Changes in 16s RNA Gene Microbial Community Profiling by Concentration of Prokaryotic DNA

Gut dysbiosis induced by florfenicol increases susceptibility to Aeromonas hydrophila infection in Zebrafish Danio rerio after the recommended withdrawal period

OBJECTIVE

Florfenicol (FFC) is a broad-spectrum antibiotic approved by the U.S. Food and Drug Administration to treat both systemic and external bacterial infections in food fish. The objective of this study was to evaluate the effect of FFC-medicated feed on the gut microbiota of Zebrafish Danio danio to determine (1) if the therapeutic dose of FFC-medicated feed induces dysbiosis and (2) if fish with altered gut microbiota were more susceptible to subsequent infection by the common opportunistic fish pathogen Aeromonas hydrophila.

METHODS

Zebrafish that were treated with regular and FFC-medicated feeds were artificially challenged with A. hydrophila at the end of the recommended 15-day antibiotic withdrawal period. The gut microbiota of the Zebrafish at different stages was analyzed using 16S ribosomal RNA gene sequencing.

RESULT

Our results found that FFC-medicated feed induced disruption of the gut microbiota. Dysbiosis was observed in all treated groups, with a significant increase in bacterial diversity, and was characterized by a remarkable bloom of Proteobacteria and a drastic decline of Mycoplasma and Cetobacterium in treated animals but without noticeable clinical signs or mortalities. In addition, the increase of Proteobacteria was not significantly reduced after the recommended 15-day withdrawal period, and the Zebrafish treated with FFC-medicated feed exhibited a significantly higher mortality rate when they were subsequently challenged with A. hydrophila compared to the control (regular feed) groups. Interestingly, the most dramatic changes in the gut microbiome composition occurred at the transition time between the late stage of the medicated treatment and the beginning of the withdrawal period instead of the time during the Aeromonas infection.

CONCLUSION

The administration of FFC-medicated feed at the recommended dose induced gut dysbiosis in Zebrafish, and fish did not recover to the baseline after the recommended withdrawal period. Our findings suggest that the use of antibiotics in fish elicits a response similar to those previously described in mammals and possibly makes the host more susceptible to subsequent infections of opportunistic pathogens. This study using a controlled model system suggests that antibiotics in aquaculture may have long-term effects on the general well-being of the fish.

Topsoil and subsoil bacterial community assemblies across different drainage conditions in a mountain environment

BACKGROUND

High mountainous environments are of particular interest as they play an essential role for life and human societies, while being environments which are highly vulnerable to climate change and land use intensification. Despite this, our knowledge of high mountain soils in South America and their microbial community structure is strikingly scarce, which is of more concern considering the large population that depends on the ecosystem services provided by these areas. Conversely, the Central Andes, located in the Mediterranean region of Chile, has long been studied for its singular flora, whose diversity and endemism has been attributed to the particular geological history and pronounced environmental gradients in short distances. Here, we explore soil properties and microbial community structure depending on drainage class in a well-preserved Andean valley on the lower alpine vegetation belt (~2500 m a.s.l.) at 33.5˚S. This presents an opportunity to determine changes in the overall bacterial community structure across different types of soils and their distinct layers in a soil depth profile of a highly heterogeneous environment.

METHODS

Five sites closely located (<1.5 km) and distributed in a well preserved Andean valley on the lower alpine vegetation belt (~2500 m a.s.l.) at 33.5˚S were selected based on a pedological approach taking into account soil types, drainage classes and horizons. We analyzed 113 soil samples using high-throughput sequencing of the 16S rRNA gene to describe bacterial abundance, taxonomic composition, and co-occurrence networks.

