Abstract (Expand)

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

Authors: P. Patumcharoenpol, M. Nakphaichit, Gianni Panagiotou, A. Senavonge, N. Suratannon, W. Vongsangnak

Date Published: 6th Jan 2021

Journal: PLoS Comput Biol

Abstract (Expand)

Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal-bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.

Authors: Mohammad Mirhakkak, Sascha Schäuble, Tilman Klassert, S. Brunke, Philipp Brandt, D. Loos, R. V. Uribe, F. Senne de Oliveira Lino, Y. Ni, Slavena Vylkova, Hortense Slevogt, Bernhard Hube, Esther Weiß, M. O. A. Sommer, Gianni Panagiotou

Date Published: 15th Dec 2020

Journal: ISME J

Abstract (Expand)

Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is both an environmental saprobe and an opportunistic human fungal pathogen, resistance is suggested to arise from fungicide use in agriculture, as the azoles used for plant protection share the same molecular target as the frontline antifungals used clinically. However, limiting azole fungicide use on crop fields to preserve their activity for clinical use could threaten the global food supply via a reduction in yield. In this study, we clarify the link between azole fungicide use on crop fields and resistance in a prototypical human pathogen through systematic soil sampling on farms in Germany and surveying fields before and after fungicide application. We observed a reduction in the abundance of A. fumigatus on fields following fungicide treatment in 2017, a finding that was not observed on an organic control field with only natural plant protection agents applied. However, this finding was less pronounced during our 2018 sampling, indicating that the impact of fungicides on A. fumigatus population size is variable and influenced by additional factors. The overall resistance frequency among agricultural isolates is low, with only 1 to 3% of isolates from 2016 to 2018 displaying resistance to medical azoles. Isolates collected after the growing season and azole exposure show a subtle but consistent decrease in susceptibility to medical and agricultural azoles. Whole-genome sequencing indicates that, despite the alterations in antifungal susceptibility, fungicide application does not significantly affect the population structure and genetic diversity of A. fumigatus in fields. Given the low observed resistance rate among agricultural isolates as well the lack of genomic impact following azole application, we do not find evidence that azole use on crops is significantly driving resistance in A. fumigatus in this context.IMPORTANCE Antibiotic resistance is an increasing threat to human health. In the case of Aspergillus fumigatus, which is an environmental fungus that also causes life-threatening infections in humans, antimicrobial resistance is suggested to arise from fungicide use in agriculture, as the chemicals used for plant protection are almost identical to the antifungals used clinically. However, removing azole fungicides from crop fields threatens the global food supply via a reduction in yield. In this study, we survey crop fields before and after fungicide application. We find a low overall azole resistance rate among agricultural isolates, as well as a lack of genomic and population impact following fungicide application, leading us to conclude azole use on crops does not significantly contribute to resistance in A. fumigatus.

Authors: A. E. Barber, J. Riedel, T. Sae-Ong, K. Kang, W. Brabetz, Gianni Panagiotou, H. B. Deising, Oliver Kurzai

Date Published: 24th Nov 2020

Journal: mBio

Abstract (Expand)

High-throughput RNA sequencing (RNA-seq) is routinely applied to study diverse biological processes; however, when performed separately on interacting organisms, systemic noise intrinsic to RNA extraction, library preparation, and sequencing hampers the identification of cross-species interaction nodes. Here, we develop triple RNA-seq to simultaneously detect transcriptomes of monocyte-derived dendritic cells (moDCs) infected with the frequently co-occurring pulmonary pathogens Aspergillus fumigatus and human cytomegalovirus (CMV). Comparing expression patterns after co-infection with those after single infections, our data reveal synergistic effects and mutual interferences between host responses to the two pathogens. For example, CMV attenuates the fungus-mediated activation of pro-inflammatory cytokines through NF-kappaB (nuclear factor kappaB) and NFAT (nuclear factor of activated T cells) cascades, while A. fumigatus impairs viral clearance by counteracting viral nucleic acid-induced activation of type I interferon signaling. Together, the analytical power of triple RNA-seq proposes molecular hubs in the differential moDC response to fungal/viral single infection or co-infection that contribute to our understanding of the etiology and, potentially, clearance of post-transplant infections.

