scholarly journals Applying Genome-Resolved Metagenomics to Deconvolute the Halophilic Microbiome

Genes ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 220 ◽  
Author(s):  
Gherman Uritskiy ◽  
Jocelyne DiRuggiero
Keyword(s):  
Microbial Communities ◽  
Intraspecific Diversity ◽  
Metagenomic Sequencing ◽  
Chromosome Conformation ◽  
Shotgun Metagenomics ◽  
Sequencing Technologies ◽  
Shotgun Metagenomic Sequencing ◽  
Long Read ◽  
Analytical Strategies ◽  
Potential Applications

In the past decades, the study of microbial life through shotgun metagenomic sequencing has rapidly expanded our understanding of environmental, synthetic, and clinical microbial communities. Here, we review how shotgun metagenomics has affected the field of halophilic microbial ecology, including functional potential reconstruction, virus–host interactions, pathway selection, strain dispersal, and novel genome discoveries. However, there still remain pitfalls and limitations from conventional metagenomic analysis being applied to halophilic microbial communities. Deconvolution of halophilic metagenomes has been difficult due to the high G + C content of these microbiomes and their high intraspecific diversity, which has made both metagenomic assembly and binning a challenge. Halophiles are also underrepresented in public genome databases, which in turn slows progress. With this in mind, this review proposes experimental and analytical strategies to overcome the challenges specific to the halophilic microbiome, from experimental designs to data acquisition and the computational analysis of metagenomic sequences. Finally, we speculate about the potential applications of other next-generation sequencing technologies in halophilic communities. RNA sequencing, long-read technologies, and chromosome conformation assays, not initially intended for microbiomes, are becoming available in the study of microbial communities. Together with recent analytical advancements, these new methods and technologies have the potential to rapidly advance the field of halophile research.

scholarly journals Human gut microbial communities dictate efficacy of anti-PD-1 therapy in a humanized microbiome mouse model of glioma

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Kory J Dees ◽  
Hyunmin Koo ◽  
J Fraser Humphreys ◽  
Joseph A Hakim ◽  
David K Crossman ◽  
...  
Keyword(s):  
Mouse Model ◽  
Microbial Communities ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Microbial Composition ◽  
Healthy Human ◽  
Fecal Transplantation ◽  
Host Interaction ◽  
Shotgun Metagenomic Sequencing ◽  
Mouse Lines

Abstract Background Although immunotherapy works well in glioblastoma (GBM) preclinical mouse models, the therapy has not demonstrated efficacy in humans. To address this anomaly, we developed a novel humanized microbiome (HuM) model to study the response to immunotherapy in a preclinical mouse model of GBM. Methods We used 5 healthy human donors for fecal transplantation of gnotobiotic mice. After the transplanted microbiomes stabilized, the mice were bred to generate 5 independent humanized mouse lines (HuM1-HuM5). Results Analysis of shotgun metagenomic sequencing data from fecal samples revealed a unique microbiome with significant differences in diversity and microbial composition among HuM1-HuM5 lines. All HuM mouse lines were susceptible to GBM transplantation, and exhibited similar median survival ranging from 19 to 26 days. Interestingly, we found that HuM lines responded differently to the immune checkpoint inhibitor anti-PD-1. Specifically, we demonstrate that HuM1, HuM4, and HuM5 mice are nonresponders to anti-PD-1, while HuM2 and HuM3 mice are responsive to anti-PD-1 and displayed significantly increased survival compared to isotype controls. Bray-Curtis cluster analysis of the 5 HuM gut microbial communities revealed that responders HuM2 and HuM3 were closely related, and detailed taxonomic comparison analysis revealed that Bacteroides cellulosilyticus was commonly found in HuM2 and HuM3 with high abundances. Conclusions The results of our study establish the utility of humanized microbiome mice as avatars to delineate features of the host interaction with gut microbial communities needed for effective immunotherapy against GBM.

scholarly journals Diversity and Function of Wolf Spider Gut Microbiota Revealed by Shotgun Metagenomics

2021 ◽  
Vol 12 ◽  
Author(s):  
Runbiao Wu ◽  
Luyu Wang ◽  
Jianping Xie ◽  
Zhisheng Zhang
Keyword(s):  
Gut Microbiota ◽  
Wolf Spider ◽  
Metagenomic Sequencing ◽  
Wolf Spiders ◽  
Shotgun Metagenomics ◽  
Microbial Genomes ◽  
Shotgun Metagenomic Sequencing ◽  
Crucial Component ◽  
Genes Encoding ◽  
And Function