RESULTS

Almost 18,427 Amplicon Sequence Variant (ASVs) affiliated to 55 phyla were detected. The bacterial community structure within the same horizons were very similar validating the pedological sampling approach. Bray-Curtis dissimilarity analysis revealed that the structure of bacterial communities in superficial horizons (topsoil) differed from those found in deep horizons (subsoil) in a site-specific manner. However, an overall closer relationship was observed between topsoil as opposed to between subsoil microbial communities. Alpha diversity of soil bacterial communities was higher in topsoil, which also showed more bacterial members interacting and with higher average connectivity compared to subsoils. Finally, abundances of specific taxa could be considered as biological markers in the transition from topsoil to subsoil horizons, like Fibrobacterota, Proteobacteria, Bacteroidota for shallower soils and Chloroflexi, Latescibacterota and Nitrospirota for deeper soils.

CONCLUSIONS

The results indicate the importance of the soil drainage conditions for the bacterial community composition, suggesting that information of both structure and their possible ecological relationships, might be useful in clarifying the location of the edge of the topsoil-subsoil transition in mountainous environments.

Characterization of the bacterial microbiome of Amblyomma scalpturatum and Amblyomma ovale collected from Tapirus terrestris and Amblyomma sabanerae collected from Chelonoidis denticulata, Madre de Dios- Peru

BACKGROUND

Ticks are arthropods that can host and transmit pathogens to wild animals, domestic animals, and even humans. The microbiome in ticks is an endosymbiotic, pathogenic and is yet to be fully understood.

RESULTS

Adult male Amblyomma scalpturatum (A. scalpturatum) and Amblyomma ovale (A. ovale) ticks were collected from Tapirus terrestris (T. terrestris) captured in the rural area of San Lorenzo Village, and males Amblyomma sabanerae were collected from Chelonoidis denticulate (C. denticulate) of the Gamita Farm in the Amazon region of Madre de Dios, Peru. The Chao1 and Shannon-Weaver analyses indicated a greater bacterial richness and diversity in male A. sabanerae (Amblyomma sabanerae; 613.65-2.03) compared to male A. scalpturatum and A. ovale (A. scalpturatum and A. ovale; 102.17-0.40). Taxonomic analyses identified 478 operational taxonomic units representing 220 bacterial genera in A. sabanerae and 86 operational taxonomic units representing 28 bacterial genera in A. scalpturatum and A. ovale. Of the most prevalent genera was Francisella (73.2%) in A. sabanerae, and Acinetobacter (96.8%) in A. scalpturatum and A. ovale to be considered as the core microbiome of A. sabanerae and A. scalpturatum/A. ovale respectively.

CONCLUSIONS

We found a high bacterial diversity in male of A. sabanerae collected from C. denticulata showed prevalence of Francisella and prevalence of Acinetobacter in male A. scalpturatum and A. ovale collected from T. terrestris. The greatest bacterial diversity and richness was found in males A. sabanerae. This is the first bacterial metagenomic study performed in A. scalpturatum/A. ovale and A. sabanerae collected from T. terrestris and C. denticulata in the Peruvian jungle.

Collection Time, Location, and Mosquito Species Have Distinct Impacts on the Mosquito Microbiota

The mosquito microbiota affects many aspects of mosquito biology including development and reproduction. It also strongly impacts interactions between the mosquito host and pathogens that cause important disease in humans, such as dengue and malaria. Critically, the mosquito microbiota is highly diverse and can vary in composition in response to multiple environmental variables, but these effects are not always consistent. Understanding how the environment shapes mosquito microbial diversity is a critical step in elucidating the ubiquity of key host-microbe-pathogen interactions in nature. To that end, we examined the role of time of collection, collection location and host species on mosquito microbial diversity by repeating collections at two-month intervals on a trapping grid spanning three distinct biomes. We then used 16S rRNA sequencing to compare the microbiomes of Aedes taeniorhynchus, Anopheles crucians, and Culex nigripalpus mosquitoes from those collections. We saw that mosquito diversity was strongly affected by both time and collection location. We also observed that microbial richness and diversity increased from March to May, and that An. crucians and Cx. nigripalpus had greater microbial diversity than Ae. taeniorhynchus. However, we also observed that collection location had no impact on microbial diversity except for significantly lower bacterial richness observed in mosquitoes collected from the mangrove wetlands. Our results highlight that collection time, collection location, and mosquito species each affect aspects of mosquito microbial diversity, but their importance is context dependent. We also demonstrate that these variables have differing impacts on mosquito diversity and mosquito microbial diversity. Our findings suggest that the environment likely plays an important but variable role in influencing the composition of the mosquito microbiota.