Authors: Bastian Seelbinder, J. Wallstabe, Lothar Marischen, Esther Weiß, S. Wurster, L. Page, C. Loffler, L. Bussemer, A. L. Schmitt, Thomas Wolf, Jörg Linde, L. Cicin-Sain, J. Becker, U. Kalinke, J. Vogel, Gianni Panagiotou, Hermann Einsele, A. J. Westermann, Sascha Schäuble, Jürgen Löffler

Date Published: 17th Nov 2020

Journal: Cell Rep

Abstract (Expand)

BACKGROUND: Antibiotic treatment has a well-established detrimental effect on the gut bacterial composition, but effects on the fungal community are less clear. Bacteria in the lumen of the gastrointestinal tract may limit fungal colonization and invasion. Antibiotic drugs targeting bacteria are therefore seen as an important risk factor for fungal infections and induced allergies. However, antibiotic effects on gut bacterial-fungal interactions, including disruption and resilience of fungal community compositions, were not investigated in humans. We analysed stool samples collected from 14 healthy human participants over 3 months following a 6-day antibiotic administration. We integrated data from shotgun metagenomics, metatranscriptomics, metabolomics, and fungal ITS2 sequencing. RESULTS: While the bacterial community recovered mostly over 3 months post treatment, the fungal community was shifted from mutualism at baseline to competition. Half of the bacterial-fungal interactions present before drug intervention had disappeared 3 months later. During treatment, fungal abundances were associated with the expression of bacterial genes with functions for cell growth and repair. By extending the metagenomic species approach, we revealed bacterial strains inhibiting the opportunistic fungal pathogen Candida albicans. We demonstrated in vitro how C. albicans pathogenicity and host cell damage might be controlled naturally in the human gut by bacterial metabolites such as propionate or 5-dodecenoate. CONCLUSIONS: We demonstrated that antibacterial drugs have long-term influence on the human gut mycobiome. While bacterial communities recovered mostly 30-days post antibacterial treatment, the fungal community was shifted from mutualism towards competition. Video abstract.

Authors: Bastian Seelbinder, J. Chen, S. Brunke, R. Vazquez-Uribe, R. Santhaman, A. C. Meyer, F. S. de Oliveira Lino, K. F. Chan, D. Loos, L. Imamovic, C. C. Tsang, R. P. Lam, S. Sridhar, K. Kang, Bernhard Hube, P. C. Woo, M. O. A. Sommer, Gianni Panagiotou

Date Published: 12th Sep 2020

Journal: Microbiome

Abstract (Expand)

Rhinovirus (RV) and influenza virus are the most frequently detected respiratory viruses among adult patients with community acquired pneumonia. Previous clinical studies have identified major differences in the clinical presentations and inflammatory or immune response during these infections. A systematic transcriptomic analysis directly comparing influenza and RV is lacking. Here, we sought to compare the transcriptomic response to these viral infections. Human airway epithelial Calu-3 cells were infected with contemporary clinical isolates of RV, influenza A virus (IAV), or influenza B virus (IBV). Host gene expression was determined using RNA-seq. Differentially expressed genes (DEGs) with respect to mock-infected cells were identified using the overlapping gene-set of four different statistical models. Transcriptomic analysis showed that RV-infected cells have a more blunted host response with fewer DEGs than IAV or IBV-infected cells. IFNL1 and CXCL10 were among the most upregulated DEGs during RV, IAV, and IBV infection. Other DEGs that were highly expressed for all 3 viruses were mainly genes related to type I or type III interferons (RSAD2, IDO1) and chemokines (CXCL11). Notably, ICAM5, a known receptor for enterovirus D68, was highly expressed during RV infection only. Gene Set Enrichment Analysis (GSEA) confirmed that pathways associated with interferon response, innate immunity, or regulation of inflammatory response, were most perturbed for all three viruses. Network analysis showed that steroid-related pathways were enriched. Taken together, our data using contemporary virus strains suggests that genes related to interferon and chemokine predominated the host response associated with RV, IAV, and IBV infection. Several highly expressed genes, especially ICAM5 which is preferentially-induced during RV infection, deserve further investigation.

