Low Biomass Samples Research Articles

Enrichment of Clinically Relevant Organisms in Spontaneous Preterm-Delivered Placentas and Reagent Contamination across All Clinical Groups in a Large Pregnancy Cohort in the United Kingdom.

In this study, differences in the placental microbiota from term and preterm deliveries in a large pregnancy cohort in the United Kingdom were studied by using 16S-targeted amplicon sequencing. The impacts of contamination from DNA extraction, PCR reagents, and the delivery itself were also examined. A total of 400 placental samples from 256 singleton pregnancies were analyzed, and differences between spontaneous preterm-, nonspontaneous preterm-, and term-delivered placentas were investigated. DNA from recently delivered placentas was extracted, and screening for bacterial DNA was carried out by using targeted sequencing of the 16S rRNA gene on the Illumina MiSeq platform. Sequenced reads were analyzed for the presence of contaminating operational taxonomic units (OTUs) identified via sequencing of negative extraction and PCR-blank samples. Differential abundances and between-sample (beta) diversity metrics were then compared. A large proportion of the reads sequenced from the extracted placental samples mapped to OTUs that were also found for negative extractions. Striking differences in the compositions of samples were also observed, according to whether the placenta was delivered abdominally or vaginally, providing strong circumstantial evidence for delivery contamination as an important contributor to observed microbial profiles. When OTU- and genus-level abundances were compared between the groups of interest, a number of organisms were enriched in the spontaneous preterm-delivery cohort, including organisms that have been associated previously with adverse pregnancy outcomes, specifically Mycoplasma spp. and Ureaplasma spp. However, analyses of the overall community structure did not reveal convincing evidence for the existence of a reproducible "preterm placental microbiome."IMPORTANCE Preterm birth is associated with both psychological and physical disabilities and is the leading cause of infant morbidity and mortality worldwide. Infection is known to be an important cause of spontaneous preterm birth, and recent research has implicated variation in the "placental microbiome" in the risk of preterm birth. Consistent with data from previous studies, the abundances of certain clinically relevant species differed between spontaneous preterm- and nonspontaneous preterm- or term-delivered placentas. These results support the view that a proportion of spontaneous preterm births have an intrauterine-infection component. However, an additional observation from this study was that a substantial proportion of sequenced reads were contaminating reads rather than DNA from endogenous, clinically relevant species. This observation warrants caution in the interpretation of sequencing outputs from low-biomass samples such as the placenta.

Small RNA profiling of low biomass samples: identification and removal of contaminants

BackgroundSequencing-based analyses of low-biomass samples are known to be prone to misinterpretation due to the potential presence of contaminating molecules derived from laboratory reagents and environments. DNA contamination has been previously reported, yet contamination with RNA is usually considered to be very unlikely due to its inherent instability. Small RNAs (sRNAs) identified in tissues and bodily fluids, such as blood plasma, have implications for physiology and pathology, and therefore the potential to act as disease biomarkers. Thus, the possibility for RNA contaminants demands careful evaluation.ResultsHerein, we report on the presence of small RNA (sRNA) contaminants in widely used microRNA extraction kits and propose an approach for their depletion. We sequenced sRNAs extracted from human plasma samples and detected important levels of non-human (exogenous) sequences whose source could be traced to the microRNA extraction columns through a careful qPCR-based analysis of several laboratory reagents. Furthermore, we also detected the presence of artefactual sequences related to these contaminants in a range of published datasets, thereby arguing in particular for a re-evaluation of reports suggesting the presence of exogenous RNAs of microbial and dietary origin in blood plasma. To avoid artefacts in future experiments, we also devise several protocols for the removal of contaminant RNAs, define minimal amounts of starting material for artefact-free analyses, and confirm the reduction of contaminant levels for identification of bona fide sequences using ‘ultra-clean’ extraction kits.ConclusionThis is the first report on the presence of RNA molecules as contaminants in RNA extraction kits. The described protocols should be applied in the future to avoid confounding sRNA studies.