Metagenomic Sequencing for Microbial DNA in Human Samples: Emerging Technological Advances

Whole genome metagenomic sequencing is a powerful platform enabling the simultaneous identification of all genes from entirely different kingdoms of organisms in a complex sample. This technology has revolutionised multiple areas from microbiome research to clinical diagnoses. However, one of the major challenges of a metagenomic study is the overwhelming non-microbial DNA present in most of the host-derived specimens, which can inundate the microbial signals and reduce the sensitivity of microorganism detection. Various host DNA depletion methods to facilitate metagenomic sequencing have been developed and have received considerable attention in this context. In this review, we present an overview of current host DNA depletion approaches along with explanations of their underlying principles, advantages and disadvantages. We also discuss their applications in laboratory microbiome research and clinical diagnoses and, finally, we envisage the direction of the further perfection of metagenomic sequencing in samples with overabundant host DNA.

Microbial Diversity of Adult Aedes aegypti and Water Collected from Different Mosquito Aquatic Habitats in Puerto Rico

Mosquitoes, the major vectors of viruses like dengue, are naturally host to diverse microorganisms, which play an important role in their development, fecundity, immunity, and vector competence. The composition of their microbiota is strongly influenced by the environment, particularly their aquatic larval habitat. In this study, we used 2×300 bp 16s Illumina sequencing to compare the microbial profiles of emerging adult Aedes aegypti mosquitoes and the water collected from common types of aquatic habitat containers in Puerto Rico, which has endemic dengue transmission. We sequenced 141 mosquito and 46 water samples collected from plastic containers, septic tanks, discarded tires, underground trash cans, tree holes, or water meters. We identified 9 bacterial genera that were highly prevalent in the mosquito microbiome, and 77 for the microbiome of the aquatic habitat. The most abundant mosquito-associated bacterial OTUs were from the families Burkholderiaceae, Pseudomonadaceae, Comamonadaceae, and Xanthomonadaceae. Microbial profiles varied greatly between mosquitoes, and there were few major differences explained by container type; however, the microbiome of mosquitoes from plastic containers was more diverse and contained more unique taxa than the other groups. Container water was significantly more diverse than mosquitoes, and our data suggest that mosquitoes filter out many bacteria, with Alphaproteobacteria in particular being far more abundant in water. These findings provide novel insight into the microbiome of mosquitoes in the region and provide a platform to improve our understanding of the fundamental mosquito-microbe interactions.

Characterization of the bacterial microbiome of Rhipicephalus (Boophilus) microplus collected from Pecari tajacu "Sajino" Madre de Dios, Peru

Ticks are arthropods that can host and transmit pathogens to wild animals, domestic animals, and even humans. The bacterial microbiome of adult (males and females) and nymph Rhipicephalus microplus ticks collected from a collared peccary, Pecari tajacu, captured in the rural area of Botijón Village in the Amazon region of Madre de Dios, Peru, was evaluated using metagenomics. The Chao1 and Shannon-Weaver analyses indicated greater bacterial richness and diversity in female ticks (GARH; 375-4.15) and nymph ticks (GARN; 332-4.75) compared to that in male ticks (GARM; 215-3.20). Taxonomic analyses identified 185 operational taxonomic units representing 147 bacterial genera. Of the 25 most prevalent genera, Salmonella (17.5%) and Vibrio (15.0%) showed the highest relative abundance followed by several other potentially pathogenic genera, such as Paracoccus (7.8%), Staphylococcus (6.8%), Pseudomonas (6.6%), Corynebacterium (5.0%), Cloacibacterium (3.6%), and Acinetobacter (2.5%). In total, 19.7% of the detected genera are shared by GARH, GARM, and GARN, and they can be considered as the core microbiome of R. microplus. To the best of our knowledge, this study is the first to characterize the microbiome of ticks collected from P. tajacu and to report the presence of Salmonella and Vibrio in R. microplus. The pathogenic potential and the role of these bacteria in the physiology of R. microplus should be further investigated due to the possible implications for public health and animal health in populations neighboring the habitat of P. tajacu.