Authors: T. K. Dissanayake, Sascha Schäuble, Mohammad Mirhakkak, W. L. Wu, A. C. Ng, C. C. Y. Yip, A. G. Lopez, Thomas Wolf, M. L. Yeung, K. H. Chan, K. Y. Yuen, Gianni Panagiotou, K. K. To

Date Published: 28th Aug 2020

Journal: Front Microbiol

Abstract (Expand)

Fungal spores and hyphal fragments play an important role as allergens in respiratory diseases. In this study, we performed trypsin shaving and secretome analyses to identify the surface-exposed proteins and secreted/shed proteins of Aspergillus fumigatus conidia, respectively. We investigated the surface proteome under different conditions, including temperature variation and germination. We found that the surface proteome of resting A. fumigatus conidia is not static but instead unexpectedly dynamic, as evidenced by drastically different surface proteomes under different growth conditions. Knockouts of two abundant A. fumigatus surface proteins, ScwA and CweA, were found to function only in fine-tuning the cell wall stress response, implying that the conidial surface is very robust against perturbations. We then compared the surface proteome of A. fumigatus to other allergy-inducing molds, including Alternaria alternata, Penicillium rubens, and Cladosporium herbarum, and performed comparative proteomics on resting and swollen conidia, as well as secreted proteins from germinating conidia. We detected 125 protein ortholog groups, including 80 with putative catalytic activity, in the extracellular region of all four molds, and 42 nonorthologous proteins produced solely by A. fumigatus. Ultimately, this study highlights the dynamic nature of the A. fumigatus conidial surface and provides targets for future diagnostics and immunotherapy.

Authors: M. G. Blango, A. Pschibul, Flora Rivieccio, Thomas Krüger, M. Rafiq, L. J. Jia, T. Zheng, M. Goldmann, V. Voltersen, J. Li, Gianni Panagiotou, Olaf Kniemeyer, Axel Brakhage

Date Published: 1st May 2020

Journal: J Proteome Res

Abstract (Expand)

The gut microbiota has the potential to influence the efficacy of cancer therapy. Here, we investigated the contribution of the intestinal microbiome on treatment outcomes in a heterogeneous cohort that included multiple cancer types to identify microbes with a global impact on immune response. Human gut metagenomic analysis revealed that responder patients had significantly higher microbial diversity and different microbiota compositions compared to non-responders. A machine-learning model was developed and validated in an independent cohort to predict treatment outcomes based on gut microbiota composition and functional repertoires of responders and non-responders. Specific species, Bacteroides ovatus and Bacteroides xylanisolvens, were positively correlated with treatment outcomes. Oral gavage of these responder bacteria significantly increased the efficacy of erlotinib and induced the expression of CXCL9 and IFN-gamma in a murine lung cancer model. These data suggest a predictable impact of specific constituents of the microbiota on tumor growth and cancer treatment outcomes with implications for both prognosis and therapy.

Authors: Y. Heshiki, R. Vazquez-Uribe, J. Li, Y. Ni, S. Quainoo, L. Imamovic, J. Li, M. Sorensen, B. K. C. Chow, G. J. Weiss, A. Xu, M. O. A. Sommer, Gianni Panagiotou

Date Published: 5th Mar 2020

Journal: Microbiome

Abstract (Expand)

Pathogenic microorganisms exploit host metabolism for sustained survival by rewiring its metabolic interactions. Therefore, several metabolic changes are induced in both pathogen and host cells in the course of infection. A systems-based approach to elucidate those changes includes the integrative use of genome-scale metabolic networks and molecular omics data, with the overall goal of better characterizing infection mechanisms for novel treatment strategies. This review focuses on novel aspects of metabolism-oriented systems-based investigation of pathogen-human interactions. The reviewed approaches are the generation of dual-omics data for the characterization of metabolic signatures of pathogen-host interactions, the reconstruction of pathogen-host integrated genome-scale metabolic networks, which has a high potential to be applied to pathogen-gut microbiota interactions, and the structure-based analysis of enzymes playing role in those interactions. The integrative use of those approaches will pave the way for the identification of novel biomarkers and drug targets for the prediction and prevention of infectious diseases.

