Measuring the microbiome: perspectives on advances in DNA-based techniques for exploring microbial life

Evaluating Methods of Preserving Aquatic Invertebrates for Microbiome Analysis

Research on the microbiomes of animals has increased substantially within the past decades. More recently, microbial analyses of aquatic invertebrates have become of increased interest. The storage method used while collecting aquatic invertebrates has not been standardized throughout the scientific community, and the effects of common storage methods on the microbial composition of the organism is unknown. Using crayfish and dragonfly nymphs collected from a natural pond and crayfish maintained in an aquarium, the effects of two common storage methods, preserving in 95% ethanol and freezing at −20 °C, on the invertebrate bacterial microbiome was evaluated. We found that the bacterial community was conserved for two sample types (gut and exoskeleton) of field-collected crayfish stored either in ethanol or frozen, as was the gut microbiome of aquarium crayfish. However, there were significant differences between the bacterial communities found on the exoskeleton of aquarium crayfish stored in ethanol compared to those that were frozen. Dragonfly nymphs showed significant differences in gut microbial composition between species, but the microbiome was conserved between storage methods. These results demonstrate that preserving field-collected specimens of aquatic invertebrates in 95% ethanol is likely to be a simple and effective sample preservation method for subsequent gut microbiome analysis but is less reliable for the external microbiome.

Metagenomic landscape of taxonomy, metabolic potential and resistome of Sardinella longiceps gut microbiome

Fish gut microbiota, encompassing a colossal reserve of microbes represents a dynamic ecosystem, influenced by a myriad of environmental and host factors. The current study presents a comprehensive insight into Sardinella longiceps gut microbiome using whole metagenome shotgun sequencing. Taxonomic profiling identified the predominance of phylum Proteobacteria, comprising of Photobacterium, Vibrio and Shewanella sp. Functional annotation revealed the dominance of Clustering based subsystems, Carbohydrate, and Amino acids and derivatives. Analysis of Virulence, disease and defense subsystem identified genes conferring resistance to antibiotics and toxic compounds, like multidrug resistance efflux pumps and resistance genes for fluoroquinolones and heavy metals like cobalt, zinc, cadmium and copper. The presence of overlapping genetic mechanisms of resistance to antibiotics and heavy metals, like the efflux pumps is a serious cause of concern as it is likely to aggravate co-selection pressure, leading to an increased dissemination of these resistance genes to fish and humans.

Tracing seafood at high spatial resolution using NGS-generated data and machine learning: Comparing microbiome versus SNPs

Developing reliable tools to trace food origin represents a major goal for producers and control authorities. Here, we test the hypothesis whether NGS-generated data could provide a reliable tool to ensure seafood traceability. As a test case, we used the Manila clam Ruditapes philippinarum, a bivalve mollusk of high commercial interest with worldwide distribution, collected in the Venice lagoon sites subjected to prohibition of clam harvesting because of chemical contamination as well as in authorized clam harvesting areas. The results obtained demonstrated that the geographic origin of Manila clam may be more accurately determined basing on microbiome data than single nucleotide polymorphisms. In particular, combining microbiome data with machine-learning techniques, we provide the experimental evidence that it is possible to trace the clam place of origin at high spatial resolution. Considering its low cost and portability, NGS-analysis of microbiome data might represent a cost-effective, high-resolution tool for reliable food traceability.

Application of molecular tools to elucidate the microbiota of seafood

The aim of this review is to present the methodologies currently applied to identify microbiota and pathogens transmitted to humans through seafood consumption, focusing on molecular techniques and pointing out their importance, advantages, disadvantages and applicability. Knowledge of available techniques allows researchers to identify which technique best fits their expectations. With such discernment, it will be possible to infer which disadvantages will be present and, therefore, not interfering with the final result. Two methodologies can be employed for this purpose, dependent and independent cultures. However, the dependent culture has certain limitations that can be solved through the independent cultivation techniques, such as PCR, PFGE and NGS, especially through the sequencing of the 16S rRNA region, providing a complete view of microbial diversity. These have revolutionized microbiological knowledge, mainly because they allow for the identification of uncultivable micro-organisms, which represent a substantial portion of total micro-organisms, making it possible to elucidate not yet described taxa which may display pathogenic potential, besides quantifying microbial communities, microbiota genetics, translated proteins and produced metabolites. In addition, transcriptomic and metabolomic techniques also allow for the evaluation of possible impacts that microbial communities may create in their environment, as well as the determination of potential pathogenicity to humans.