Deciphering the Omics of Plant-Microbe Interaction: Perspectives and New Insights

Introduction

Plants do not grow in isolation, rather they are hosts to a variety of microbes in their natural environments. While, few thrive in the plants for their own benefit, others may have a direct impact on plants in a symbiotic manner. Unraveling plant-microbe interactions is a critical component in recognizing the positive and negative impacts of microbes on plants. Also, by affecting the environment around plants, microbes may indirectly influence plants. The progress in sequencing technologies in the genomics era and several omics tools has accelerated in biological science. Studying the complex nature of plant-microbe interactions can offer several strategies to increase the productivity of plants in an environmentally friendly manner by providing better insights. This review brings forward the recent works performed in building omics strategies that decipher the interactions between plant-microbiome. At the same time, it further explores other associated mutually beneficial aspects of plant-microbe interactions such as plant growth promotion, nitrogen fixation, stress suppressions in crops and bioremediation; as well as provides better insights on metabolic interactions between microbes and plants through omics approaches. It also aims to explore advances in the study of Arabidopsis as an important avenue to serve as a baseline tool to create models that help in scrutinizing various factors that contribute to the elaborate relationship between plants and microbes. Causal relationships between plants and microbes can be established through systematic gnotobiotic experimental studies to test hypotheses on biologically derived interactions.

Conclusion

This review will cover recent advances in the study of plant-microbe interactions keeping in view the advantages of these interactions in improving nutrient uptake and plant health.

The microbiome of diabetic foot ulcers: a comparison of swab and tissue biopsy wound sampling techniques using 16S rRNA gene sequencing

Background

Health-care professionals need to collect wound samples to identify potential pathogens that contribute to wound infection. Obtaining appropriate samples from diabetic foot ulcers (DFUs) where there is a suspicion of infection is of high importance. Paired swabs and tissue biopsies were collected from DFUs and both sampling techniques were compared using 16S rRNA gene sequencing.

Results

Mean bacterial abundance determined using quantitative polymerase chain reaction (qPCR) was significantly lower in tissue biopsies (p = 0.03). The mean number of reads across all samples was significantly higher in wound swabs \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \Big(\overline{X} $$\end{document}(X¯ = 32,014) compared to tissue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \overline{X} $$\end{document}X¯ = 15,256, p = 0.001). Tissue biopsies exhibited greater overall diversity of bacteria relative to swabs (Shannon’s H diversity p = 0.009). However, based on a presence/absence analysis of all paired samples, the frequency of occurrence of bacteria from genera of known and potential pathogens was generally higher in wound swabs than tissue biopsies. Multivariate analysis identified significantly different bacterial communities in swabs compared to tissue (p = 0.001). There was minimal correlation between paired wound swabs and tissue biopsies in the number and types of microorganisms. RELATE analysis revealed low concordance between paired DFU swab and tissue biopsy samples (Rho = 0.043, p = 0.34).

Conclusions

Using 16S rRNA gene sequencing this study identifies the potential for using less invasive swabs to recover high relative abundances of known and potential pathogen genera from DFUs when compared to the gold standard collection method of tissue biopsy.

Human and Extracellular DNA Depletion for Metagenomic Analysis of Complex Clinical Infection Samples Yields Optimized Viable Microbiome Profiles

Metagenomic sequencing is a promising approach for identifying and characterizing organisms and their functional characteristics in complex, polymicrobial infections, such as airway infections in people with cystic fibrosis. These analyses are often hampered, however, by overwhelming quantities of human DNA, yielding only a small proportion of microbial reads for analysis. In addition, many abundant microbes in respiratory samples can produce large quantities of extracellular bacterial DNA originating either from biofilms or dead cells. We describe a method for simultaneously depleting DNA from intact human cells and extracellular DNA (human and bacterial) in sputum, using selective lysis of eukaryotic cells and endonuclease digestion. We show that this method increases microbial sequencing depth and, consequently, both the number of taxa detected and coverage of individual genes such as those involved in antibiotic resistance. This finding underscores the substantial impact of DNA from sources other than live bacteria in micro-biological analyses of complex, chronic infection specimens.