Authors: T. Cakir, Gianni Panagiotou, R. Uddin, S. Durmus

Date Published: 3rd Mar 2020

Journal: Front Cell Infect Microbiol

Abstract (Expand)

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is a last-resort treatment to induce substantial and sustained weight loss in cases of severe obesity. This anatomical rearrangement affects the intestinal microbiota, but so far, little information is available on how it interferes with microbial functionality and microbial-host interactions independently of weight loss. METHODS: A rat model was employed where the RYGB-surgery cohort is compared to sham-operated controls which were kept at a matched body weight by food restriction. We investigated the microbial taxonomy and functional activity using 16S rRNA amplicon gene sequencing, metaproteomics, and metabolomics on samples collected from theileum, the cecum, and the colon, and separately analysed the lumen and mucus-associated microbiota. RESULTS: Altered gut architecture in RYGB increased the relative occurrence of Actinobacteria, especially Bifidobacteriaceae and Proteobacteria, while in general, Firmicutes were decreased although Streptococcaceae and Clostridium perfringens were observed at relative higher abundances independent of weight loss. A decrease of conjugated and secondary bile acids was observed in the RYGB-gut lumen. The arginine biosynthesis pathway in the microbiota was altered, as indicated by the changes in the abundance of upstream metabolites and enzymes, resulting in lower levels of arginine and higher levels of aspartate in the colon after RYGB. CONCLUSION: The anatomical rearrangement in RYGB affects microbiota composition and functionality as well as changes in amino acid and bile acid metabolism independently of weight loss. The shift in the taxonomic structure of the microbiota after RYGB may be mediated by the resulting change in the composition of the bile acid pool in the gut and by changes in the composition of nutrients in the gut. Video abstract.

Authors: S. B. Haange, N. Jehmlich, U. Krugel, C. Hintschich, D. Wehrmann, M. Hankir, F. Seyfried, J. Froment, T. Hubschmann, S. Muller, D. K. Wissenbach, K. Kang, C. Buettner, Gianni Panagiotou, M. Noll, U. Rolle-Kampczyk, W. Fenske, M. von Bergen

Date Published: 7th Feb 2020

Journal: Microbiome

Abstract (Expand)

Exercise is an effective strategy for diabetes management but is limited by the phenomenon of exercise resistance (i.e., the lack of or the adverse response to exercise on metabolic health). Here, in 39 medication-naive men with prediabetes, we found that exercise-induced alterations in the gut microbiota correlated closely with improvements in glucose homeostasis and insulin sensitivity ( entry NCT03240978). The microbiome of responders exhibited an enhanced capacity for biosynthesis of short-chain fatty acids and catabolism of branched-chain amino acids, whereas those of non-responders were characterized by increased production of metabolically detrimental compounds. Fecal microbial transplantation from responders, but not non-responders, mimicked the effects of exercise on alleviation of insulin resistance in obese mice. Furthermore, a machine-learning algorithm integrating baseline microbial signatures accurately predicted personalized glycemic response to exercise in an additional 30 subjects. These findings raise the possibility of maximizing the benefits of exercise by targeting the gut microbiota.

Authors: Y. Liu, Y. Wang, Y. Ni, C. K. Y. Cheung, K. S. L. Lam, Y. Wang, Z. Xia, D. Ye, J. Guo, M. A. Tse, Gianni Panagiotou, A. Xu

Date Published: 7th Jan 2020

Journal: Cell Metab

Abstract (Expand)

Despite the documented antibiotic-induced disruption of the gut microbiota, the impact of antibiotic intake on strain-level dynamics, evolution of resistance genes, and factors influencing resistance dissemination potential remains poorly understood. To address this gap we analyzed public metagenomic datasets from 24 antibiotic treated subjects and controls, combined with an in-depth prospective functional study with two subjects investigating the bacterial community dynamics based on cultivation-dependent and independent methods. We observed that short-term antibiotic treatment shifted and diversified the resistome composition, increased the average copy number of antibiotic resistance genes, and altered the dominant strain genotypes in an individual-specific manner. More than 30% of the resistance genes underwent strong differentiation at the single nucleotide level during antibiotic treatment. We found that the increased potential for horizontal gene transfer, due to antibiotic administration, was approximately 3-fold stronger in the differentiated resistance genes than the non-differentiated ones. This study highlights how antibiotic treatment has individualized impacts on the resistome and strain level composition, and drives the adaptive evolution of the gut microbiota.