Inter-laboratory testing of the effect of DNA blocking reagent G2 on DNA extraction from low-biomass clay samples

Here we show that a commercial blocking reagent (G2) based on modified eukaryotic DNA significantly improved DNA extraction efficiency. We subjected G2 to an inter-laboratory testing, where DNA was extracted from the same clay subsoil using the same batch of kits. The inter-laboratory extraction campaign revealed large variation among the participating laboratories, but the reagent increased the number of PCR-amplified16S rRNA genes recovered from biomass naturally present in the soils by one log unit. An extensive sequencing approach demonstrated that the blocking reagent was free of contaminating DNA, and may therefore also be used in metagenomics studies that require direct sequencing.

A Method for Targeted 16S Sequencing of Human Milk Samples.

Studies of microbial communities have become widespread with the development of relatively inexpensive, rapid, and high throughput sequencing. However, as with all these technologies, reproducible results depend on a laboratory workflow that incorporates appropriate precautions and controls. This is particularly important with low-biomass samples where contaminating bacterial DNA can generate misleading results. This article details a semi-automated workflow to identify microbes from human breast milk samples using targeted sequencing of the 16S ribosomal RNA (rRNA) V4 region on a low- to mid-throughput scale. The protocol describes sample preparation from whole milk including: sample lysis, nucleic acid extraction, amplification of the V4 region of the 16S rRNA gene, and library preparation with quality control measures. Importantly, the protocol and discussion consider issues that are salient to the preparation and analysis of low-biomass samples including appropriate positive and negative controls, PCR inhibitor removal, sample contamination by environmental, reagent, or experimental sources, and experimental best practices designed to ensure reproducibility. While the protocol as described is specific to human milk samples, it is adaptable to numerous low- and high-biomass sample types, including samples collected on swabs, frozen neat, or stabilized in a preservation buffer.

KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples.

Microbiome analyses of low-biomass samples are challenging because of contamination and inefficiencies, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos [clean]), that outperforms single-tube extractions while processing at least five times as fast. KatharoSeq incorporates positive and negative controls to reveal the whole bacterial community from inputs of as few as 50 cells and correctly identifies 90.6% (standard error, 0.013%) of the reads from 500 cells. To demonstrate the broad utility of KatharoSeq, we performed 16S rRNA amplicon and shotgun metagenome analyses of the Jet Propulsion Laboratory spacecraft assembly facility (SAF; n = 192, 96), 52 rooms of a neonatal intensive care unit (NICU; n = 388, 337), and an endangered-abalone-rearing facility (n = 192, 123), obtaining spatially resolved, unique microbiomes reproducible across hundreds of samples. The SAF, our primary focus, contains 32 sOTUs (sub-OTUs, defined as exact sequence matches) and their inferred variants identified by the deblur algorithm, with four (Acinetobacter lwoffii, Paracoccus marcusii, Mycobacterium sp., and Novosphingobium) being present in >75% of the samples. According to microbial spatial topography, the most abundant cleanroom contaminant, A.lwoffii, is related to human foot traffic exposure. In the NICU, we have been able to discriminate environmental exposure related to patient infectious disease, and in the abalone facility, we show that microbial communities reflect the marine environment rather than human input. Consequently, we demonstrate the feasibility and utility of large-scale, low-biomass metagenomic analyses using the KatharoSeq protocol. IMPORTANCE Various indoor, outdoor, and host-associated environments contain small quantities of microbial biomass and represent a niche that is often understudied because of technical constraints. Many studies that attempt to evaluate these low-biomass microbiome samples are riddled with erroneous results that are typically false positive signals obtained during the sampling process. We have investigated various low-biomass kits and methods to determine the limit of detection of these pipelines. Here we present KatharoSeq, a high-throughput protocol combining laboratory and bioinformatic methods that can differentiate a true positive signal in samples with as few as 50 to 500 cells. We demonstrate the application of this method in three unique low-biomass environments, including a SAF, a hospital NICU, and an abalone-rearing facility.

Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid

Advances in genomics have the potential to revolutionize clinical diagnostics. Here, we examine the microbiome of vitreous (intraocular body fluid) from patients who developed endophthalmitis following cataract surgery or intravitreal injection. Endophthalmitis is an inflammation of the intraocular cavity and can lead to a permanent loss of vision. As controls, we included vitreous from endophthalmitis-negative patients, balanced salt solution used during vitrectomy and DNA extraction blanks. We compared two DNA isolation procedures and found that an ultraclean production of reagents appeared to reduce background DNA in these low microbial biomass samples. We created a curated microbial genome database (>5700 genomes) and designed a metagenomics workflow with filtering steps to reduce DNA sequences originating from: (i) human hosts, (ii) ambiguousness/contaminants in public microbial reference genomes and (iii) the environment. Our metagenomic read classification revealed in nearly all cases the same microorganism that was determined in cultivation- and mass spectrometry-based analyses. For some patients, we identified the sequence type of the microorganism and antibiotic resistance genes through analyses of whole genome sequence (WGS) assemblies of isolates and metagenomic assemblies. Together, we conclude that genomics-based analyses of human ocular body fluid specimens can provide actionable information relevant to infectious disease management.

Characterizing the Deep Terrestrial Subsurface Microbiome.

A large portion of the earth's biomass resides in the subsurface and recent studies have expanded our knowledge of indigenous microbial life. Advances in the field of metagenomics now allow analysis of microbial communities from low-biomass samples such as deep (>2.5km) shale core samples. Here we present protocols for the best practices in contamination control, handling core material, extraction of nucleic acids, and low-input library preparation for subsequent metagenomic sequencing.

A microfluidic sub-critical water extraction instrument.

This article discusses a microfluidic subcritical water extraction (SCWE) chip for autonomous extraction of amino acids from astrobiologically interesting samples. The microfluidic instrument is composed of three major components. These include a mixing chamber where the soil sample is mixed and agitated with the solvent (water), a subcritical water extraction chamber where the sample is sealed with a freeze valve at the chip inlet after a vapor bubble is injected into the inlet channels to ensure the pressure in the chip is in equilibrium with the vapor pressure and the slurry is then heated to ≤200 °C in the SCWE chamber, and a filter or settling chamber where the slurry is pumped to after extraction. The extraction yield of the microfluidic SCWE chip process ranged from 50% compared to acid hydrolysis and 80%-100% compared to a benchtop microwave SCWE for low biomass samples.

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome.

Modified RNA-seq method for microbial community and diversity analysis using rRNA in different types of environmental samples.

RNA-seq-based SSU (small subunit) rRNA (ribosomal RNA) analysis has provided a better understanding of potentially active microbial community within environments. However, for RNA-seq library construction, high quantities of purified RNA are typically required. We propose a modified RNA-seq method for SSU rRNA-based microbial community analysis that depends on the direct ligation of a 5’ adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10–100 ng) and does not require a DNA removal step. The method was initially tested on three mock communities synthesized with enriched SSU rRNA of archaeal, bacterial and fungal isolates at different ratios, and was subsequently used for environmental samples of high or low biomass. For high-biomass salt-marsh sediments, enriched SSU rRNA and total nucleic acid-derived RNA-seq datasets revealed highly consistent community compositions for all of the SSU rRNA sequences, and as much as 46.4%-59.5% of 16S rRNA sequences were suitable for OTU (operational taxonomic unit)-based community and diversity analyses with complete coverage of V1-V2 regions. OTU-based community structures for the two datasets were also highly consistent with those determined by all of the 16S rRNA reads. For low-biomass samples, total nucleic acid-derived RNA-seq datasets were analyzed, and highly active bacterial taxa were also identified by the OTU-based method, notably including members of the previously underestimated genus Nitrospira and phylum Acidobacteria in tap water, members of the phylum Actinobacteria on a shower curtain, and members of the phylum Cyanobacteria on leaf surfaces. More than half of the bacterial 16S rRNA sequences covered the complete region of primer 8F, and non-coverage rates as high as 38.7% were obtained for phylum-unclassified sequences, providing many opportunities to identify novel bacterial taxa. This modified RNA-seq method will provide a better snapshot of diverse microbial communities, most notably by OTU-based analysis, even communities with low-biomass samples.

