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Gianni Panagiotou

About Gianni Panagiotou:
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SEEK ID: https://funginet.hki-jena.de/people/115

Location:  Germany

Expertise: Not specified

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FungiNet total
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Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/home.html

FungiNet B - Bioinformatics projects
No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-area-b.html

INF

Integrated database for experimental data

Within the Collaborative Research Center / Transregio 124 “Pathogenic fungi and their human host: Networks of Interaction – FungiNet”, the INF project is responsible to analyse and share OMICS data. Databases help to foster the collaboration within FungiNet as an important point of the Collaborative Research Center. Therefore, we set-up two databases:

a) SEEK is a web-based platform to find, share and exchange unstructured data and knowledge, such as
...

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-inf.html

B5
No description specified

Programme: Collaborative Research Center / Transregio 124 "Pathogenic fungi and their human host: Networks of Interaction - FungiNet"

Public web page: http://www.funginet.de/project-b5.html

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MetGEMs Toolbox: Metagenome-scale models as integrative toolbox for uncovering metabolic functions and routes of human gut microbiome.
INF, B5

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

Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels.
INF, A5, C1, C2, B5

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

Lipid metabolic signatures deviate in sepsis survivors compared to non-survivors.
INF, C5

Abstract (Expand)

Sepsis remains a major cause of death despite advances in medical care. Metabolic deregulation is an important component of the survival process. Metabolomic analysis allows profiling of critical … metabolic functions with the potential to classify patient outcome. Our prospective longitudinal characterization of 33 septic and non-septic critically ill patients showed that deviations, independent of direction, in plasma levels of lipid metabolites were associated with sepsis mortality. We identified a coupling of metabolic signatures between liver and plasma of a rat sepsis model that allowed us to apply a human kinetic model of mitochondrial beta-oxidation to reveal differing enzyme concentrations for medium/short-chain hydroxyacyl-CoA dehydrogenase (elevated in survivors) and crotonase (elevated in non-survivors). These data suggest a need to monitor cellular energy metabolism beyond the available biomarkers. A loss of metabolic adaptation appears to be reflected by an inability to maintain cellular (fatty acid) metabolism within a "corridor of safety".

Authors: W. Khaliq, Peter Großmann, S. Neugebauer, A. Kleyman, R. Domizi, S. Calcinaro, D. Brealey, M. Graler, M. Kiehntopf, Sascha Schäuble, M. Singer, Gianni Panagiotou, Michael Bauer

Date Published: 11th Dec 2020

Journal: Comput Struct Biotechnol J

Effects of Agricultural Fungicide Use on Aspergillus fumigatus Abundance, Antifungal Susceptibility, and Population Structure.
INF, B5

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

Triple RNA-Seq Reveals Synergy in a Human Virus-Fungus Co-infection Model.
INF, A2, B5

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

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