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.

Gene Sequence Analyses of the Healthy Oral Microbiome in Humans and Companion Animals

It has long been accepted that certain oral bacterial species are responsible for the development of periodontal disease. However, the focus of microbial and immunological research is shifting from studying the organisms associated with disease to examining the indigenous microbial inhabitants that are present in health. Microbiome refers to the aggregate genetic material of all microorganisms living in, or on, a defined habitat. Recent developments in gene sequence analysis have enabled detection and identification of bacteria from polymicrobial samples, including subgingival plaque. Diversity surveys utilizing this technology have demonstrated that bacterial culture techniques have vastly underestimated the richness and diversity of microorganisms in vivo, since only certain bacteria grow in vitro. Surveys using gene sequence analysis have demonstrated that the healthy oral microbiome is composed of an unexpectedly high number of diverse species, including putative pathogens. These findings support the view that coevolution microorganisms and macroscopic hosts has occurred in which certain microorganisms have adapted to survive in the oral cavity and host immune tolerance has allowed the establishment of a symbiotic relationship in which both parties receive benefits (mutualism). This review describes gene sequence analysis as an increasingly common, culture-independent tool for detecting bacteria in vivo and describes the results of recent oral microbiome diversity surveys of clinically healthy humans, dogs, and cats. Six bacterial phyla consistently dominated the healthy oral microbiome of all 3 host species. Previous hypotheses on etiology of periodontitis are reviewed in light of new scientific findings. Finally, the consideration that clinically relevant periodontal disease occurs when immune tolerance of the symbiotic oral microbiome is altered to a proinflammatory response will be discussed.

Intestinal microbiome disruption in patients in a long-term acute care hospital: A case for development of microbiome disruption indices to improve infection prevention

BACKGROUND

Composition and diversity of intestinal microbial communities (microbiota) are generally accepted as a risk factor for poor outcomes; however, we cannot yet use this information to prevent adverse outcomes.

METHODS

Stool was collected from 8 long-term acute care hospital patients experiencing diarrhea and 2 fecal microbiota transplant donors; 16S rDNA V1-V2 hypervariable regions were sequenced. Composition and diversity of each sample were described. Stool was also tested for Clostridium difficile, vancomycin-resistant enterococci (VRE), and carbapenem-resistant Enterobacteriaceae. Associations between microbiota diversity and demographic and clinical characteristics, including antibiotic use, were analyzed.

RESULTS

Antibiotic exposure and Charlson Comorbidity Index were inversely correlated with diversity (Spearman = -0.7). Two patients were positive for VRE; both had microbiomes dominated by Enterococcus faecium, accounting for 67%-84% of their microbiome.

CONCLUSIONS

Antibiotic exposure correlated with diversity; however, other environmental and host factors not easily obtainable in a clinical setting are also known to impact the microbiota. Therefore, direct measurement of microbiome disruption by sequencing, rather than reliance on surrogate markers, might be most predictive of adverse outcomes. If and when microbiome characterization becomes a standard diagnostic test, improving our understanding of microbiome dynamics will allow for interpretation of results to improve patient outcomes.

Exploring the environmental diversity of kinetoplastid flagellates in the high-throughput DNA sequencing era

The class Kinetoplastea encompasses both free-living and parasitic species from a wide range of hosts. Several representatives of this group are responsible for severe human diseases and for economic losses in agriculture and livestock. While this group encompasses over 30 genera, most of the available information has been derived from the vertebrate pathogenic genera Leishmaniaand Trypanosoma. Recent studies of the previously neglected groups of Kinetoplastea indicated that the actual diversity is much higher than previously thought. This article discusses the known segment of kinetoplastid diversity and how gene-directed Sanger sequencing and next-generation sequencing methods can help to deepen our knowledge of these interesting protists.