Three distinct pneumotypes characterize the microbiome of the lung in BALB/cJ mice

Bacteria can rarely be isolated from normal healthy lungs using conventional culture techniques, supporting the traditional belief that the lungs are sterile. Yet recent studies using next generation sequencing report that bacterial DNA commonly found in the upper respiratory tract (URT) is present at lower levels in the lungs. Interpretation of that finding is complicated by the technical limitations and potential for contamination introduced when dealing with low biomass samples. The current work sought to overcome those limitations to clarify the number, type and source of bacteria present in the lungs of normal mice. Results showed that the oral microbiome is diverse and highly conserved whereas murine lung samples fall into three distinct patterns. 33% of the samples were sterile, as they lacked culturable bacteria and their bacterial DNA content did not differ from background. 9% of samples contained comparatively higher amounts of bacterial DNA whose composition mimicked that detected in the URT. A final group (58%) contained smaller amounts of microbial DNA whose composition was correlating to that of rodent chow and cage bedding, likely acquired by inspiration of food and bedding fragments. By analyzing each sample independently rather than working with group averages, this work eliminated the bias introduced by aspiration-contaminated samples to establish that three distinct microbiome pneumotypes are present in normal murine lungs.

Three distinct pneumotypes characterize the microbiome of the lung in BALB/cJ mice.

Abstract Bacteria can rarely be isolated from normal healthy lungs using conventional culture techniques, supporting the traditional belief that the lungs are sterile. Yet recent studies using next generation sequencing report that bacterial DNA commonly found in the upper respiratory tract (URT) is present at lower levels in the lungs. Interpretation of that finding is complicated by the technical limitations and potential for contamination introduced when dealing with low biomass samples. The current work sought to overcome those limitations to clarify the number, type and source of bacteria present in the lungs of normal mice. Results showed that the oral microbiome is large, less diverse and highly conserved whereas murine lung samples fall into three distinct patterns. Most pulmonary samples were sterile, as they lacked culturable bacteria and their bacterial DNA content did not differ from background. 11% of samples contained comparatively higher amounts of bacterial DNA whose composition mimicked that detected in the URT, consistent with (micro)aspiration. A final group (26%) contained smaller amounts of microbial DNA whose composition was similar to that of rodent chow, perhaps acquired by inspiration of food fragments. This work eliminated the bias introduced by aspiration-contaminated samples to establish that three distinct microbiome pneumotypes are present in normal murine lungs of BALB/cJ mice. The presented findings contribute to the knowledge in the growing field of microbiome research in the respiratory tract and are of relevance to researchers evaluating respiratory diseases in murine models.

Impact of Contaminating DNA in Whole-Genome Amplification Kits Used for Metagenomic Shotgun Sequencing for Infection Diagnosis.

Whole-genome amplification (WGA) is a useful tool for amplification of very small quantities of DNA for many uses, including metagenomic shotgun sequencing for infection diagnosis. Depending on the application, background DNA from WGA kits can be problematic. Three WGA kits were tested for their utility in a metagenomics approach to identify the pathogens in sonicate fluid comprised of biofilms and other materials dislodged from the surfaces of explanted prosthetic joints using sonication. The Illustra V2 Genomiphi, Illustra single cell Genomiphi, and Qiagen REPLI-g single cell kits were used to test identical sonicate fluid samples. Variations in the number of background reads, the genera identified in the background, and the number of reads from known pathogens known to be present in the samples were observed between kits. These results were then compared to those obtained with a library preparation without prior WGA using an NEBNext Ultra II paired-end kit, which requires a very small amount of input DNA. This approach also resulted in the presence of contaminant bacterial DNA and yielded fewer reads from the known pathogens. These findings highlight the impact that WGA kit selection can have on metagenomic analysis of low-biomass samples and the importance of the careful selection and consideration of the implications of using these tools.

