scholarly journals Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community

2020 ◽  
Vol 8 (12) ◽  
pp. 1861
Author(s):  
Claudia Sala ◽  
Hanne Mordhorst ◽  
Josephine Grützke ◽  
Annika Brinkmann ◽  
Thomas N. Petersen ◽  
...  
Keyword(s):  
Proficiency Test ◽  
Metagenomic Sequencing ◽  
Food Matrix ◽  
Community Members ◽  
Mock Community ◽  
Sequencing Platform ◽  
Shotgun Metagenomic Sequencing ◽  
Smoked Salmon ◽  
Genomic Tool ◽  
Wet Lab

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

scholarly journals Evaluation of methods for the reduction of contaminating host reads when performing shotgun metagenomic sequencing of the milk microbiome

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Min Yap ◽  
Conor Feehily ◽  
Calum J. Walsh ◽  
Mark Fenelon ◽  
Eileen F. Murphy ◽  
...  
Keyword(s):  
Human Milk ◽  
Sequencing Depth ◽  
Metagenomic Sequencing ◽  
Mock Community ◽  
Milk Samples ◽  
Optimal Classifier ◽  
Shotgun Metagenomic Sequencing ◽  
Functional Profiling ◽  
Microbial Dna

AbstractShotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.

scholarly journals Culture-Independent Genotyping, Virulence and Antimicrobial Resistance Gene Identification of Staphylococcus aureus from Orthopaedic Implant-Associated Infections

2021 ◽  
Vol 9 (4) ◽  
pp. 707
Author(s):  
J. Christopher Noone ◽  
Fabienne Antunes Ferreira ◽  
Hege Vangstein Aamot
Keyword(s):  
Staphylococcus Aureus ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Virulence Gene ◽  
Orthopaedic Implant ◽  
Metagenomic Sequencing ◽  
Gene Detection ◽  
Shotgun Metagenomic Sequencing ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent

Our culture-independent nanopore shotgun metagenomic sequencing protocol on biopsies has the potential for same-day diagnostics of orthopaedic implant-associated infections (OIAI). As OIAI are frequently caused by Staphylococcus aureus, we included S. aureus genotyping and virulence gene detection to exploit the protocol to its fullest. The aim was to evaluate S. aureus genotyping, virulence and antimicrobial resistance genes detection using the shotgun metagenomic sequencing protocol. This proof of concept study included six patients with S. aureus-associated OIAI at Akershus University Hospital, Norway. Five tissue biopsies from each patient were divided in two: (1) conventional microbiological diagnostics and genotyping, and whole genome sequencing (WGS) of S. aureus isolates; (2) shotgun metagenomic sequencing of DNA from the biopsies. Consensus sequences were analysed using spaTyper, MLST, VirulenceFinder, and ResFinder from the Center for Genomic Epidemiology (CGE). MLST was also compared using krocus. All spa-types, one CGE and four krocus MLST results matched Sanger sequencing results. Virulence gene detection matched between WGS and shotgun metagenomic sequencing. ResFinder results corresponded to resistance phenotype. S. aureus spa-typing, and identification of virulence and antimicrobial resistance genes are possible using our shotgun metagenomics protocol. MLST requires further optimization. The protocol has potential application to other species and infection types.

scholarly journals Discriminating between JCPyV and BKPyV in Urinary Virome Data Sets

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1041
Author(s):  
Rita Mormando ◽  
Alan J. Wolfe ◽  
Catherine Putonti
Keyword(s):  
Jc Virus ◽  
Sequence Similarity ◽  
Bk Virus ◽  
Data Sets ◽  
Metagenomic Sequencing ◽  
Significant Sequence Similarity ◽  
Sequence Identity ◽  
Shotgun Metagenomic Sequencing ◽  
Urinary Microbiome ◽  
Six Genes

Polyomaviruses are abundant in the human body. The polyomaviruses JC virus (JCPyV) and BK virus (BKPyV) are common viruses in the human urinary tract. Prior studies have estimated that JCPyV infects between 20 and 80% of adults and that BKPyV infects between 65 and 90% of individuals by age 10. However, these two viruses encode for the same six genes and share 75% nucleotide sequence identity across their genomes. While prior urinary virome studies have repeatedly reported the presence of JCPyV, we were interested in seeing how JCPyV prevalence compares to BKPyV. We retrieved all publicly available shotgun metagenomic sequencing reads from urinary microbiome and virome studies (n = 165). While one third of the data sets produced hits to JCPyV, upon further investigation were we able to determine that the majority of these were in fact BKPyV. This distinction was made by specifically mining for JCPyV and BKPyV and considering uniform coverage across the genome. This approach provides confidence in taxon calls, even between closely related viruses with significant sequence similarity.

scholarly journals 673 Precision microbiome mapping identifies a microbiome signature predictive of Immune checkpoint inhibitor response across multiple research study cohorts

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A711-A711
Author(s):  
Matthew Robinson ◽  
Kevin Vervier ◽  
Simon Harris ◽  
David Adams ◽  
Doreen Milne ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Advanced Melanoma ◽  
List Type ◽  
Metagenomic Sequencing ◽  
Genome Database ◽  
Sequencing Platform ◽  
Melanoma Patients