Nelson et al. describe a method for reducing both human cellular DNA and extracellular DNA (human and bacterial) in a complex respiratory sample using hypotonic lysis and endonuclease digestion. This method increases effective microbial sequencing depth and minimizes bias introduced into subsequent phylogenetic analysis by bacterial extracellular DNA.

Effects of Microcystin-LR on Metabolic Functions and Structure Succession of Sediment Bacterial Community under Anaerobic Conditions

Microcystins (MCs), which are produced by harmful cyanobacteria blooms, pose a serious threat to environmental health. However, the effect of MCs on the bacterial community under anaerobic conditions is still unclear. This study examined the dynamic changes of MC-degrading capacity, metabolic activity, and structure of the bacterial community in lake sediment repeatedly treated with 1 mg/L microcystin-LR (MC-LR) under anaerobic conditions. The results showed that the MC-degrading capacity of the bacterial community was increased nearly three-fold with increased treatment frequency. However, the metabolic profile behaved in exactly opposite trend, in which the overall carbon metabolic activity was inhibited by repeated toxin addition. Microbial diversity was suppressed by the first addition of MC-LR and then gradually recovered. The 16S amplicon sequencing showed that the dominant genera were changed from Exiguobacterium and Acinetobacter to Prosthecobacter, Dechloromonas, and Agrobacterium. Furthermore, the increase in the relative abundance of Dechloromonas, Pseudomonas, Hydrogenophaga, and Agrobacterium was positively correlated with the MC-LR treatment times. This indicates that they might be responsible for MC degradation under anaerobic conditions. Our findings reveal the relationship between MC-LR and the sediment bacterial community under anaerobic conditions and indicate that anaerobic biodegradation is an effective and promising method to remediate MCs pollution.

Detection and quantification of Staphylococcus in chronic rhinosinusitis

BACKGROUND

The sinonasal microbiota has been implicated in chronic rhinosinusitis (CRS) pathogenesis, particularly related to the presence of Staphylococcus aureus. Staphylococcus epidermidis is also prevalent within the sinonasal microbiota and may inhibit S. aureus colonization. We investigated polymerase chain reaction (PCR) primer pairs for measuring absolute abundances of S. aureus and S. epidermidis, then compared bacterial community composition and absolute abundances of these species between CRS patients and controls.

METHODS

Six candidate Staphylococcus species-specific primer pairs were tested in silico and in vitro against pure bacterial isolates. Quantitative PCR (qPCR) for absolute quantification of S. aureus, S. epidermidis, and overall bacterial load were assessed in 40 CRS (CRS without nasal polyposis [CRSsNP] = 22, CRS with nasal polyposis [CRSwNP] = 18) patients and 14 controls. Amplicon sequencing of the V3-V4 hypervariable regions of the 16S ribosomal RNA (rRNA) bacterial gene were conducted to investigate community composition.

RESULTS

Primer pairs targeting the gmk gene of S. aureus and nrd gene from S. epidermidis were the most specific and sensitive primers. S. aureus (CRSsNP = 81.8% occurrence, CRSwNP = 83%, control = 92.9%) and S. epidermidis (CRSsNP = 95.5%, CRSwNP = 100%, control = 92.9%) were very prevalent, as indicated by qPCR results. Both CRSsNP and CRSwNP had significantly (p < 0.05) higher bacterial load when compared with controls (p < 0.05 for both). No significant correlation was observed between S. aureus and S. epidermidis abundances (p > 0.05).

