels of contamination. Extraction methods differed in their occurrences and levels of well-to-well contamination, with plate methods having more well-to-well contamination and single-tube methods having higher levels of background contaminants. Well-to-well contamination occurred primarily in neighboring samples, with rare events up to 10 wells apart. This effect was greatest in samples with lower biomass and negatively impacted metrics of alpha and beta diversity. Our work emphasizes that sample contamination is a combination of cross talk from nearby wells and background contaminants. To reduce well-to-well effects, samples should be randomized across plates, samples of similar biomasses should be processed together, and manual single-tube extractions or hybrid plate-based cleanups should be employed. Researchers should avoid simplistic removals of taxa or operational taxonomic units (OTUs) appearing in negative controls, as many will be microbes from other samples rather than reagent contaminants.IMPORTANCE Microbiome research has uncovered magnificent biological and chemical stories across nearly all areas of life science, at times creating controversy when findings reveal fantastic descriptions of microbes living and even thriving in what were once thought to be sterile environments. Scientists have refuted many of these claims because of contamination, which has led to robust requirements, including the use of controls, for validating accurate portrayals of microbial communities. In this study, we describe a previously undocumented form of contamination, well-to-well contamination, and show that this sort of contamination primarily occurs during DNA extraction rather than PCR, is highest with plate-based methods compared to single-tube extraction, and occurs at a higher frequency in low-biomass samples. This finding has profound importance in the field, as many current techniques to "decontaminate" a data set simply rely on an assumption that microbial reads found in blanks are contaminants from "outside," namely, the reagents or consumables.

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.

Microbiome analysis as a platform R&D tool for parasitic nematode disease management

The relationship between bacterial communities and their host is being extensively investigated for the potential to improve the host's health. Little is known about the interplay between the microbiota of parasites and the health of the infected host. Using nematode co-infection of lambs as a proof-of-concept model, the aim of this study was to characterise the microbiomes of nematodes and that of their host, enabling identification of candidate nematode-specific microbiota member(s) that could be exploited as drug development tools or for targeted therapy. Deep sequencing techniques were used to elucidate the microbiomes of different life stages of two parasitic nematodes of ruminants, Haemonchus contortus and Teladorsagia circumcincta, as well as that of the co-infected ovine hosts, pre- and post infection. Bioinformatic analyses demonstrated significant differences between the composition of the nematode and ovine microbiomes. The two nematode species also differed significantly. The data indicated a shift in the constitution of the larval nematode microbiome after exposure to the ovine microbiome, and in the ovine intestinal microbial community over time as a result of helminth co-infection. Several bacterial species were identified in nematodes that were absent from their surrounding abomasal environment, the most significant of which included Escherichia coli/Shigella. The ability to purposefully infect nematode species with engineered E. coli was demonstrated in vitro, validating the concept of using this bacterium as a nematode-specific drug development tool and/or drug delivery vehicle. To our knowledge, this is the first description of the concept of exploiting a parasite's microbiome for drug development and treatment purposes.

A new home for microbes

Modern microorganisms growing in fossils provide major challenges for researchers trying to detect ancient molecules in the same fossils.

Whole genome sequencing revealed microbiome in lung adenocarcinomas presented as ground-glass nodules

Background

Emerging evidence has suggested that dysbiosis of the microbiota may play vital roles in tumorigenesis. However, the interplay between the microbiome and lung cancer remains undetermined. In this study, we characterize the microbiome in the early stage of lung cancer, which presented as ground-glass nodules (GGNs).

Methods

We sequenced the whole genomes from 10 GGN lesions and 5 adjacent normal lung tissue samples. After being filtered with human genome sequences, the sequence reads were mapped to prokaryotic genomes refSeq and non-redundant protein database for taxa and gene functions profiling, respectively.

