Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples

Temporal Stability and Composition of the Ocular Surface Microbiome

To determine if there is a core ocular surface microbiome and whether there are microbial community changes over time, the conjunctiva of 45 healthy subjects were sampled at three time points over three months and processed using culture-dependent and -independent methods. Contaminant taxa were removed using a linear regression model using taxa abundances in negative controls as predictor of taxa abundances in subject samples. Both cultured cell counts and sequencing indicated low microbial biomass on the ocular surface. No cultured species was found in all subjects at all times or in all subjects at any one time. After removal of contaminant taxa identified in negative controls using a statistical model, the most commonly detected taxon was Corynebacterium (11.1%). No taxa were found in all subjects at all times or in all subjects in any one time, but there were 26 taxa present in at least one or more subjects at all times including Corynebacterium and Streptococcus. The ocular surface contains a low diversity of microorganisms. Using culture dependent and independent methods, the ocular surface does not appear to support a substantial core microbiome. However, consistently present taxa could be observed within individuals suggesting the possibility of individual-specific core microbiomes.

Influence of lung CT changes in chronic obstructive pulmonary disease (COPD) on the human lung microbiome

BACKGROUND

Changes in microbial community composition in the lung of patients suffering from moderate to severe COPD have been well documented. However, knowledge about specific microbiome structures in the human lung associated with CT defined abnormalities is limited.

METHODS

Bacterial community composition derived from brush samples from lungs of 16 patients suffering from different CT defined subtypes of COPD and 9 healthy subjects was analyzed using a cultivation independent barcoding approach applying 454-pyrosequencing of 16S rRNA gene fragment amplicons.

RESULTS

We could show that bacterial community composition in patients with changes in CT (either airway or emphysema type changes, designated as severe subtypes) was different from community composition in lungs of patients without visible changes in CT as well as from healthy subjects (designated as mild COPD subtype and control group) (PC1, Padj = 0.002). Higher abundance of Prevotella in samples from patients with mild COPD subtype and from controls and of Streptococcus in the severe subtype cases mainly contributed to the separation of bacterial communities of subjects. No significant effects of treatment with inhaled glucocorticoids on bacterial community composition were detected within COPD cases with and without abnormalities in CT in PCoA. Co-occurrence analysis suggests the presence of networks of co-occurring bacteria. Four communities of positively correlated bacteria were revealed. The microbial communities can clearly be distinguished by their associations with the CT defined disease phenotype.

CONCLUSION

Our findings indicate that CT detectable structural changes in the lung of COPD patients, which we termed severe subtypes, are associated with alterations in bacterial communities, which may induce further changes in the interaction between microbes and host cells. This might result in a changed interplay with the host immune system.

The functional microbiome of arthropods

Many studies on the microbiome of animals have been reported but a comprehensive analysis is lacking. Here we present a meta-analysis on the microbiomes of arthropods and their terrestrial habitat, focusing on the functional profile of bacterial communities derived from metabolic traits that are essential for microbial life. We report a detailed analysis of probably the largest set of biochemically defined functional traits ever examined in microbiome studies. This work deals with the phylum proteobacteria, which is usually dominant in marine and terrestrial environments and covers all functions associated with microbiomes. The considerable variation in the distribution and abundance of proteobacteria in microbiomes has remained fundamentally unexplained. This analysis reveals discrete functional groups characteristic for adaptation to anaerobic conditions, which appear to be defined by environmental filtering of taxonomically related taxa. The biochemical diversification of the functional groups suggests an evolutionary trajectory in the structure of arthropods' microbiome, from metabolically versatile to specialized proteobacterial organisms that are adapted to complex environments such as the gut of social insects. Bacterial distribution in arthropods' microbiomes also shows taxonomic clusters that do not correspond to functional groups and may derive from other factors, including common contaminants of soil and reagents.

Optimizing methods and dodging pitfalls in microbiome research

Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

Insights of the dental calculi microbiome of pre-Columbian inhabitants from Puerto Rico

Background

The study of ancient microorganisms in mineralized dental plaque or calculi is providing insights into microbial evolution, as well as lifestyles and disease states of extinct cultures; yet, little is still known about the oral microbial community structure and function of pre-Columbian Caribbean cultures. In the present study, we investigated the dental calculi microbiome and predicted function of one of these cultures, known as the Saladoid. The Saladoids were horticulturalists that emphasized root-crop production. Fruits, as well as small marine and terrestrial animals were also part of the Saladoid diet.

Methods

Dental calculi samples were recovered from the archaeological site of Sorcé, in the municipal island of Vieques, Puerto Rico, characterized using 16S rRNA gene high-throughput sequencing, and compared to the microbiome of previously characterized coprolites of the same culture, as well modern plaque, saliva and stool microbiomes available from the Human Microbiome Project.

Results

Actinobacteria, Proteobacteria and Firmicutes comprised the majority of the Saladoid dental calculi microbiome. The Saladoid dental calculi microbiome was distinct when compared to those of modern saliva and dental plaque, but showed the presence of common inhabitants of modern oral cavities including Streptococcus sp., Veillonella dispar and Rothia mucilaginosa. Cell motility, signal transduction and biosynthesis of other secondary metabolites may be unique features of the Saladoid microbiome.

