IMMU-09. HUMAN MICROBIOTA INFLUENCE THE EFFICACY OF IMMUNOTHERAPY IN A MOUSE MODEL OF GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi93-vi94
Author(s):  
Kory Dees ◽  
Hyunmin Koo ◽  
James Humphreys ◽  
Joseph Hakim ◽  
David Crossman ◽  
...  
Keyword(s):  
Mouse Model ◽  
Microbial Communities ◽  
Mouse Models ◽  
Gut Microbiome ◽  
Positive Response ◽  
Checkpoint Inhibitors ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Microbial Composition ◽  
Healthy Human

Abstract Although immunotherapy works well in glioblastoma (GBM) pre-clinical mouse models, the therapy has unfortunately not demonstrated efficacy in humans. In melanoma and other cancers, the composition of the gut microbiome has been shown to determine responsiveness or resistance to immune checkpoint inhibitors (anti-PD-1). Most pre-clinical cancer studies have been done in mouse models using mouse gut microbiomes, but there are significant differences between mouse and human microbial gut compositions. To address this inconsistency, we developed a novel humanized microbiome (HuM) model to study the response to immunotherapy in a pre-clinical mouse model of GBM. We used five healthy human donors for fecal transplantation of gnotobiotic mice. After the transplanted microbiomes stabilized, the mice were bred to generate five independent humanized mouse lines (HuM1-HuM5). 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. Interestingly, we found that the HuM lines responded differently to anti-PD-1. Specifically, we demonstrate that HuM2 and HuM3 mice are responsive to anti-PD-1 and displayed significantly increased survival compared to isotype controls, while HuM1, HuM4, and HuM5 mice are resistant to anti-PD-1. These mice are genetically identical, and only differ in the composition of the gut microbiome. In a correlative experiment, we found that disrupting the responder HuM2 microbiome with antibiotics abrogated the positive response to anti-PD-1, indicating that HuM2 microbiota must be present in the mice to elicit the positive response to anti-PD-1 in the GBM model. The question remains of whether the “responsive” microbial communities in HuM2 and HuM3 can be therapeutically exploited and applicable in other tumor models, or if the “resistant” microbial communities in HuM1, HuM4, and HuM5 can be depleted and/or replaced. Future studies will assess responder microbial transplants as a method of enhancing immunotherapy.

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 TMOD-19. INDIVIDUAL SPECIFIC HUMAN GUT MICROBE COMMUNITIES INFLUENCE RESPONSE TO IMMUNOTHERAPY IN A HUMANIZED MICROBIOME MOUSE MODEL OF GLIOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii232-ii232
Author(s):  
Kory Dees ◽  
Hyunmin Koo ◽  
J Fraser Humphreys ◽  
Joseph Hakim ◽  
David Crossman ◽  
...  
Keyword(s):  
Mouse Model ◽  
Microbial Community Composition ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Microbial Composition ◽  
Healthy Human ◽  
Fecal Transplantation ◽  
Microbiome Composition ◽  
Gut Microbe ◽  
Mouse Lines

Abstract Although immunotherapy works well in glioblastoma (GBM) pre-clinical mouse models, the therapy has not demonstrated efficacy in GBM patients. Since recent studies have linked the gut microbial composition to the success with immunotherapy for other cancers, we utilized a novel humanized microbiome (HuM) model in order to study the response to immunotherapy in a pre-clinical mouse model of GBM. We used five healthy human donors for fecal transplantation of gnotobiotic mice since it is now recognized that microbe strain level differences render individual humans with a unique microbial community composition. After the transplanted microbiomes stabilized, the mice were bred to generate 5 independent humanized mouse lines (humanized microbiome HuM1-HuM5). Analysis of shotgun metagenomic sequencing data from fecal samples revealed a unique microbiome composition with significant differences in diversity and microbial composition among HuM1-HuM5 lines. We next analyzed the growth of intracranial glioma cells in the HuM lines. All HuM mouse lines were susceptible to GBM transplantation, and exhibited similar median survival ranging from 19-26 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 non-responders to anti-PD-1 resulting in the death of the mice from the intracranial tumors, 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 HuM2 and HuM3 were closely related. Detailed taxonomic comparison analysis at the top 5 across all HuM mouse lines revealed that Bacteroides cellulosilyticus was commonly found between HuM2 and HuM3 with high abundances. The results of our study establish the utility of humanized microbiome mice as avatars to delineate features of the host interaction with gut microbe communities needed for effective immunotherapy against GBM.

