Systematic evaluation of bias in microbial community profiles induced by whole genome amplification

Evaluation of multiple displacement amplification for metagenomic analysis of low biomass samples

Combining multiple displacement amplification (MDA) with metagenomics enables the analysis of samples with extremely low DNA concentrations, making them suitable for high-throughput sequencing. Although amplification bias and nonspecific amplification have been reported from MDA-amplified samples, the impact of MDA on metagenomic datasets is not well understood. We compared three MDA methods (i.e. bulk MDA, emulsion MDA, and primase MDA) for metagenomic analysis of two DNA template concentrations (approx. 1 and 100 pg) derived from a microbial community standard "mock community" and two low biomass environmental samples (i.e. borehole fluid and groundwater). We assessed the impact of MDA on metagenome-based community composition, assembly quality, functional profiles, and binning. We found amplification bias against high GC content genomes but relatively low nonspecific amplification such as chimeras, artifacts, or contamination for all MDA methods. We observed MDA-associated representational bias for microbial community profiles, especially for low-input DNA and with the primase MDA method. Nevertheless, similar taxa were represented in MDA-amplified libraries to those of unamplified samples. The MDA libraries were highly fragmented, but similar functional profiles to the unamplified libraries were obtained for bulk MDA and emulsion MDA at higher DNA input and across these MDA libraries for the groundwater sample. Medium to low-quality bins were possible for the high input bulk MDA metagenomes for the most simple microbial communities, borehole fluid, and mock community. Although MDA-based amplification should be avoided, it can still reveal meaningful taxonomic and functional information from samples with extremely low DNA concentration where direct metagenomics is otherwise impossible.

First shotgun metagenomics study of Juan de Fuca deep-sea sediments reveals distinct microbial communities above, within, between, and below sulfate methane transition zones

The marine deep subsurface is home to a vast microbial ecosystem, affecting biogeochemical cycles on a global scale. One of the better-studied deep biospheres is the Juan de Fuca (JdF) Ridge, where hydrothermal fluid introduces oxidants into the sediment from below, resulting in two sulfate methane transition zones (SMTZs). In this study, we present the first shotgun metagenomics study of unamplified DNA from sediment samples from different depths in this stratified environment. Bioinformatic analyses showed a shift from a heterotrophic, Chloroflexota-dominated community above the upper SMTZ to a chemolithoautotrophic Proteobacteria-dominated community below the secondary SMTZ. The reintroduction of sulfate likely enables respiration and boosts active cells that oxidize acetate, iron, and complex carbohydrates to degrade dead biomass in this low-abundance, low-diversity environment. In addition, analyses showed many proteins of unknown function as well as novel metagenome-assembled genomes (MAGs). The study provides new insights into microbial communities in this habitat, enabled by an improved DNA extraction protocol that allows a less biased view of taxonomic composition and metabolic activities, as well as uncovering novel taxa. Our approach presents the first successful attempt at unamplified shotgun sequencing samples from beyond 50 meters below the seafloor and opens new ways for capturing the true diversity and functional potential of deep-sea sediments.

A primer-independent DNA polymerase-based method for competent whole-genome amplification of intermediate to high GC sequences

Multiple displacement amplification (MDA) has proven to be a useful technique for obtaining large amounts of DNA from tiny samples in genomics and metagenomics. However, MDA has limitations, such as amplification artifacts and biases that can interfere with subsequent quantitative analysis. To overcome these challenges, alternative methods and engineered DNA polymerase variants have been developed. Here, we present new MDA protocols based on the primer-independent DNA polymerase (piPolB), a replicative-like DNA polymerase endowed with DNA priming and proofreading capacities. These new methods were tested on a genomes mixture containing diverse sequences with high-GC content, followed by deep sequencing. Protocols relying on piPolB as a single enzyme cannot achieve competent amplification due to its limited processivity and the presence of ab initio DNA synthesis. However, an alternative method called piMDA, which combines piPolB with Φ29 DNA polymerase, allows proficient and faithful amplification of the genomes. In addition, the prior denaturation step commonly performed in MDA protocols is dispensable, resulting in a more straightforward protocol. In summary, piMDA outperforms commercial methods in the amplification of genomes and metagenomes containing high GC sequences and exhibits similar profiling, error rate and variant determination as the non-amplified samples.