Discussion

Results suggest that the Saladoid dental calculi microbiome structure and function may possibly reflect a horticulturalist lifestyle and distinct dietary habits. Results also open the opportunity to further elucidate oral disease states in extinct Caribbean cultures and extinct indigenous cultures with similar lifestyles.

Role of the Gut Microbiome in the Pathogenesis of Obesity and Obesity-Related Metabolic Dysfunction

The potential role of intestinal microbiota in the etiology of various human diseases has attracted massive attention in the last decade. As such, the intestinal microbiota has been advanced as an important contributor in the development of obesity and obesity-related metabolic dysfunctions, amongst others. Experiments in animal models have produced evidence for a causal role of intestinal microbiota in the etiology of obesity and insulin resistance. However, with a few exceptions, such causal relation is lacking for humans and most publications merely report associations between intestinal microbial composition and metabolic disorders such as obesity and type 2 diabetes. Thus, the reciprocal relationship between the bacteria and these metabolic disorders remains a matter of debate. The main objective of this review is to critically assess the driving role of intestinal microbe composition in the etiology, prevention, and treatment of obesity and obesity-related metabolic dysfunction, including type 2 diabetes.

The blood DNA virome in 8,000 humans

The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

Novel sequencing technologies offer insight into the virome in human samples. Here, we identify the viral DNA sequences in blood of over 8,000 individuals undergoing whole genome sequencing. This approach serves to identify 94 viruses; however, many are shown to reflect widespread DNA contamination of commercial reagents or of environmental origin. While this represents a significant limitation to reliably identify novel viruses infecting humans, we could confidently detect sequences and quantify abundance of 19 human viruses in 42% of individuals. Ancestry, sex, and age were important determinants of viral prevalence. This large study calls attention on the challenge of interpreting next generation sequencing data for the identification of novel viruses. However, it serves to categorize the abundance of human DNA viruses using an unbiased technique.

Detection and Enumeration of Spore-Forming Bacteria in Powdered Dairy Products

With the abolition of milk quotas in the European Union in 2015, several member states including Ireland, Luxembourg, and Belgium have seen year on year bi-monthly milk deliveries to dairies increase by up to 35%. Milk production has also increased outside of Europe in the past number of years. Unsurprisingly, there has been a corresponding increased focus on the production of dried milk products for improved shelf life. These powders are used in a wide variety of products, including confectionery, infant formula, sports dietary supplements and supplements for health recovery. To ensure quality and safety standards in the dairy sector, strict controls are in place with respect to the acceptable quantity and species of microorganisms present in these products. A particular emphasis on spore-forming bacteria is necessary due to their inherent ability to survive extreme processing conditions. Traditional microbiological detection methods used in industry have limitations in terms of time, efficiency, accuracy, and sensitivity. The following review will explore the common spore-forming bacterial contaminants of milk powders, will review the guidelines with respect to the acceptable limits of these microorganisms and will provide an insight into recent advances in methods for detecting these microbes. The various advantages and limitations with respect to the application of these diagnostics approaches for dairy food will be provided. It is anticipated that the optimization and application of these methods in appropriate ways can ensure that the enhanced pressures associated with increased production will not result in any lessening of safety and quality standards.

Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons

The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, alpha- and beta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea.

The predominant site of bacterial translocation across the intestinal mucosal barrier occurs at the advancing disease margin in Crohn's disease

Crohn's disease is characterized by increased permeability of the intestinal mucosal barriers and an abnormal or dysregulated immune response to specific and/or commensal bacteria arising from the intestinal lumen. To determine the types of bacteria that are transgressing the mucosal barrier and colonizing the intestinal submucosal tissues, we performed 16S rRNA gene microbiota sequencing of the submucosal and mucosal tissues at the advancing disease margin in ileal Crohn's disease. Microbial populations were compared between mucosa and submucosa and non-inflammatory bowel disease (non-IBD) controls, as well as to microbial populations previously found at the centre of the disease lesion. There was no significant increase in bacteria within the submucosa of non-IBD controls at any taxonomic level when compared to the corresponding superjacent mucosa, indicating an effective mucosal barrier within the non-IBD population. In contrast, there was a statistically significant increase in 13 bacterial families and 16 bacterial genera within the submucosa at the advancing disease margin in Crohn's disease when compared to the superjacent mucosa. Major increases within the submucosa included bacteria of the Families Sphingomonadaceae, Alicyclobacillaceae, Methylobacteriaceae, Pseudomonadaceae and Prevotellaceae. Data suggest that the primary site of bacterial translocation across the mucosal barrier occurs at the margin between diseased and normal tissue, the advancing disease margin. The heterogeneity of the bacterial populations penetrating the mucosal barrier and colonizing the submucosal intestinal tissues and, therefore, contributing to the inflammatory processes, suggests that bacterial translocation is secondary to a primary event leading to a breakdown of the mucosal barrier.