BackgroundThe gut microbiome of cancer patients appears to be associated with response to Immune Checkpoint Inhibitor (ICIs) treatment.1–4 However, the bacteria linked to response differ between published studies.MethodsLongitudinal stool samples were collected from 69 patients with advanced melanoma receiving approved ICIs in the Cambridge (UK) MELRESIST study. Pretreatment samples were analysed by Microbiotica, using shotgun metagenomic sequencing. Microbiotica’s sequencing platform comprises the world’s leading Reference Genome Database and advanced Microbiome Bioinformatics to give the most comprehensive and precise mapping of the gut microbiome. This has enabled us to identify gut bacteria associated with ICI response missed using public reference genomes. Published microbiome studies in advanced melanoma,1–3renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC)4 were reanalysed with the same platform.ResultsAnalysis of the MELRESIST samples showed an overall change in the microbiome composition between advanced melanoma patients and a panel of healthy donor samples, but not between patients who subsequently responded or did not respond to ICIs. However, we did identify a discrete microbiome signature which correlated with response. This signature predicted response with an accuracy of 93% in the MELRESIST cohort, but was less predictive in the published melanoma cohorts.1–3 Therefore, we developed a bioinformatic analytical model, incorporating an interactive random forest model and the MELRESIST dataset, to identify a microbiome signature which was consistent across all published melanoma studies. This model was validated three times by accurately predicting the outcome of an independent cohort. A final microbiome signature was defined using the validated model on MELRESIST and the three published melanoma cohorts. This was very accurate at predicting response in all four studies combined (91%), or individually (82–100%). This signature was also predictive of response in a NSCLC study and to a lesser extent in RCC. The core of this signature is nine bacteria significantly increased in abundance in responders.ConclusionsAnalysis of the MELRESIST study samples, precision microbiome profiling by the Microbiotica Platform and a validated bioinformatic analysis, have enabled us to identify a unique microbiome signature predictive of response to ICI therapy in four independent melanoma studies. This removes the challenge to the field of different bacteria apparently being associated with response in different studies, and could represent a new microbiome biomarker with clinical application. Nine core bacteria may be driving response and hold potential for co-therapy with ICIs.Ethics ApprovalThe study was approved by Newcastle & North Tyneside 2 Research Ethics Committee, approval number 11/NE/0312.ReferencesMatson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 2018;359(6371):104–108.Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018;359(6371):97–103.Frankel AE, Coughlin LA, Kim J, et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 2017;19(10):848–855.Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359(6371):91–97.

Microbiome population dynamics of cold smoked sockeye salmon during refrigerated storage and after culture enrichment

2021 ◽  
Author(s):  
Karen Jarvis ◽  
Chiun-Kang Hsu ◽  
James B. Pettengill ◽  
John Ihrie ◽  
Hiren Karathia ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Foodborne Pathogens ◽  
Sockeye Salmon ◽  
Pathogen Detection ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Smoked Salmon ◽  
Spoilage Bacteria ◽  
Culture Enrichment ◽  
Processing And Storage

Cold smoked salmon is a ready-to-eat seafood product of high commercial importance. The processing and storage steps facilitate the introduction, growth and persistence of foodborne pathogens and spoilage bacteria. The growth of commensal bacteria during storage and once the product is opened also influence the quality and safety of cold smoked salmon. Here we investigated the microbial community through targeted 16s rRNA gene and shotgun metagenomic sequencing, as means to better understand the interactions among bacteria in cold smoked salmon. Cold smoked salmon samples were tested over 30 days of aerobic storage at 4℃ and cultured at each timepoint in buffered Listeria enrichment broth (BLEB) commonly used to detect Listeria in foods. The microbiomes were comprised of Firmicutes and Proteobacteria namely, Carnobacterium , Brochothrix , Pseudomonas , Serratia , and Psychrobacter . Pseudomonas species were the most diverse species with 181 taxa identified. Additionally, we identified potential homologs to 10 classes of bacteriocins in microbiomes of cold smoked salmon stored at 4°C and corresponding BLEB culture enrichments. The findings presented here contribute to our understanding of microbiome population dynamics in cold smoked salmon, including changes in bacterial taxa during aerobic cold storage and after culture enrichment.  This may facilitate improvements to pathogen detection and quality preservation of this food.

scholarly journals Evaluation of the CosmosID Bioinformatics Platform for Prosthetic Joint-Associated Sonicate Fluid Shotgun Metagenomic Data Analysis

2018 ◽  
Vol 57 (2) ◽  
Author(s):  
Qun Yan ◽  
Yu Mi Wi ◽  
Matthew J. Thoendel ◽  
Yash S. Raval ◽  
Kerryl E. Greenwood-Quaintance ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Antibacterial Resistance ◽  
Sequencing Data ◽  
Bacterial Detection ◽  
Shotgun Metagenomic Sequencing ◽  
Prosthetic Joint ◽  
Validation Set ◽  
Fluid Culture