DNA Polymerases for Whole Genome Amplification: Considerations and Future Directions

In the same way that specialized DNA polymerases (DNAPs) replicate cellular and viral genomes, only a handful of dedicated proteins from various natural origins as well as engineered versions are appropriate for competent exponential amplification of whole genomes and metagenomes (WGA). Different applications have led to the development of diverse protocols, based on various DNAPs. Isothermal WGA is currently widely used due to the high performance of Φ29 DNA polymerase, but PCR-based methods are also available and can provide competent amplification of certain samples. Replication fidelity and processivity must be considered when selecting a suitable enzyme for WGA. However, other properties, such as thermostability, capacity to couple replication, and double helix unwinding, or the ability to maintain DNA replication opposite to damaged bases, are also very relevant for some applications. In this review, we provide an overview of the different properties of DNAPs widely used in WGA and discuss their limitations and future research directions.

Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

Circulating tumor cells are tumor cells with high vitality and high metastatic potential that invade and shed into the peripheral blood from primary solid tumors or metastatic foci. Due to the heterogeneity of tumors, it is difficult for high-throughput sequencing analysis of tumor tissues to find the genomic characteristics of low-abundance tumor stem cells. Single-cell sequencing of circulating tumor cells avoids interference from tumor heterogeneity by comparing the differences between single-cell genomes, transcriptomes, and epigenetic groups among circulating tumor cells, primary and metastatic tumors, and metastatic lymph nodes in patients' peripheral blood, providing a new perspective for understanding the biological process of tumors. This article describes the identification, biological characteristics, and single-cell genome-wide variation in circulating tumor cells and summarizes the application of single-cell sequencing technology to tumor typing, metastasis analysis, progression detection, and adjuvant therapy.

One-Cell Metabolic Phenotyping and Sequencing of Soil Microbiome by Raman-Activated Gravity-Driven Encapsulation (RAGE)

Soil harbors arguably the most metabolically and genetically heterogeneous microbiomes on Earth, yet establishing the link between metabolic functions and genome at the precisely one-cell level has been difficult. Here, for mock microbial communities and then for soil microbiota, we established a Raman-activated gravity-driven single-cell encapsulation and sequencing (RAGE-Seq) platform, which identifies, sorts, and sequences precisely one bacterial cell via its anabolic (incorporating D from heavy water) and physiological (carotenoid-containing) functions. We showed that (i) metabolically active cells from numerically rare soil taxa, such as Corynebacterium spp., Clostridium spp., Moraxella spp., Pantoea spp., and Pseudomonas spp., can be readily identified and sorted based on D₂O uptake, and their one-cell genome coverage can reach ∼93% to allow high-quality genome-wide metabolic reconstruction; (ii) similarly, carotenoid-containing cells such as Pantoea spp., Legionella spp., Massilia spp., Pseudomonas spp., and Pedobacter spp. were identified and one-cell genomes were generated for tracing the carotenoid-synthetic pathways; and (iii) carotenoid-producing cells can be either metabolically active or inert, suggesting culture-based approaches can miss many such cells. As a Raman-activated cell sorter (RACS) family member that can establish a metabolism-genome link at exactly one-cell resolution from soil, RAGE-Seq can help to precisely pinpoint “who is doing what” in complex ecosystems.

IMPORTANCE Soil is home to an enormous and complex microbiome that features arguably the highest genomic diversity and metabolic heterogeneity of cells on Earth. Their in situ metabolic activities drive many natural processes of pivotal ecological significance or underlie industrial production of numerous valuable bioactivities. However, pinpointing “who is doing what” in a soil microbiome, which consists of mainly yet-to-be-cultured species, has remained a major challenge. Here, for soil microbiota, we established a Raman-activated gravity-driven single-cell encapsulation and sequencing (RAGE-Seq) method, which identifies, sorts, and sequences at the resolution of precisely one microbial cell via its catabolic and anabolic functions. As a Raman-activated cell sorter (RACS) family member that can establish a metabolism-genome link at one-cell resolution from soil, RAGE-Seq can help to precisely pinpoint “who is doing what” in complex ecosystems.