Assessment of REPLI-g Multiple Displacement Whole Genome Amplification (WGA) Techniques for Metagenomic Applications.

Amplification of minute quantities of DNA is a fundamental challenge in low-biomass metagenomic and microbiome studies because of potential biases in coverage, guanine-cytosine (GC) content, and altered species abundances. Whole genome amplification (WGA), although widely used, is notorious for introducing artifact sequences, either by amplifying laboratory contaminants or by nonrandom amplification of a sample's DNA. In this study, we investigate the effect of REPLI-g multiple displacement amplification (MDA; Qiagen, Valencia, CA, USA) on sequencing data quality and species abundance detection in 8 paired metagenomic samples and 1 titrated, mixed control sample. We extracted and sequenced genomic DNA (gDNA) from 8 environmental samples and compared the quality of the sequencing data for the MDA and their corresponding non-MDA samples. The degree of REPLI-g MDA bias was evaluated by sequence metrics, species composition, and cross-validating observed species abundance and species diversity estimates using the One Codex and MetaPhlAn taxonomic classification tools. Here, we provide evidence of the overall efficacy of REPLI-g MDA on retaining sequencing data quality and species abundance measurements while providing increased yields of high-fidelity DNA. We find that species abundance estimates are largely consistent across samples, even with REPLI-g amplification, as demonstrated by the Spearman's rank order coefficient (R2 > 0.8). However, REPLI-g MDA often produced fewer classified reads at the species, genera, and family level, resulting in decreased species diversity. We also observed some areas with the PCR "jackpot effect," with varying input DNA values for the Metagenomics Research Group (MGRG) controls at specific genomic loci. We visualize this effect in whole genome coverage plots and with sequence composition analyses and note these caveats of the MDA method. Despite overall concordance of species abundance between the amplified and unamplified samples, these results demonstrate that amplification of DNA using the REPLI-g method has some limitations. These concerns could be addressed by future improvements in the enzymes or methods for REPLI-g to be considered a >99% robust method for increasing the amount of high-fidelity DNA from low-biomass samples or at the very least, accounted for during computational analysis of MDA samples.

Oral Microbiome Characterization in Murine Models.

The oral microbiome has been implicated as a trigger for immune responsiveness in the oral cavity, particularly in the setting of the inflammatory disease periodontitis. The protocol presented here is aimed at characterizing the oral microbiome in murine models at steady state and during perturbations of immunity or physiology. Herein, we describe murine oral microbiome sampling procedures, processing of low biomass samples and subsequent microbiome characterization based on 16S rRNA gene sequencing.

The excreted microbiota of bats: evidence of niche specialisation based on multiple body habitats.

Animal-associated microbiotas form complex communities, which play crucial functions for their host, including susceptibility to infections. Despite increasing attention to bats as reservoirs of zoonotic pathogens, their microbiota is poorly documented, especially for samples potentially implicated in pathogen transmission such as urine and saliva. Here, using low-biomass individual samples, we examined the composition and structure of bacterial communities excreted by insectivorous bats, focusing on three body habitats (saliva, urine and faeces). We show that niche specialisation occurs as bacterial community composition was distinct across body habitats with the majority of phylotypes being body habitat specific. Our results suggest that urine harbours more diverse bacterial communities than saliva and faeces and reveal potentially zoonotic bacteria such as Leptospira, Rickettsia, Bartonella and Coxiella in all body habitats. Our study emphasised that, in addition to the traditional use of gut-associated samples such as faeces, both urine and saliva are also of interest because of their diverse microbiota and the potential transmission of pathogenic bacteria. Our results represent a critical baseline for future studies investigating the interactions between microbiota and infection dynamics in bats.