Results

Mycobacterium, Corynebacterium, and Negativicoccus were the core microbiota found in all GGNs and the normal tissue samples. The microbiota composition did not show significant difference between GGNs and normal tissues except the adenocarcinoma (AD) (P=0.047). A significant β diversity in microbiome gene functions was found among different patients. Two individual gene functions, the Secondary Metabolism (1.32 fold with P=0.01) and the Serine Threonine protein kinase (4.23 fold, P<0.001), were significantly increased in GGNs over normal tissue samples.

Conclusions

This study helps shed light on the implication of the microbiome in early stage lung cancer, which encourages the further study and development of innovative strategies for early prevention and treatment of lung cancer.

Not all animals need a microbiome

It is often taken for granted that all animals host and depend upon a microbiome, yet this has only been shown for a small proportion of species. We propose that animals span a continuum of reliance on microbial symbionts. At one end are the famously symbiont-dependent species such as aphids, humans, corals and cows, in which microbes are abundant and important to host fitness. In the middle are species that may tolerate some microbial colonization but are only minimally or facultatively dependent. At the other end are species that lack beneficial symbionts altogether. While their existence may seem improbable, animals are capable of limiting microbial growth in and on their bodies, and a microbially independent lifestyle may be favored by selection under some circumstances. There is already evidence for several ‘microbiome-free’ lineages that represent distantly related branches in the animal phylogeny. We discuss why these animals have received such little attention, highlighting the potential for contaminants, transients, and parasites to masquerade as beneficial symbionts. We also suggest ways to explore microbiomes that address the limitations of DNA sequencing. We call for further research on microbiome-free taxa to provide a more complete understanding of the ecology and evolution of macrobe-microbe interactions.

Contribution of the Mucosal Microbiota to Bovine Respiratory Health

Recognizing the respiratory tract as a dynamic and complex ecosystem has enhanced our understanding of the pathophysiology of bovine respiratory disease (BRD). There is widespread evidence showing that disease-predisposing factors often disrupt the respiratory microbial ecosystem, provoking atypical colonization patterns and a progressive dysbiosis. The ecological factors that shape the respiratory microbiota, and the influence of these complex communities on bovine respiratory health, are a rich area for research exploration. Here, we review the current status of understanding of the bovine respiratory microbiota, the factors that influence its development and stability, its role in maintaining mucosal homeostasis, and ultimately its contribution to bovine health and disease. Finally, we explore the limitations of current research approaches to the microbiome and discuss potential directions for future research that can help us better understand the role of the respiratory microbiota in the health, welfare, and productivity of livestock.

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.

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.

Towards precision quantification of contamination in metagenomic sequencing experiments

Metagenomic next-generation sequencing (mNGS) experiments involving small amounts of nucleic acid input are highly susceptible to erroneous conclusions resulting from unintentional sequencing of occult contaminants, especially those derived from molecular biology reagents. Recent work suggests that, for any given microbe detected by mNGS, an inverse linear relationship between microbial sequencing reads and sample mass implicates that microbe as a contaminant. By associating sequencing read output with the mass of a spike-in control, we demonstrate that contaminant nucleic acid can be quantified in order to identify the mass contributions of each constituent. In an experiment using a high-resolution (n = 96) dilution series of HeLa RNA spanning 3-logs of RNA mass input, we identified a complex set of contaminants totaling 9.1 ± 2.0 attograms. Given the competition between contamination and the true microbiome in ultra-low biomass samples such as respiratory fluid, quantification of the contamination within a given batch of biological samples can be used to determine a minimum mass input below which sequencing results may be distorted. Rather than completely censoring contaminant taxa from downstream analyses, we propose here a statistical approach that allows separation of the true microbial components from the actual contribution due to contamination. We demonstrate this approach using a batch of n = 97 human serum samples and note that despite E. coli contamination throughout the dataset, we are able to identify a patient sample with significantly more E. coli than expected from contamination alone. Importantly, our method assumes no prior understanding of possible contaminants, does not rely on any prior collection of environmental or reagent-only sequencing samples, and does not censor potentially clinically relevant taxa, thus making it a generalized approach to any kind of metagenomic sequencing, for any purpose, clinical or otherwise.