Authors: J. Li, E. A. Rettedal, E. van der Helm, M. Ellabaan, Gianni Panagiotou, M. O. A. Sommer

Date Published: 27th Apr 2019

Journal: Genomics Proteomics Bioinformatics

Abstract (Expand)

BACKGROUND: The selection of bioengineering platform strains and engineering strategies to improve the stress resistance of Saccharomyces cerevisiae remains a pressing need in bio-based chemical production. Thus, a systematic effort to exploit genotypic and phenotypic diversity to boost yeast's industrial value is still urgently needed. RESULTS: We analyzed 5,400 growth curves obtained from 36 S. cerevisiae strains and comprehensively profiled their resistances against 13 industrially relevant stresses. We observed that bioethanol and brewing strains exhibit higher resistance against acidic conditions; however, plant isolates tend to have a wider range of resistance, which may be associated with their metabolome and fluxome signatures in the tricarboxylic acid cycle and fatty acid metabolism. By deep genomic sequencing, we found that industrial strains have more genomic duplications especially affecting transcription factors, showing that they result from disparate evolutionary paths in comparison with the environmental strains, which have more indels, gene deletions, and strain-specific genes. Genome-wide association studies coupled with protein-protein interaction networks uncovered novel genetic determinants of stress resistances. CONCLUSIONS: These resistance-related engineering targets and strain rankings provide a valuable source for engineering significantly improved industrial platform strains.

Authors: K. Kang, B. Bergdahl, D. Machado, L. Dato, T. L. Han, J. Li, S. Villas-Boas, M. J. Herrgard, J. Forster, Gianni Panagiotou

Date Published: 1st Apr 2019

Journal: Gigascience

Abstract (Expand)

BACKGROUND: Viruses are important components of microbial communities modulating community structure and function; however, only a couple of tools are currently available for phage identification and analysis from metagenomic sequencing data. Here we employed the random forest algorithm to develop VirMiner, a web-based phage contig prediction tool especially sensitive for high-abundances phage contigs, trained and validated by paired metagenomic and phagenomic sequencing data from the human gut flora. RESULTS: VirMiner achieved 41.06% +/- 17.51% sensitivity and 81.91% +/- 4.04% specificity in the prediction of phage contigs. In particular, for the high-abundance phage contigs, VirMiner outperformed other tools (VirFinder and VirSorter) with much higher sensitivity (65.23% +/- 16.94%) than VirFinder (34.63% +/- 17.96%) and VirSorter (18.75% +/- 15.23%) at almost the same specificity. Moreover, VirMiner provides the most comprehensive phage analysis pipeline which is comprised of metagenomic raw reads processing, functional annotation, phage contig identification, and phage-host relationship prediction (CRISPR-spacer recognition) and supports two-group comparison when the input (metagenomic sequence data) includes different conditions (e.g., case and control). Application of VirMiner to an independent cohort of human gut metagenomes obtained from individuals treated with antibiotics revealed that 122 KEGG orthology and 118 Pfam groups had significantly differential abundance in the pre-treatment samples compared to samples at the end of antibiotic administration, including clustered regularly interspaced short palindromic repeats (CRISPR), multidrug resistance, and protein transport. The VirMiner webserver is available at . CONCLUSIONS: We developed a comprehensive tool for phage prediction and analysis for metagenomic samples. Compared to VirSorter and VirFinder-the most widely used tools-VirMiner is able to capture more high-abundance phage contigs which could play key roles in infecting bacteria and modulating microbial community dynamics. TRIAL REGISTRATION: The European Union Clinical Trials Register, EudraCT Number: 2013-003378-28 . Registered on 9 April 2014.

Authors: T. Zheng, J. Li, Y. Ni, K. Kang, M. A. Misiakou, L. Imamovic, B. K. C. Chow, A. A. Rode, P. Bytzer, M. Sommer, Gianni Panagiotou

Date Published: 19th Mar 2019

Journal: Microbiome

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