ABSTRACT We previously demonstrated that shotgun metagenomic sequencing can detect bacteria in sonicate fluid, providing a diagnosis of prosthetic joint infection (PJI). A limitation of the approach that we used is that data analysis was time-consuming and specialized bioinformatics expertise was required, both of which are barriers to routine clinical use. Fortunately, automated commercial analytic platforms that can interpret shotgun metagenomic data are emerging. In this study, we evaluated the CosmosID bioinformatics platform using shotgun metagenomic sequencing data derived from 408 sonicate fluid samples from our prior study with the goal of evaluating the platform vis-à-vis bacterial detection and antibiotic resistance gene detection for predicting staphylococcal antibacterial susceptibility. Samples were divided into a derivation set and a validation set, each consisting of 204 samples; results from the derivation set were used to establish cutoffs, which were then tested in the validation set for identifying pathogens and predicting staphylococcal antibacterial resistance. Metagenomic analysis detected bacteria in 94.8% (109/115) of sonicate fluid culture-positive PJIs and 37.8% (37/98) of sonicate fluid culture-negative PJIs. Metagenomic analysis showed sensitivities ranging from 65.7 to 85.0% for predicting staphylococcal antibacterial resistance. In conclusion, the CosmosID platform has the potential to provide fast, reliable bacterial detection and identification from metagenomic shotgun sequencing data derived from sonicate fluid for the diagnosis of PJI. Strategies for metagenomic detection of antibiotic resistance genes for predicting staphylococcal antibacterial resistance need further development.

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 Bacterial secondary metabolite biosynthetic potential in soil varies with phylum, depth, and vegetation type

2019 ◽  
Author(s):  
Allison M. Sharrar ◽  
Alexander Crits-Christoph ◽  
Raphaël Méheust ◽  
Spencer Diamond ◽  
Evan P. Starr ◽  
...  
Keyword(s):  
Secondary Metabolite ◽  
Vegetation Type ◽  
Bacterial Species ◽  
Gene Clusters ◽  
Metagenomic Sequencing ◽  
Soil Bacterial Diversity ◽  
Community Members ◽  
Clinical Value ◽  
Specialized Metabolites ◽  
Shallow Soils

AbstractBacteria isolated from soils are major sources of specialized metabolites, including antibiotics and other compounds with clinical value that likely shape interactions among microbial community members and impact biogeochemical cycles. Yet, isolated lineages represent a small fraction of all soil bacterial diversity. It remains unclear how the production of specialized metabolites varies across the phylogenetic diversity of bacterial species in soils, and whether the genetic potential for production of these metabolites differs with soil type. We sampled soils and saprolite from three sites in a northern California Critical Zone Observatory with varying vegetation and bedrock characteristics and used metagenomic sequencing and assembly to reconstruct 1,334 microbial genomes containing diverse biosynthetic gene clusters (BGCs) for secondary metabolite production. We obtained genomes for prolific producers of secondary metabolites, including novel groups within the Actinobacteria, Chloroflexi and candidate phylum Dormibactereota. Surprisingly, one genome of a Candidate Phyla Radiation bacterium encoded for a ribosomally synthesized linear azole/azoline-containing peptide, a capacity we found in other publicly available CPR bacterial genomes. Overall, bacteria with higher biosynthetic potential were enriched in shallow soils and grassland soils, with patterns of abundance of BGC type varying by taxonomy.

scholarly journals Yoghurt Consumption is Associated With Transient Changes in the Composition of the Human Gut Microbiome

2020 ◽  
Author(s):  
Caroline Ivanne Le Roy ◽  
Alexander Kurilshikov ◽  
Emily Leeming ◽  
Alessia Visconti ◽  
Ruth Bowyer ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
Visceral Fat ◽  
Gut Microbiome ◽  
Body Weight Gain ◽  
Healthy Eating Index ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Shotgun Metagenomic Sequencing

Abstract Background: Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. Results: According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17±0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18±11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41±0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30±0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed that increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation.Conclusions: Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).

scholarly journals The human microbiome in hematopoiesis and hematologic disorders

Blood ◽  
2015 ◽  
Vol 126 (3) ◽  
pp. 311-318 ◽  
Author(s):  
Veronica E. Manzo ◽  
Ami S. Bhatt
Keyword(s):  
Community Structure ◽  
Human Health ◽  
Ribosomal Rna ◽  
Human Microbiome ◽  
Human Cells ◽  
Metagenomic Sequencing ◽  
Hematologic Disorders ◽  
Hematologic Diseases ◽  
Shotgun Metagenomic Sequencing

AbstractHumans are now understood to be in complex symbiosis with a diverse ecosystem of microbial organisms, including bacteria, viruses, and fungi. Efforts to characterize the role of these microorganisms, commonly referred as the microbiota, in human health have sought to answer the fundamental questions of what organisms are present, how are they functioning to interact with human cells, and by what mechanism are these interactions occurring. In this review, we describe recent efforts to describe the microbiota in healthy and diseased individuals, summarize the role of various molecular technologies (ranging from 16S ribosomal RNA to shotgun metagenomic sequencing) in enumerating the community structure of the microbiota, and explore known interactions between the microbiota and humans, with a focus on the microbiota’s role in hematopoiesis and hematologic diseases.

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