Template length, concentration and guanidine and cytosine content influence on multiple displacement amplification efficiency

Detection of low abundance human health pathogens in environmental samples is a challenge for water monitoring. This limitation can be overcome by the introduction of multiple displacement amplification (MDA) where a minute amount of genetic material can be amplified using a phi-29 DNA polymerase. However, the genetic makeup and the concentration of the polynucleotides might influence the amplification process due to inherent assay bias. Herein, a series of experiments were designed to demonstrate the effect of genome length, guanidine and cytosine content, and template concentration on the efficiency of MDA. Quantitative polymerase chain reaction (qPCR) was performed to quantify pre- and post-MDA concentrations of selected genes. Linear regression between pre- and post-MDA log gene copies L^-1 of both environmental and lab-grown samples showed a positive correlation (F = 77.59, P < 0.001, R² = 0.7, slope = 1.01). Correlation between relative polynucleotide increase after MDA and target organism length and gene target guanidine and cytosine (G + C) content (F = 4.3, P = 0.02) shows that lower G + C and higher genome length is favored in the MDA process. The MDA process was shown to favor a longer genome over a shorter genome (1.19 and 1.04 change in log gene copy L^-1, respectively) and a lower G + C content over a higher G + C content (1.11 and 0.61 change in log gene copy L^-1, respectively). There was no MDA bias observed when polynucleotides had the same G + C and genome length but different initial concentrations. This study highlights the need for increased caution when interpreting relative abundance of organisms amplified by MDA such as in next generation sequencing.

Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates

Sequencing PCR‐amplified gene fragments from metagenomic DNA is a widely applied method for studying the diversity and dynamics of soil microbial communities. Typically, DNA is extracted from 0.25 to 1 g of soil. These amounts, however, neglect the heterogeneity of soil present at the scale of soil aggregates and thus ignore a crucial scale for understanding the structure and functionality of soil microbial communities. Here, we show with a nitrogen‐depleted agricultural soil the impact of reducing the amount of soil used for DNA extraction from 250 mg to approx. 1 mg to access spatial information on the prokaryotic community structure, as indicated by 16S rRNA gene amplicon analyses. Furthermore, we demonstrate that individual aggregates from the same soil differ in their prokaryotic community compositions. The analysis of 16S rRNA gene amplicon sequences from individual soil aggregates allowed us, in contrast to 250 mg soil samples, to construct a co‐occurrence network that provides insight into the structure of microbial associations in the studied soil. Two dense clusters were apparent in the network, one dominated by Thaumarchaeota, known to be capable of ammonium oxidation at low N concentrations, and the other by Acidobacteria subgroup 6, representing an oligotrophic lifestyle to obtain energy from SOC. Overall this study demonstrates that DNA obtained from individual soil aggregates provides new insights into how microbial communities are assembled.

The cutaneous microbiota of bats has in vitro antifungal activity against the white nose pathogen

Since its introduction into the USA, Pseudogymnoascus destructans (Pd), the fungal pathogen of white-nose syndrome, has killed millions of bats. Recently, bacteria capable of inhibiting the growth of Pd have been identified within bat microbial assemblages, leading to increased interest in elucidating bacterial assemblage-pathogen interactions. Our objectives were to determine if bat cutaneous bacteria have antifungal activity against Pd, and correlate differences in the bat cutaneous microbiota with the presence/absence of Pd. We hypothesized that the cutaneous microbiota of bats is enriched with antifungal bacteria, and that the skin assemblage will correlate with Pd status. To test this, we sampled bat microbiota, adjacent roost surfaces and soil from Pd positive caves to infer possible overlap of antifungal taxa, we tested these bacteria for bioactivity in vitro, and lastly compared bacterial assemblages using both amplicon and shotgun high-throughput DNA sequencing. Results suggest that the presence of Pd has an inconsistent influence on the bat cutaneous microbial assemblage across sites. Operational taxonomic units (OTUs) that corresponded with cultured antifungal bacteria were present within all sample types but were significantly more abundant on bat skin relative to the environment. Additionally, the microbial assemblage of Pd negative bats was found to have more OTUs that corresponded to antifungal taxa than positive bats, suggesting an interaction between the fungal pathogen and cutaneous microbial assemblage.