CONCLUSION

Bacterial community sequencing detected Staphylococcus-assigned sequences in nearly all patients; however, it could not differentiate between S. aureus and S. epidermidis. Here, we present primer pairs that can distinguish between these species. We report a very high prevalence of S. aureus in both CRS patients and controls.

Pharmaceuticals and Personal Care Products Can Be Transformed by Anaerobic Microbiomes in the Environment and in Waste-Treatment Processes

Pharmaceuticals and personal care products (PPCPs) are emerging environmental contaminants that can be transformed by anaerobic microorganisms in anoxic environments. The present study examined 2 consortia, enriched under methanogenic and sulfate-rich conditions, that demethylate the phenylmethyl ether anti-inflammatory drug naproxen to 6-O-desmethylnaproxen. Both enriched consortia were also able to demethylate a range of phenylmethyl ether compounds of plant-based origin or used as PPCPs. Results from 16S rRNA gene sequencing showed that the 2 communities were very different despite sharing the same PPCP metabolism. In most cases, the demethylated metabolite was not further degraded but rather accumulated in the culture medium. For the expectorant guaifenesin, this resulted in a novel microbial metabolite. Furthermore, to our knowledge, this is the first report of methylparaben metabolism under methanogenic conditions. The wide range of phenylmethyl ether substrates that underwent O-demethylation in both methanogenic and sulfate-rich conditions suggests that there are potentially bioactive transformation products in the environment that have not yet been quantified. Environ Toxicol Chem 2019;38:1585-1593. © 2019 SETAC.

Performance of Microbiome Sequence Inference Methods in Environments with Varying Biomass

Microbial communities have important ramifications for human health, but determining their impact requires accurate characterization. Current technology makes microbiome sequence data more accessible than ever. However, popular software methods for analyzing these data are based on algorithms developed alongside older sequencing technology and smaller data sets and thus may not be adequate for modern, high-throughput data sets. Additionally, samples from environments where microbes are scarce present additional challenges to community characterization relative to high-biomass environments, an issue that is often ignored. We found that a new class of microbiome sequence processing tools, called amplicon sequence variant (ASV) methods, outperformed conventional methods. In samples representing low-biomass communities, where sample contamination becomes a significant confounding factor, the improved accuracy of ASV methods may allow more-robust computational identification of contaminants.

Microbiome community composition plays an important role in human health, and while most research to date has focused on high-microbial-biomass communities, low-biomass communities are also important. However, contamination and technical noise make determining the true community signal difficult when biomass levels are low, and the influence of varying biomass on sequence processing methods has received little attention. Here, we benchmarked six methods that infer community composition from 16S rRNA sequence reads, using samples of varying biomass. We included two operational taxonomic unit (OTU) clustering algorithms, one entropy-based method, and three more-recent amplicon sequence variant (ASV) methods. We first compared inference results from high-biomass mock communities to assess baseline performance. We then benchmarked the methods on a dilution series made from a single mock community—samples that varied only in biomass. ASVs/OTUs inferred by each method were classified as representing expected community, technical noise, or contamination. With the high-biomass data, we found that the ASV methods had good sensitivity and precision, whereas the other methods suffered in one area or in both. Inferred contamination was present only in small proportions. With the dilution series, contamination represented an increasing proportion of the data from the inferred communities, regardless of the inference method used. However, correlation between inferred contaminants and sample biomass was strongest for the ASV methods and weakest for the OTU methods. Thus, no inference method on its own can distinguish true community sequences from contaminant sequences, but ASV methods provide the most accurate characterization of community and contaminants.

IMPORTANCE Microbial communities have important ramifications for human health, but determining their impact requires accurate characterization. Current technology makes microbiome sequence data more accessible than ever. However, popular software methods for analyzing these data are based on algorithms developed alongside older sequencing technology and smaller data sets and thus may not be adequate for modern, high-throughput data sets. Additionally, samples from environments where microbes are scarce present additional challenges to community characterization relative to high-biomass environments, an issue that is often ignored. We found that a new class of microbiome sequence processing tools, called amplicon sequence variant (ASV) methods, outperformed conventional methods. In samples representing low-biomass communities, where sample contamination becomes a significant confounding factor, the improved accuracy of ASV methods may allow more-robust computational identification of contaminants.