scholarly journals Development of Inflammatory Bowel Disease Is Linked to a Longitudinal Restructuring of the Gut Metagenome in Mice

mSystems ◽  
2017 ◽  
Vol 2 (5) ◽  
Author(s):  
Thomas Sharpton ◽  
Svetlana Lyalina ◽  
Julie Luong ◽  
Joey Pham ◽  
Emily M. Deal ◽  
...  
Keyword(s):  
Mouse Model ◽  
Microbial Communities ◽  
Immune Activation ◽  
Gut Microbiome ◽  
Longitudinal Design ◽  
Disease Onset ◽  
Mixed Effects ◽  
Metagenomic Sequencing ◽  
Early Biomarkers ◽  
Host Microbe Interactions

ABSTRACT IBD patients harbor distinct microbial communities with functional capabilities different from those seen with healthy people. But is this cause or effect? Answering this question requires data on changes in gut microbial communities leading to disease onset. By performing weekly metagenomic sequencing and mixed-effects modeling on an established mouse model of IBD, we identified several functional pathways encoded by the gut microbiome that covary with host immune status. These pathways are novel early biomarkers that may either enable microbes to live inside an inflamed gut or contribute to immune activation in IBD mice. Future work will validate the potential roles of these microbial pathways in host-microbe interactions and human disease. This study was novel in its longitudinal design and focus on microbial pathways, which provided new mechanistic insights into the role of gut microbes in IBD development. The gut microbiome is linked to inflammatory bowel disease (IBD) severity and altered in late-stage disease. However, it is unclear how gut microbial communities change over the course of IBD development, especially in regard to function. To investigate microbiome-mediated disease mechanisms and discover early biomarkers of IBD, we conducted a longitudinal metagenomic investigation in an established mouse model of IBD, where damped transforming growth factor β (TGF-β) signaling in T cells leads to peripheral immune activation, weight loss, and severe colitis. IBD development is associated with abnormal gut microbiome temporal dynamics, including damped acquisition of functional diversity and significant differences in abundance trajectories for KEGG modules such as glycosaminoglycan degradation, cellular chemotaxis, and type III and IV secretion systems. Most differences between sick and control mice emerge when mice begin to lose weight and heightened T cell activation is detected in peripheral blood. However, levels of lipooligosaccharide transporter abundance diverge prior to immune activation, indicating that it could be a predisease indicator or microbiome-mediated disease mechanism. Taxonomic structure of the gut microbiome also significantly changes in association with IBD development, and the abundances of particular taxa, including several species of Bacteroides, correlate with immune activation. These discoveries were enabled by our use of generalized linear mixed-effects models to test for differences in longitudinal profiles between healthy and diseased mice while accounting for the distributions of taxon and gene counts in metagenomic data. These findings demonstrate that longitudinal metagenomics is useful for discovering the potential mechanisms through which the gut microbiome becomes altered in IBD. IMPORTANCE IBD patients harbor distinct microbial communities with functional capabilities different from those seen with healthy people. But is this cause or effect? Answering this question requires data on changes in gut microbial communities leading to disease onset. By performing weekly metagenomic sequencing and mixed-effects modeling on an established mouse model of IBD, we identified several functional pathways encoded by the gut microbiome that covary with host immune status. These pathways are novel early biomarkers that may either enable microbes to live inside an inflamed gut or contribute to immune activation in IBD mice. Future work will validate the potential roles of these microbial pathways in host-microbe interactions and human disease. This study was novel in its longitudinal design and focus on microbial pathways, which provided new mechanistic insights into the role of gut microbes in IBD development.