Wolf spiders (Lycosidae) are crucial component of integrated pest management programs and the characteristics of their gut microbiota are known to play important roles in improving fitness and survival of the host. However, there are only few studies of the gut microbiota among closely related species of wolf spider. Whether wolf spiders gut microbiota vary with habitats remains unknown. Here, we used shotgun metagenomic sequencing to compare the gut microbiota of two wolf spider species, Pardosa agraria and P. laura from farmland and woodland ecosystems, respectively. The results show that the gut microbiota of Pardosa spiders is similar in richness and abundance. Approximately 27.3% of the gut microbiota of P. agraria comprises Proteobacteria, and approximately 34.5% of the gut microbiota of P. laura comprises Firmicutes. We assembled microbial genomes and found that the gut microbiota of P. laura are enriched in genes for carbohydrate metabolism. In contrast, those of P. agraria showed a higher proportion of genes encoding acetyltransferase, an enzyme involved in resistance to antibiotics. We reconstructed three high-quality and species-level microbial genomes: Vulcaniibacterium thermophilum, Anoxybacillus flavithermus and an unknown bacterium belonging to the family Simkaniaceae. Our results contribute to an understanding of the diversity and function of gut microbiota in closely related spiders.

scholarly journals A probabilistic model to recover individual genomes from metagenomes

2016 ◽  
Author(s):  
Johannes Dröge ◽  
Alexander Schönhuth ◽  
Alice C McHardy
Keyword(s):  
Microbial Communities ◽  
Probabilistic Model ◽  
Reference Data ◽  
Shotgun Metagenomics ◽  
Metagenome Analysis ◽  
Sample Enrichment ◽  
Potential Applications ◽  
Technical Factors ◽  
Types Of Information ◽  
Python Package

Shotgun metagenomics of microbial communities reveals information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial, but very challenging step, due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.

scholarly journals A probabilistic model to recover individual genomes from metagenomes

2016 ◽  
Author(s):  
Johannes Dröge ◽  
Alexander Schönhuth ◽  
Alice C McHardy
Keyword(s):  
Microbial Communities ◽  
Probabilistic Model ◽  
Reference Data ◽  
Shotgun Metagenomics ◽  
Metagenome Analysis ◽  
Sample Enrichment ◽  
Potential Applications ◽  
Technical Factors ◽  
Types Of Information ◽  
Python Package

Shotgun metagenomics of microbial communities reveals information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial, but very challenging step, due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.

scholarly journals Mesophilic Sporeformers Identified in Whey Powder by Using Shotgun Metagenomic Sequencing

2018 ◽  
Vol 84 (20) ◽  
Author(s):  
Aoife J. McHugh ◽  
Conor Feehily ◽  
John T. Tobin ◽  
Mark A. Fenelon ◽  
Colin Hill ◽  
...  
Keyword(s):  
Dairy Product ◽  
Metagenomic Sequencing ◽  
Shotgun Metagenomics ◽  
Food Ingredients ◽  
Content Type ◽  
Whey Powder ◽  
Shotgun Metagenomic Sequencing ◽  
Spoilage Bacteria ◽  
Culture Independent ◽  
Spore Forming Bacteria

ABSTRACT Spoilage and pathogenic spore-forming bacteria are a major cause of concern for producers of dairy products. Traditional agar-based detection methods employed by the dairy industry have limitations with respect to their sensitivity and specificity. The aim of this study was to identify low-abundance sporeformers in samples of a powdered dairy product, whey powder, produced monthly over 1 year, using novel culture-independent shotgun metagenomics-based approaches. Although mesophilic sporeformers were the main target of this study, in one instance thermophilic sporeformers were also targeted using this culture-independent approach. For comparative purposes, mesophilic and thermophilic sporeformers were also tested for within the same sample using culture-based approaches. Ultimately, the approaches taken highlighted differences in the taxa identified due to treatment and isolation methods. Despite this, low levels of transient, mesophilic, and in some cases potentially pathogenic sporeformers were consistently detected in powder samples. Although the specific sporeformers changed from one month to the next, it was apparent that 3 groups of mesophilic sporeformers, namely, Bacillus cereus, Bacillus licheniformis/Bacillus paralicheniformis, and a third, more heterogeneous group containing Brevibacillus brevis, dominated across the 12 samples. Total thermophilic sporeformer taxonomy was considerably different from mesophilic taxonomy, as well as from the culturable thermophilic taxonomy, in the one sample analyzed by all four approaches. Ultimately, through the application of shotgun metagenomic sequencing to dairy powders, the potential for this technology to facilitate the detection of undesirable bacteria present in these food ingredients is highlighted. IMPORTANCE The ability of sporeformers to remain dormant in a desiccated state is of concern from a safety and spoilage perspective in dairy powder. Traditional culturing techniques are slow and provide little information without further investigation. We describe the identification of mesophilic sporeformers present in powders produced over 1 year, using novel shotgun metagenomic sequencing. This method allows detection and identification of possible pathogens and spoilage bacteria in parallel. Strain-level analysis and functional gene analysis, such as identification of toxin genes, were also performed. This approach has the potential to be of great value with respect to the detection of spore-forming bacteria and could allow a processor to make an informed decision surrounding process changes to reduce the risk of spore contamination.