The apical root canal system microbial communities determined by next-generation sequencing

The aim of this study was to explore the microbial communities of endodontic infections at their apical portion by 16S rRNA Illumina sequencing and delineate the core microbiome of root canal infections and that of their associated clinical symptomatology. Samples were collected from fifteen subjects presenting one tooth with a root canal infection, and their associated symptoms were recorded. Samples were collected from the apical third of roots using a #10 K file and then amplified using multiple displacement amplification and PCR-amplified with universal primers. Amplicons were sequenced (V3–V4 hypervariable region of the 16S rRNA gene) using MiSeq (Illumina, CA). The microbial composition of the samples was determined using QIIME and HOMINGS. Data were analyzed using t tests and ANOVA. A total of 1,038,656 good quality sequences were obtained, and OTUs were assigned to 10 bacterial phyla, led by Bacteroidetes (51.2%) and Firmicutes (27.1%), and 94 genera were represented primarily by Prevotella (17.9%) and Bacteroidaceae G-1 (14.3%). Symptomatic teeth were associated with higher levels of Porphyromonas (p < 0.05) and Prevotella. P. endodontalis and P. oris were present in both cores. The present study demonstrated the complexity of the root canal microbiome and the “common denominators” of root canal infections and identified taxa whose virulence properties should be further explored. The polymicrobial etiology of endodontic infections has long been established. However, few studies have focused on expanding the breadth and depth of coverage of microbiome-infected root canals at their apical portion.

Evaluation of bias induced by viral enrichment and random amplification protocols in metagenomic surveys of saliva DNA viruses

BACKGROUND

Viruses are key players regulating microbial ecosystems. Exploration of viral assemblages is now possible thanks to the development of metagenomics, the most powerful tool available for studying viral ecology and discovering new viruses. Unfortunately, several sources of bias lead to the misrepresentation of certain viruses within metagenomics workflows, hindering the shift from merely descriptive studies towards quantitative comparisons of communities. Therefore, benchmark studies on virus enrichment and random amplification protocols are required to better understand the sources of bias.

RESULTS

We assessed the bias introduced by viral enrichment on mock assemblages composed of seven DNA viruses, and the bias from random amplification methods on human saliva DNA viromes, using qPCR and deep sequencing, respectively. While iodixanol cushions and 0.45 μm filtration preserved the original composition of nuclease-protected viral genomes, low-force centrifugation and 0.22 μm filtration removed large viruses. Comparison of unamplified and randomly amplified saliva viromes revealed that multiple displacement amplification (MDA) induced stochastic bias from picograms of DNA template. However, the type of bias shifted to systematic using 1 ng, with only a marginal influence by amplification time. Systematic bias consisted of over-amplification of small circular genomes, and under-amplification of those with extreme GC content, a negative bias that was shared with the PCR-based sequence-independent, single-primer amplification (SISPA) method. MDA based on random priming provided by a DNA primase activity slightly outperformed those based on random hexamers and SISPA, which may reflect differences in ability to handle sequences with extreme GC content. SISPA viromes showed uneven coverage profiles, with high coverage peaks in regions with low linguistic sequence complexity. Despite misrepresentation of certain viruses after random amplification, ordination plots based on dissimilarities among contig profiles showed perfect overlapping of related amplified and unamplified saliva viromes and strong separation from unrelated saliva viromes. This result suggests that random amplification bias has a minor impact on beta diversity studies.

CONCLUSIONS

Benchmark analyses of mock and natural communities of viruses improve understanding and mitigate bias in metagenomics surveys. Bias induced by random amplification methods has only a minor impact on beta diversity studies of human saliva viromes.

Methods for Enrichment and Sequencing of Oral Viral Assemblages: Saliva, Oral Mucosa, and Dental Plaque Viromes

The oral cavity is a major portal of entry for human pathogens including viruses. However, metagenomics has revealed that highly personalized and time-persistent bacteriophage assemblages dominate this habitat. Most oral bacteriophages follow lysogenic life cycles, deploying complex strategies to manage bacterial homeostasis. Although bacterial dysbiosis underlies common oral pathologies such as caries and periodontitis, the cause of these bacteria replacements remains obscure, and it is theorized that bacteriophages play an important role. The enormous sensitivity of metagenomics coupled with next-generation sequencing has made technically feasible to address the putative role of bacteriophages in oral dysbiosis and represents a valuable tool to discover new human viruses.This chapter proposes a workflow that consists of a simple viral enrichment protocol, two alternative random amplification methods, and next-generation sequencing to access virome composition in three oral environments: supragingival plaque, saliva, and mucosa. These protocols circumvent some well-known sources of bias, providing genomic information about DNA and RNA viral communities with minimal contamination from human and bacterial sources.