Plasmid DNA contaminant in molecular reagents

Background noise in metagenomic studies is often of high importance and its removal requires extensive post-analytic, bioinformatics filtering. This is relevant as significant signals may be lost due to a low signal-to-noise ratio. The presence of plasmid residues, that are frequently present in reagents as contaminants, has not been investigated so far, but may pose a substantial bias. Here we show that plasmid sequences from different sources are omnipresent in molecular biology reagents. Using a metagenomic approach, we identified the presence of the (pol) of equine infectious anemia virus in human samples and traced it back to the expression plasmid used for generation of a commercial reverse transcriptase. We found fragments of multiple other expression plasmids in human samples as well as commercial polymerase preparations. Plasmid contamination sources included production chain of molecular biology reagents as well as contamination of reagents from environment or human handling of samples and reagents. Retrospective analyses of published metagenomic studies revealed an inaccurate signal-to-noise differentiation. Hence, the plasmid sequences that seem to be omnipresent in molecular biology reagents may misguide conclusions derived from genomic/metagenomics datasets and thus also clinical interpretations. Critical appraisal of metagenomic data sets for the possibility of plasmid background noise is required to identify reliable and significant signals.

The antihistamine diphenhydramine is demethylated by anaerobic wastewater microorganisms

While emerging pharmaceutical contaminants are monitored in wastewater treatment and the environment, there is little information concerning their microbial metabolites. The transformation of diphenhydramine by microorganisms in anaerobic digester sludge was investigated using anaerobic cultures amended with 1 mM diphenhydramine as the sole carbon source. Complete transformation of the parent compound to a persistent metabolite occurred within 191 days. Using GC/MS analysis, the metabolite was identified as N-desmethyl diphenhydramine. Loss of the parent compound diphenhydramine followed a first order rate constant of 0.013 day^-1. There was no observed decrease in metabolite concentration even after a further 12 months of incubation, suggesting that the metabolite resists further degradation during wastewater treatment. Bacterial community diversity in the diphenhydramine transforming assay cultures showed enrichment in Comamonadaceae, Symbiobacteriaceae, Anaerolineaceae, and Prevotellaceae relative to unamended background controls. An anaerobic toxicity assay demonstrated that diphenhydramine has an inhibitory effect on both fermentative bacteria and methanogenic archaea in the wastewater community. In contrast, the metabolite N-desmethyl diphenhydramine partially suppressed methanogens but did not impact the fermenting community. To our knowledge, this is the first report of diphenhydramine metabolism by a bacterial community. The limited transformation of diphenhydramine by wastewater microorganisms indicates that N-desmethyl diphenhydramine will enter the environment along with unmetabolized diphenhydramine.

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

Background

The advent and use of highly sensitive molecular biology techniques to explore the microbiota and microbiome in environmental and tissue samples have detected the presence of contaminating microbial DNA within reagents. These microbial DNA contaminants may distort taxonomic distributions and relative frequencies in microbial datasets, as well as contribute to erroneous interpretations and identifications.

Results

We herein report on the occurrence of bacterial DNA contamination within commonly used DNA extraction kits and PCR reagents and the effect of these contaminates on data interpretation. When compared to previous reports, we identified an additional 88 bacterial genera as potential contaminants of molecular biology grade reagents, bringing the total number of known contaminating microbes to 181 genera. Many of the contaminants detected are considered normal inhabitants of the human gastrointestinal tract and the environment and are often indistinguishable from those genuinely present in the sample.

Conclusions

Laboratories working on bacterial populations need to define contaminants present in all extraction kits and reagents used in the processing of DNA. Any unusual and/or unexpected findings need to be viewed as possible contamination as opposed to unique findings.

Electronic supplementary material

The online version of this article (doi:10.1186/s13099-016-0103-7) contains supplementary material, which is available to authorized users.