scholarly journals TMOD-19. ELUCIDATING THE RESISTANCE TO IMMUNOTHERAPY IN BRAIN TUMORS USING A HUMANIZED MICROBIOME MOUSE MODEL

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi266-vi266
Author(s):  
Kory Dees ◽  
Hyunmin Koo ◽  
Joseph Hakim ◽  
J Fraser Humphreys ◽  
David Crossman ◽  
...  
Keyword(s):  
Mouse Model ◽  
Tumor Growth ◽  
Mouse Models ◽  
Gut Microbiome ◽  
Standard Of Care ◽  
Similar Efficacy ◽  
Healthy Human ◽  
Human Donor ◽  
Microbiome Composition ◽  
Gut Microbe

Abstract Although the immunotherapy anti-PD-1 works well in glioblastoma (GBM) pre-clinical mouse models, the therapy has not demonstrated a similar efficacy in patient clinical trials. Recent studies have linked the gut microbe composition to tumor growth and response to immunotherapy in some cancers. To date, all GBM pre-clinical studies have been done in mouse models using mouse gut microbiomes. There are significant differences between mouse and human microbial gut compositions, with up to 85% of gut bacteria found in laboratory mice not found in humans. Because it is known that the gut microbe composition can impact the immune system, we hypothesize that the non-responsiveness of GBM patients to immunotherapy may be due to the composition of the gut microbiome. Therefore, we have generated a humanized microbiome mouse model in which mice have been colonized by human donor microbes in their GI tract (two different healthy human donors (HuM1 and HuM2)). In preliminary results, we have found that HuM1 mice are resistant to anti-PD-1, while HuM2 mice are responders to anti-PD-1 in the GL261 syngeneic intracranial model. These mice are genetically identical and only differ in gut microbiome composition. Furthermore, we found that HuM2 mice exhibited a significant increase in cytotoxic CD8+T-cells producing IFN-γ and significant increased CD8+/Treg ratio in the spleen following anti-PD-1 treatment, which was not observed in the HuM1 mice. When testing the efficacy of standard of care temozolomide (TMZ) in our humanized mice, we found that TMZ significantly prolonged survival of both HuM1 and HuM2 mice with intracranial tumors. However, HuM2 mice exhibited superior efficacy (p< 0.001; 57% survival), compared to HuM1 mice (p< 0.01; 0% survival). We are extending these studies to analyze additional humanized microbiome lines as well as GBM patient donor lines to more accurately understand individual responses to tumor growth and responsiveness to therapies.

scholarly journals Integrating Metagenomics into Personalized Medicine in Dermatology

2020 ◽  
Vol 4 (6) ◽  
pp. 623-625
Author(s):  
Amy Huang ◽  
Sharon Glick
Keyword(s):  
Atopic Dermatitis ◽  
Personalized Medicine ◽  
Gut Microbiome ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Therapy Response ◽  
Skin Microbiome ◽  
Metagenomic Sequencing ◽  
Microbial Composition

There has been a recent focus on the association between human microbiomes and disease development, disease resistance, and therapy response. Fecal transplants for inflammatory bowel disease and resistant Clostridium difficile infection have demonstrated that manipulating the gut microbiome can be beneficial in treating disease. Microbiomes are important in dermatology, where response to immune checkpoint inhibitors for melanoma therapy can be affected by differences in gut microbial composition. Bleach baths, which alter the skin microbiome, are known to be beneficial in atopic dermatitis. Gut dysbiosis, or disturbance in the gut microbiome in early life, can influence the development of systemic sclerosis and atopic dermatitis. Metagenomic sequencing can therefore be a useful addition to personalized medicine to identify therapy responders versus non-responders, patients at risk of serious side-effects from biologics and immune checkpoint inhibitors, and prebiotic supplements that aid in improving therapy response.