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.

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

BACKGROUND

Whole 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.

RESULTS

As 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.

CONCLUSIONS

Partitioning 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.

Functional Metagenomics of Spacecraft Assembly Cleanrooms: Presence of Virulence Factors Associated with Human Pathogens

Strict planetary protection practices are implemented during spacecraft assembly to prevent inadvertent transfer of earth microorganisms to other planetary bodies. Therefore, spacecraft are assembled in cleanrooms, which undergo strict cleaning and decontamination procedures to reduce total microbial bioburden. We wanted to evaluate if these practices selectively favor survival and growth of hardy microorganisms, such as pathogens. Three geographically distinct cleanrooms were sampled during the assembly of three NASA spacecraft: The Lockheed Martin Aeronautics' Multiple Testing Facility during DAWN, the Kennedy Space Center's Payload Hazardous Servicing Facility (KSC-PHSF) during Phoenix, and the Jet Propulsion Laboratory's Spacecraft Assembly Facility during Mars Science Laboratory. Sample sets were collected from the KSC-PHSF cleanroom at three time points: before arrival of the Phoenix spacecraft, during the assembly and testing of the Phoenix spacecraft, and after removal of the spacecraft from the KSC-PHSF facility. All samples were subjected to metagenomic shotgun sequencing on an Illumina HiSeq 2500 platform. Strict decontamination procedures had a greater impact on microbial communities than sampling location Samples collected during spacecraft assembly were dominated by Acinetobacter spp. We found pathogens and potential virulence factors, which determine pathogenicity in all the samples tested during this study. Though the relative abundance of pathogens was lowest during the Phoenix assembly, potential virulence factors were higher during assembly compared to before and after assembly, indicating a survival advantage. Decreased phylogenetic and pathogenic diversity indicates that decontamination and preventative measures were effective against the majority of microorganisms and well implemented, however, pathogen abundance still increased over time. Four potential pathogens, Acinetobacter baumannii, Acinetobacter lwoffii, Escherichia coli and Legionella pneumophila, and their corresponding virulence factors were present in all cleanroom samples. This is the first functional metagenomics study describing presence of pathogens and their corresponding virulence factors in cleanroom environments. The results of this study should be considered for microbial monitoring of enclosed environments such as schools, homes, hospitals and more isolated habitation such the International Space Station and future manned missions to Mars.

Comparison of microbial DNA enrichment tools for metagenomic whole genome sequencing

Metagenomic whole genome sequencing for detection of pathogens in clinical samples is an exciting new area for discovery and clinical testing. A major barrier to this approach is the overwhelming ratio of human to pathogen DNA in samples with low pathogen abundance, which is typical of most clinical specimens. Microbial DNA enrichment methods offer the potential to relieve this limitation by improving this ratio. Two commercially available enrichment kits, the NEBNext Microbiome DNA Enrichment Kit and the Molzym MolYsis Basic kit, were tested for their ability to enrich for microbial DNA from resected arthroplasty component sonicate fluids from prosthetic joint infections or uninfected sonicate fluids spiked with Staphylococcus aureus. Using spiked uninfected sonicate fluid there was a 6-fold enrichment of bacterial DNA with the NEBNext kit and 76-fold enrichment with the MolYsis kit. Metagenomic whole genome sequencing of sonicate fluid revealed 13- to 85-fold enrichment of bacterial DNA using the NEBNext enrichment kit. The MolYsis approach achieved 481- to 9580-fold enrichment, resulting in 7 to 59% of sequencing reads being from the pathogens known to be present in the samples. These results demonstrate the usefulness of these tools when testing clinical samples with low microbial burden using next generation sequencing.