Picodroplet partitioned whole genome amplification of low biomass samples preserves genomic diversity for metagenomic analysis.

BackgroundWhole genome amplification (WGA) is a challenging, key step in metagenomic studies of samples containing minute amounts of DNA, such as samples from low biomass environments. It is well known that multiple displacement amplification (MDA), the most commonly used WGA method for microbial samples, skews the genomic representation in the sample. We have combined MDA with droplet microfluidics to perform the reaction in a homogeneous emulsion. Each droplet in this emulsion can be considered an individual reaction chamber, allowing partitioning of the MDA reaction into millions of parallel reactions with only one or very few template molecules per droplet.ResultsAs a proof-of-concept, we amplified genomic DNA from a synthetic metagenome by MDA either in one bulk reaction or in emulsion and found that after sequencing, the species distribution was better preserved and the coverage depth was more evenly distributed across the genomes when the MDA reaction had been performed in emulsion.ConclusionsPartitioning MDA reactions into millions of reactions by droplet microfluidics is a straightforward way to improve the uniformity of MDA reactions for amplifying complex samples with limited amounts of DNA.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-016-0197-7) contains supplementary material, which is available to authorized users.

Validation of picogram- and femtogram-input DNA libraries for microscale metagenomics.

High-throughput sequencing libraries are typically limited by the requirement for nanograms to micrograms of input DNA. This bottleneck impedes the microscale analysis of ecosystems and the exploration of low biomass samples. Current methods for amplifying environmental DNA to bypass this bottleneck introduce considerable bias into metagenomic profiles. Here we describe and validate a simple modification of the Illumina Nextera XT DNA library preparation kit which allows creation of shotgun libraries from sub-nanogram amounts of input DNA. Community composition was reproducible down to 100 fg of input DNA based on analysis of a mock community comprising 54 phylogenetically diverse Bacteria and Archaea. The main technical issues with the low input libraries were a greater potential for contamination, limited DNA complexity which has a direct effect on assembly and binning, and an associated higher percentage of read duplicates. We recommend a lower limit of 1 pg (∼100–1,000 microbial cells) to ensure community composition fidelity, and the inclusion of negative controls to identify reagent-specific contaminants. Applying the approach to marine surface water, pronounced differences were observed between bacterial community profiles of microliter volume samples, which we attribute to biological variation. This result is consistent with expected microscale patchiness in marine communities. We thus envision that our benchmarked, slightly modified low input DNA protocol will be beneficial for microscale and low biomass metagenomics.

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

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

Protocol Improvements for Low Concentration DNA-Based Bioaerosol Sampling and Analysis.

IntroductionAs bioaerosol research attracts increasing attention, there is a need for additional efforts that focus on method development to deal with different environmental samples. Bioaerosol environmental samples typically have very low biomass concentrations in the air, which often leaves researchers with limited options in choosing the downstream analysis steps, especially when culture-independent methods are intended.ObjectivesThis study investigates the impacts of three important factors that can influence the performance of culture-independent DNA-based analysis in dealing with bioaerosol environmental samples engaged in this study. The factors are: 1) enhanced high temperature sonication during DNA extraction; 2) effect of sampling duration on DNA recoverability; and 3) an alternative method for concentrating composite samples. In this study, DNA extracted from samples was analysed using the Qubit fluorometer (for direct total DNA measurement) and quantitative polymerase chain reaction (qPCR).Results and FindingsThe findings suggest that additional lysis from high temperature sonication is crucial: DNA yields from both high and low biomass samples increased up to 600% when the protocol included 30-min sonication at 65°C. Long air sampling duration on a filter media was shown to have a negative impact on DNA recoverability with up to 98% of DNA lost over a 20-h sampling period. Pooling DNA from separate samples during extraction was proven to be feasible with margins of error below 30%.