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 Phylogenetic Molecular Ecological Network of Soil Microbial Communities in Response to Elevated CO2

mBio ◽  
2011 ◽  
Vol 2 (4) ◽  
Author(s):  
Jizhong Zhou ◽  
Ye Deng ◽  
Feng Luo ◽  
Zhili He ◽  
Yunfeng Yang
Keyword(s):  
Microbial Communities ◽  
Microbial Ecology ◽  
High Throughput ◽  
Network Topology ◽  
Ecosystem Functioning ◽  
Soil Microbial Communities ◽  
Microbial Populations ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Soil Microbial

ABSTRACT Understanding the interactions among different species and their responses to environmental changes, such as elevated atmospheric concentrations of CO2, is a central goal in ecology but is poorly understood in microbial ecology. Here we describe a novel random matrix theory (RMT)-based conceptual framework to discern phylogenetic molecular ecological networks using metagenomic sequencing data of 16S rRNA genes from grassland soil microbial communities, which were sampled from a long-term free-air CO2 enrichment experimental facility at the Cedar Creek Ecosystem Science Reserve in Minnesota. Our experimental results demonstrated that an RMT-based network approach is very useful in delineating phylogenetic molecular ecological networks of microbial communities based on high-throughput metagenomic sequencing data. The structure of the identified networks under ambient and elevated CO2 levels was substantially different in terms of overall network topology, network composition, node overlap, module preservation, module-based higher-order organization, topological roles of individual nodes, and network hubs, suggesting that the network interactions among different phylogenetic groups/populations were markedly changed. Also, the changes in network structure were significantly correlated with soil carbon and nitrogen contents, indicating the potential importance of network interactions in ecosystem functioning. In addition, based on network topology, microbial populations potentially most important to community structure and ecosystem functioning can be discerned. The novel approach described in this study is important not only for research on biodiversity, microbial ecology, and systems microbiology but also for microbial community studies in human health, global change, and environmental management. IMPORTANCE The interactions among different microbial populations in a community play critical roles in determining ecosystem functioning, but very little is known about the network interactions in a microbial community, owing to the lack of appropriate experimental data and computational analytic tools. High-throughput metagenomic technologies can rapidly produce a massive amount of data, but one of the greatest difficulties is deciding how to extract, analyze, synthesize, and transform such a vast amount of information into biological knowledge. This study provides a novel conceptual framework to identify microbial interactions and key populations based on high-throughput metagenomic sequencing data. This study is among the first to document that the network interactions among different phylogenetic populations in soil microbial communities were substantially changed by a global change such as an elevated CO2 level. The framework developed will allow microbiologists to address research questions which could not be approached previously, and hence, it could represent a new direction in microbial ecology research.

scholarly journals Strain Structure and Dynamics Revealed by Targeted Deep Sequencing of the Honey Bee Gut Microbiome

mSphere ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Louis-Marie Bobay ◽  
Emily F. Wissel ◽  
Kasie Raymann
Keyword(s):  
Microbial Communities ◽  
Honey Bee ◽  
Deep Sequencing ◽  
Gut Microbiome ◽  
Cost Effective ◽  
Whole Genome Shotgun ◽  
Strain Level ◽  
Whole Genome ◽  
Metagenomic Sequencing ◽  
Microbiome Composition