The Significance of Microbe-Mineral-Biomarker Interactions in the Detection of Life on Mars and Beyond

The detection of biomarkers plays a central role in our effort to establish whether there is, or was, life beyond Earth. In this review, we address the importance of considering mineralogy in relation to the selection of locations and biomarker detection methodologies with characteristics most promising for exploration. We review relevant mineral-biomarker and mineral-microbe interactions. The local mineralogy on a particular planet reflects its past and current environmental conditions and allows a habitability assessment by comparison with life under extreme conditions on Earth. The type of mineral significantly influences the potential abundances and types of biomarkers and microorganisms containing these biomarkers. The strong adsorptive power of some minerals aids in the preservation of biomarkers and may have been important in the origin of life. On the other hand, this strong adsorption as well as oxidizing properties of minerals can interfere with efficient extraction and detection of biomarkers. Differences in mechanisms of adsorption and in properties of minerals and biomarkers suggest that it will be difficult to design a single extraction procedure for a wide range of biomarkers. While on Mars samples can be used for direct detection of biomarkers such as nucleic acids, amino acids, and lipids, on other planetary bodies remote spectrometric detection of biosignatures has to be relied upon. The interpretation of spectral signatures of photosynthesis can also be affected by local mineralogy. We identify current gaps in our knowledge and indicate how they may be filled to improve the chances of detecting biomarkers on Mars and beyond.

New perspectives on microbial community distortion after whole-genome amplification

Whole-genome amplification (WGA) has become an important tool to explore the genomic information of microorganisms in an environmental sample with limited biomass, however potential selective biases during the amplification processes are poorly understood. Here, we describe the effects of WGA on 31 different microbial communities from five biotopes that also included low-biomass samples from drinking water and groundwater. Our findings provide evidence that microbiome segregation by biotope was possible despite WGA treatment. Nevertheless, samples from different biotopes revealed different levels of distortion, with genomic GC content significantly correlated with WGA perturbation. Certain phylogenetic clades revealed a homogenous trend across various sample types, for instance Alpha- and Betaproteobacteria showed a decrease in their abundance after WGA treatment. On the other hand, Enterobacteriaceae, an important biomarker group for fecal contamination in groundwater and drinking water, were strongly affected by WGA treatment without a predictable pattern. These novel results describe the impact of WGA on low-biomass samples and may highlight issues to be aware of when designing future metagenomic studies that necessitate preceding WGA treatment.

Physiological and evolutionary potential of microorganisms from the Canterbury Basin subseafloor, a metagenomic approach

Subseafloor sediments represent a large reservoir of organic matter and are inhabited by microbial groups of the three domains of life. Besides impacting the planetary geochemical cycles, the subsurface biosphere remains poorly understood, notably questions related to possible metabolic pathways and selective advantages that may be deployed by buried microorganisms (sporulation, response to stress, dormancy). In order to better understand physiological potentials and possible lifestyles of subseafloor microbial communities, we analyzed two metagenomes from subseafloor sediments collected at 31 mbsf (meters below the sea floor) and 136 mbsf in the Canterbury Basin. Metagenomic phylogenetic and functional diversities were very similar. Phylogenetic diversity was mostly represented by Chloroflexi, Firmicutes and Proteobacteria for Bacteria and by Thaumarchaeota and Euryarchaeota for Archaea. Predicted anaerobic metabolisms encompassed fermentation, methanogenesis and utilization of fatty acids, aromatic and halogenated substrates. Potential processes that may confer selective advantages for subsurface microorganisms included sporulation, detoxication equipment or osmolyte accumulation. Annotation of genomic fragments described the metabolic versatility of Chloroflexi, Miscellaneous Crenarchaeotic Group and Euryarchaeota and showed frequent recombination events within subsurface taxa. This study confirmed that the subseafloor habitat is unique compared to other habitats at the (meta)-genomic level and described physiological potential of still uncultured groups.

Whole genome amplification induced bias in the detection of KRAS-mutated cell populations during colorectal carcinoma tissue testing

Whole genome amplification replicates the entire DNA content of a sample and can thus help to circumvent material limitations when insufficient DNA is available for planned genetic analyses. However, there are conflicting data in the literature whether whole genome amplification introduces bias or reflects precisely the spectrum of starting DNA. We analyzed the origins of discrepancies in KRAS (Kirsten rat sarcoma viral oncogene homolog gene) mutation detection in six of ten samples amplified using the GenomePlex® Tissue Whole Genome Amplification kit 5 (WGA5; Sigma-Aldrich, St. Louis, MO, USA) and KRAS StripAssay® (KRAS SA; ViennaLab Diagnostics, Vienna, Austria). We undertook reextraction, reamplification, retyping, authentication, reanalysis, and reinterpretation to determine whether the discrepancies originated during the preanalytical, analytical, and/or interpretative phase of genotyping. We conclude that a combination of glass slide/sample heterogeneity and biased amplification due to stochastic effects in the early phases of whole genome amplification (WGA) may have adversely affected the results obtained. Our findings are relevant for both forensic genetics testing and massively parallel sequencing using preamplification.