Incidence of bloodstream infections in small bowel transplant recipients receiving selective decontamination of the digestive tract: A single-center experience

Pediatric patients undergoing small bowel transplantation are susceptible to postoperative CLABSI. SDD directed against enteric microbes is a strategy for reducing CLABSI. We hypothesized that SDD reduces the frequency of CLABSI, infections outside the bloodstream, and allograft rejection during the first 30 days following transplant. A retrospective chart review of 38 pediatric small bowel transplant recipients at CCHMC from 2003 to 2011 was conducted. SDD antimicrobials were oral colistin, tobramycin, and amphotericin B. The incidence of CLABSI, infections outside the bloodstream, and rejection episodes were compared between study periods. The incidence of CLABSI did not differ between study periods (6.9 CLABSI vs. 4.6 CLABSI per 1000 catheter days; p = 0.727), but gram positives and Candida predominated in the first 30 days. Incidence of bacterial infections outside the bloodstream did not differ (p = 0.227). Rejection occurred more frequently during the first month following transplant (p = 0.302). SDD does not alter the incidence of CLABSI, bacterial infections outside the bloodstream, or allograft rejection in the immediate 30 days post-transplantation. However, SDD does influence CLABSI organism types (favoring gram positives and Candida) and Candidal infections outside the bloodstream.

Environmental genes and genomes: understanding the differences and challenges in the approaches and software for their analyses

DNA-based taxonomic and functional profiling is widely used for the characterization of organismal communities across a rapidly increasing array of research areas that include the role of microbiomes in health and disease, biomonitoring, and estimation of both microbial and metazoan species richness. Two principal approaches are currently used to assign taxonomy to DNA sequences: DNA metabarcoding and metagenomics. When initially developed, each of these approaches mandated their own particular methods for data analysis; however, with the development of high-throughput sequencing (HTS) techniques they have begun to share many aspects in data set generation and processing. In this review we aim to define the current characteristics, goals and boundaries of each field, and describe the different software used for their analysis. We argue that an appreciation of the potential and limitations of each method can help underscore the improvements required by each field so as to better exploit the richness of current HTS-based data sets.

Influence of age, reproductive cycling status, and menstruation on the vaginal microbiome in baboons (Papio anubis)

The vaginal microbiome is believed to influence host health by providing protection from pathogens and influencing reproductive outcomes such as fertility and gestational length. In humans, age-associated declines in diversity of the vaginal microbiome occur in puberty and persist into adulthood. Additionally, menstruation has been associated with decreased microbial community stability. Adult female baboons, like other non-human primates (NHPs), have a different and highly diverse vaginal microbiome compared to that of humans, which is most commonly dominated by Lactobacillus spp. We evaluated the influence of age, reproductive cycling status (cycling vs. non-cycling) and menstruation on the vaginal microbiome of 38 wild-caught, captive female olive baboons (Papio anubis) by culture-independent sequencing of the V3-V5 region of the bacterial 16S rRNA gene. All baboons had highly diverse vaginal microbial communities. Adult baboons had significantly lower microbial diversity in comparison to subadult baboons, which was attributable to decreased relative abundance of minor taxa. No significant differences were detected based on cycling state or menstruation. Predictive metagenomic analysis showed uniformity in relative abundance of metabolic pathways regardless of age, cycle stage, or menstruation, indicating conservation of microbial community functions. This study suggests that selection of an optimal vaginal microbial community occurs at puberty. Since decreased diversity occurs in both baboons and humans at puberty, this may reflect a general strategy for selection of adult vaginal microbial communities. Comparative evaluation of vaginal microbial community development and composition may elucidate mechanisms of community formation and function that are conserved across host species or across microbial community types. These findings have implications for host health, evolutionary biology, and microbe-host ecosystems.

RNA shotgun metagenomic sequencing of northern California (USA) mosquitoes uncovers viruses, bacteria, and fungi