scholarly journals Identification of core and rare species in metagenome samples based on shotgun metagenomic sequencing, Fourier transforms and spectral comparisons

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Marie-Madlen Pust ◽  
Burkhard Tümmler
Keyword(s):  
Microbial Communities ◽  
Rare Species ◽  
Fourier Transforms ◽  
Species Level ◽  
Reference Frequency ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Discrete Fourier Transforms ◽  
False Discovery ◽  
Shotgun Metagenomic Sequencing

AbstractIn shotgun metagenomic sequencing applications, low signal-to-noise ratios may complicate species-level differentiation of genetically similar core species and impede high-confidence detection of rare species. However, core and rare species can take pivotal roles in their habitats and should hence be studied as one entity to gain insights into the total potential of microbial communities in terms of taxonomy and functionality. Here, we offer a solution towards increased species-level specificity, decreased false discovery and omission rates of core and rare species in complex metagenomic samples by introducing the rare species identifier (raspir) tool. The python software is based on discrete Fourier transforms and spectral comparisons of biological and reference frequency signals obtained from real and ideal distributions of short DNA reads mapping towards circular reference genomes. Simulation-based testing of raspir enabled the detection of rare species with genome coverages of less than 0.2%. Species-level differentiation of rare Escherichia coli and Shigella spp., as well as the clear delineation between human Streptococcus spp. was feasible with low false discovery (1.3%) and omission rates (13%). Publicly available human placenta sequencing data were reanalysed with raspir. Raspir was unable to identify placental microbial communities, reinforcing the sterile womb paradigm.

scholarly journals Rapid Diagnostics of Orthopaedic-Implant-Associated Infections Using Nanopore Shotgun Metagenomic Sequencing on Tissue Biopsies

2021 ◽  
Vol 9 (1) ◽  
pp. 97
Author(s):  
J. Christopher Noone ◽  
Karin Helmersen ◽  
Truls Michael Leegaard ◽  
Inge Skråmm ◽  
Hege Vangstein Aamot
Keyword(s):  
Antimicrobial Resistance ◽  
University Hospital ◽  
Orthopaedic Implant ◽  
Metagenomic Sequencing ◽  
Pathogen Identification ◽  
Shotgun Metagenomics ◽  
Microbial Identification ◽  
Conventional Culture ◽  
Shotgun Metagenomic Sequencing ◽  
Antimicrobial Resistance Gene

Conventional culture-based diagnostics of orthopaedic-implant-associated infections (OIAIs) are arduous. Hence, the aim of this study was to evaluate a culture-independent, rapid nanopore-based diagnostic protocol with regard to (a) pathogen identification, (b) time to pathogen identification, and (c) identification of antimicrobial resistance (AMR). This prospective proof-of-concept study included soft tissue biopsies from 32 patients with OIAIs undergoing first revision surgery at Akershus University Hospital, Norway. The biopsies were divided into two segments. Nanopore shotgun metagenomic sequencing and pathogen and antimicrobial resistance gene identification using the EPI2ME analysis platform (Oxford Nanopore Technologies) were performed on one segment. Conventional culture-based diagnostics were performed on the other. Microbial identification matched in 23/32 OIAI patients (72%). Sequencing detected additional microbes in 9/32 patients. Pathogens detected by culturing were identified by sequencing within a median of 1 h of sequencing start [range 1–18 h]. Phenotypic AMR was explained by the detection of resistance genes in 11/23 patients (48%). Diagnostics of OIAIs using shotgun metagenomics sequencing are possible within 24 h from biopsy using nanopore technology. Sequencing outperformed culturing with respect to speed and pathogen detection where pathogens were at sufficient concentration, whereas culture-based methods had an advantage at lower pathogen concentrations. Sequencing-based AMR detection may not yet be a suitable replacement for culture-based antibiotic susceptibility testing.