Metagenomic analysis of the airborne environment in urban spaces

The organisms in aerosol microenvironments, especially densely populated urban areas, are relevant to maintenance of public health and detection of potential epidemic or biothreat agents. To examine aerosolized microorganisms in this environment, we performed sequencing on the material from an urban aerosol surveillance program. Whole metagenome sequencing was applied to DNA extracted from air filters obtained during periods from each of the four seasons. The composition of bacteria, plants, fungi, invertebrates, and viruses demonstrated distinct temporal shifts. Bacillus thuringiensis serovar kurstaki was detected in samples known to be exposed to aerosolized spores, illustrating the potential utility of this approach for identification of intentionally introduced microbial agents. Together, these data demonstrate the temporally dependent metagenomic complexity of urban aerosols and the potential of genomic analytical techniques for biosurveillance and monitoring of threats to public health.

Biota and biomolecules in extreme environments on Earth: implications for life detection on Mars

The three main requirements for life as we know it are the presence of organic compounds, liquid water, and free energy. Several groups of organic compounds (e.g., amino acids, nucleobases, lipids) occur in all life forms on Earth and are used as diagnostic molecules, i.e., biomarkers, for the characterization of extant or extinct life. Due to their indispensability for life on Earth, these biomarkers are also prime targets in the search for life on Mars. Biomarkers degrade over time; in situ environmental conditions influence the preservation of those molecules. Nonetheless, upon shielding (e.g., by mineral surfaces), particular biomarkers can persist for billions of years, making them of vital importance in answering questions about the origins and limits of life on early Earth and Mars. The search for organic material and biosignatures on Mars is particularly challenging due to the hostile environment and its effect on organic compounds near the surface. In support of life detection on Mars, it is crucial to investigate analogue environments on Earth that resemble best past and present Mars conditions. Terrestrial extreme environments offer a rich source of information allowing us to determine how extreme conditions affect life and molecules associated with it. Extremophilic organisms have adapted to the most stunning conditions on Earth in environments with often unique geological and chemical features. One challenge in detecting biomarkers is to optimize extraction, since organic molecules can be low in abundance and can strongly adsorb to mineral surfaces. Methods and analytical tools in the field of life science are continuously improving. Amplification methods are very useful for the detection of low concentrations of genomic material but most other organic molecules are not prone to amplification methods. Therefore, a great deal depends on the extraction efficiency. The questions “what to look for”, “where to look”, and “how to look for it” require more of our attention to ensure the success of future life detection missions on Mars.

A method enabling high-throughput sequencing of human cytomegalovirus complete genomes from clinical isolates

Human cytomegalovirus (HCMV) is a ubiquitous virus that can cause serious sequelae in immunocompromised patients and in the developing fetus. The coding capacity of the 235 kbp genome is still incompletely understood, and there is a pressing need to characterize genomic contents in clinical isolates. In this study, a procedure for the high-throughput generation of full genome consensus sequences from clinical HCMV isolates is presented. This method relies on low number passaging of clinical isolates on human fibroblasts, followed by digestion of cellular DNA and purification of viral DNA. After multiple displacement amplification, highly pure viral DNA is generated. These extracts are suitable for high-throughput next-generation sequencing and assembly of consensus sequences. Throughout a series of validation experiments, we showed that the workflow reproducibly generated consensus sequences representative for the virus population present in the original clinical material. Additionally, the performance of 454 GS FLX and/or Illumina Genome Analyzer datasets in consensus sequence deduction was evaluated. Based on assembly performance data, the Illumina Genome Analyzer was the platform of choice in the presented workflow. Analysis of the consensus sequences derived in this study confirmed the presence of gene-disrupting mutations in clinical HCMV isolates independent from in vitro passaging. These mutations were identified in genes RL5A, UL1, UL9, UL111A and UL150. In conclusion, the presented workflow provides opportunities for high-throughput characterization of complete HCMV genomes that could deliver new insights into HCMV coding capacity and genetic determinants of viral tropism and pathogenicity.