Mosquitoes, most often recognized for the microbial agents of disease they may carry, harbor diverse microbial communities that include viruses, bacteria, and fungi, collectively called the microbiota. The composition of the microbiota can directly and indirectly affect disease transmission through microbial interactions that could be revealed by its characterization in natural populations of mosquitoes. Furthermore, the use of shotgun metagenomic sequencing (SMS) approaches could allow the discovery of unknown members of the microbiota. In this study, we use RNA SMS to characterize the microbiota of seven individual mosquitoes (species include Culex pipiens, Culiseta incidens, and Ochlerotatus sierrensis) collected from a variety of habitats in California, USA. Sequencing was performed on the Illumina HiSeq platform and the resulting sequences were quality-checked and assembled into contigs using the A5 pipeline. Sequences related to single stranded RNA viruses of the Bunyaviridae and Rhabdoviridae were uncovered, along with an unclassified genus of double-stranded RNA viruses. Phylogenetic analysis finds that in all three cases, the closest relatives of the identified viral sequences are other mosquito-associated viruses, suggesting widespread host-group specificity among disparate viral taxa. Interestingly, we identified a Narnavirus of fungi, also reported elsewhere in mosquitoes, that potentially demonstrates a nested host-parasite association between virus, fungi, and mosquito. Sequences related to 8 bacterial families and 13 fungal families were found across the seven samples. Bacillus and Escherichia/Shigella were identified in all samples and Wolbachia was identified in all Cx. pipiens samples, while no single fungal genus was found in more than two samples. This study exemplifies the utility of RNA SMS in the characterization of the natural microbiota of mosquitoes and, in particular, the value of identifying all microbes associated with a specific host.

Current impact and future directions of high throughput sequencing in plant virus diagnostics

The ability to provide a fast, inexpensive and reliable diagnostic for any given viral infection is a key parameter in efforts to fight and control these ubiquitous pathogens. The recent developments of high-throughput sequencing (also called Next Generation Sequencing - NGS) technologies and bioinformatics have drastically changed the research on viral pathogens. It is now raising a growing interest for virus diagnostics. This review provides a snapshot vision on the current use and impact of high throughput sequencing approaches in plant virus characterization. More specifically, this review highlights the potential of these new technologies and their interplay with current protocols in the future of molecular diagnostic of plant viruses. The current limitations that will need to be addressed for a wider adoption of high-throughput sequencing in plant virus diagnostics are thoroughly discussed.

The complex exogenous RNA spectra in human plasma: an interface with human gut biota?

Human plasma has long been a rich source for biomarker discovery. It has recently become clear that plasma RNA molecules, such as microRNA, in addition to proteins are common and can serve as biomarkers. Surveying human plasma for microRNA biomarkers using next generation sequencing technology, we observed that a significant fraction of the circulating RNA appear to originate from exogenous species. With careful analysis of sequence error statistics and other controls, we demonstrated that there is a wide range of RNA from many different organisms, including bacteria and fungi as well as from other species. These RNAs may be associated with protein, lipid or other molecules protecting them from RNase activity in plasma. Some of these RNAs are detected in intracellular complexes and may be able to influence cellular activities under invitro conditions. These findings raise the possibility that plasma RNAs of exogenous origin may serve as signaling molecules mediating for example the human-microbiome interaction and may affect and/or indicate the state of human health.

Short-read reading-frame predictors are not created equal: sequence error causes loss of signal

Background

Gene prediction algorithms (or gene callers) are an essential tool for analyzing shotgun nucleic acid sequence data. Gene prediction is a ubiquitous step in sequence analysis pipelines; it reduces the volume of data by identifying the most likely reading frame for a fragment, permitting the out-of-frame translations to be ignored. In this study we evaluate five widely used ab initio gene-calling algorithms—FragGeneScan, MetaGeneAnnotator, MetaGeneMark, Orphelia, and Prodigal—for accuracy on short (75–1000 bp) fragments containing sequence error from previously published artificial data and “real” metagenomic datasets.

Results

While gene prediction tools have similar accuracies predicting genes on error-free fragments, in the presence of sequencing errors considerable differences between tools become evident. For error-containing short reads, FragGeneScan finds more prokaryotic coding regions than does MetaGeneAnnotator, MetaGeneMark, Orphelia, or Prodigal. This improved detection of genes in error-containing fragments, however, comes at the cost of much lower (50%) specificity and overprediction of genes in noncoding regions.

Conclusions

Ab initio gene callers offer a significant reduction in the computational burden of annotating individual nucleic acid reads and are used in many metagenomic annotation systems. For predicting reading frames on raw reads, we find the hidden Markov model approach in FragGeneScan is more sensitive than other gene prediction tools, while Prodigal, MGA, and MGM are better suited for higher-quality sequences such as assembled contigs.