scholarly journals Abundance tracking by long-read nanopore sequencing of complex microbial communities in samples from 20 different biogas/wastewater plants

2019 ◽  
Author(s):  
Christian Brandt ◽  
Erik Bongcam-Rudloff ◽  
Bettina Müller
Keyword(s):  
Microbial Communities ◽  
Fold Increase ◽  
Green Energy ◽  
Dramatic Improvement ◽  
Metagenomic Sequencing ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Long Reads ◽  
Long Read ◽  
Water Reactors

Abstract Anaerobic digestion (AD) has long been critical technology for green energy, but the majority of the microorganisms involved are unknown and not cultivable, which makes abundance tracking difficult. Developments in nanopore sequencing make it a promising approach for monitoring microbial communities via metagenomic sequencing. For reliable monitoring of AD via long reads, a robust protocol for obtaining less fragmented, high-quality DNA, while preserving bacterial composition, was established. Samples from 20 different biogas/waste-water reactors were investigated and a median of 20 Gb sequencing data per flow cell were retrieved for each reactor. Using the GTDB index allowed sufficient characterisation of abundance of bacteria and archaea in biogas reactors. A dramatic improvement (1.8- to 13-fold increase) in taxonomic classification was achieved using the GTDB-based index compared with the RefSeq index. Ongoing efforts in GTDB to achieve more phylogenetically coherent taxonomic species definitions, including meta-assembled genomes, give a clear advantage over conventional classification databases such as RefSeq. Unlike conventional 16S rRNA studies, metagenomic read classification allows abundance of the unknown microbial fraction to be monitored.

scholarly journals Comparative analysis of 16S rRNA gene and metagenome sequencing in pediatric gut microbiomes

2021 ◽  
Author(s):  
Danielle Peterson ◽  
Kevin S. Bonham ◽  
Sophie Rowland ◽  
Cassandra W. Pattanayak ◽  
Vanja Klepac-Ceraj ◽  
...  
Keyword(s):  
16S Rrna ◽  
Microbial Communities ◽  
Gut Microbiome ◽  
Age Groups ◽  
Alpha Diversity ◽  
Sequencing Depth ◽  
Human Infant ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Shotgun Metagenomic Sequencing

AbstractThe colonization of the human gut microbiome begins at birth, and, over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon versus shotgun metagenomic sequencing techniques in 130 fecal samples; younger than 15, 15-30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.

scholarly journals Abundance tracking by long-read nanopore sequencing of complex microbial communities in samples from 20 different biogas/wastewater plants

2020 ◽  
Author(s):  
Christian Brandt ◽  
Erik Bongcam-Rudloff ◽  
Bettina Müller
Keyword(s):  
Microbial Communities ◽  
Illumina Sequencing ◽  
Fold Increase ◽  
Green Energy ◽  
Dramatic Improvement ◽  
Metagenomic Sequencing ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Long Read ◽  
Genus Richness

Abstract Background: Anaerobic digestion (AD) has long been critical technology for green energy, but the majority of the microorganisms involved are unknown and are currently not cultivable, which makes abundance tracking difficult. Developments in nanopore long-read sequencing make it a promising approach for monitoring microbial communities via metagenomic sequencing. For reliable monitoring of AD via long reads, a robust protocol for obtaining less fragmented, high-quality DNA, while preserving bacteria and archaea composition, was established. Results: Samples from 20 different biogas/wastewater reactors were investigated, and a median of 20.5 Gb sequencing data per nanopore flow cell was retrieved for each reactor using the developed DNA isolation protocol. The nanopore sequencing data was compared against Illumina sequencing data while using different taxonomic indices for read classifications. The Genome Taxonomy Database (GTDB) index allowed sufficient characterisation of the abundance of bacteria and archaea in biogas reactors with a dramatic improvement (1.8- to 13-fold increase) in taxonomic classification compared to the RefSeq index. Both technologies performed similarly in taxonomic read classification with a slight advantage for Illumina in regards to the total proportion of classified reads. However, nanopore sequencing data revealed a higher genus richness after classification. Conclusion: Metagenomic read classification via nanopore provides a promising approach to monitor the abundance of taxa present in a microbial AD community, as an alternative to 16S rRNA studies or Illumina Sequencing.

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