ABSTRACT Host-associated microbiomes can be critical for the health and proper development of animals and plants. The answers to many fundamental questions regarding the modes of acquisition and microevolution of microbiome communities remain to be established. Deciphering strain-level dynamics is essential to fully understand how microbial communities evolve, but the forces shaping the strain-level dynamics of microbial communities remain largely unexplored, mostly because of methodological issues and cost. Here, we used targeted strain-level deep sequencing to uncover the strain dynamics within a host-associated microbial community using the honey bee gut microbiome as a model system. Our results revealed that amplicon sequencing of conserved protein-coding gene regions using species-specific primers is a cost-effective and accurate method for exploring strain-level diversity. In fact, using this method we were able to confirm strain-level results that have been obtained from whole-genome shotgun sequencing of the honey bee gut microbiome but with a much higher resolution. Importantly, our deep sequencing approach allowed us to explore the impact of low-frequency strains (i.e., cryptic strains) on microbiome dynamics. Results show that cryptic strain diversity is not responsible for the observed variations in microbiome composition across bees. Altogether, the findings revealed new fundamental insights regarding strain dynamics of host-associated microbiomes. IMPORTANCE The factors driving fine-scale composition and dynamics of gut microbial communities are poorly understood. In this study, we used metagenomic amplicon deep sequencing to decipher the strain dynamics of two key members of the honey bee gut microbiome. Using this high-throughput and cost-effective approach, we were able to confirm results from previous large-scale whole-genome shotgun (WGS) metagenomic sequencing studies while also gaining additional insights into the community dynamics of two core members of the honey bee gut microbiome. Moreover, we were able to show that cryptic strains are not responsible for the observed variations in microbiome composition across bees.

A Novel Probiotic Formula, BIOCG, Protects Against Alzheimer’s-Related Cognitive Deficits via Regulation of Dendritic Spine Dynamics

2021 ◽  
Vol 18 ◽  
Author(s):  
Miao Sun ◽  
Wenchenyang Bao ◽  
Chengyu Huang ◽  
Ziyue Xia ◽  
Changliang Zhang ◽  
...  
Keyword(s):  
Dendritic Spine ◽  
Gut Microbiome ◽  
Long Term Potentiation ◽  
Functional Improvement ◽  
Sequencing Data ◽  
Microbial Composition ◽  
App Processing ◽  
Probiotic Treatment ◽  
The Impact ◽  
Spine Dynamics

Background: The brain-gut-microbiome axis has emerged as an important pathway through which perturbations in the gut and/or microbial microenvironment can impact neurological function. Such alterations have been implicated in a variety of neuropsychiatric disorders, includ- ing depression, anxiety, and Alzheimer’s Disease (AD) and the use of probiotics as therapy for th- ese diseases remains promising. However, the mechanisms underlying the gut microenvironment’s influence on disease pathogenesis and therapy remain unclear. Objective: The objective of this study is to investigate the effect of a novel probiotic formula, BIOCG, on cognitive function and pathobiological mechanisms, including amyloid processing and dendritic spine dynamics, in a mouse model of AD. Methods: BIOCG was administered for 3 months to 3xTg or 3xTg; Thy1-YFP AD mice and func- tional outcomes were assessed via behavioral testing and electrophysiology. Mechanisms relevant to AD pathogenesis including dendritic spine morphology and turnover, Amyloid Precursor Pro- tein (APP) processing and microglial phenotype were also evaluated. Finally, we sequenced fecal samples following probiotic treatment to assess the impact on gut microbial composition and corre- late the changes with the above described measures. Results: Mice treated with BIOCG demonstrated preserved cognitive abilities and stronger Long- Term Potentiation (LTP), spontaneous Excitatory Postsynaptic Currents (sEPSC), and glutamate-in- duced LTPs, indicative of functional and electrophysiological effects. Moreover, we observed atten- uated AD pathogenesis, including reduced Amyloid Beta (Aβ) burden, as well as more mature den- dritic spines in the BIOCG-treated. Our finding of changes in microglial number and phenotype in the treatment group suggests that this formulation may mediate its effects via attenuation of neu- roinflammation. Sequencing data confirmed that the gut microbiome in treated mice was more varied and harbored a greater proportion of “beneficial” bacteria. Conclusion: Overall, our results indicate that treatment with BIOCG enhances microbial diversity and, through gut-brain axis interactions, attenuates neuroinflammation to produce histologic and functional improvement in AD pathogenesis.

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.

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