1
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Cacace E, Kim V, Varik V, Knopp M, Tietgen M, Brauer-Nikonow A, Inecik K, Mateus A, Milanese A, Mårli MT, Mitosch K, Selkrig J, Brochado AR, Kuipers OP, Kjos M, Zeller G, Savitski MM, Göttig S, Huber W, Typas A. Systematic analysis of drug combinations against Gram-positive bacteria. Nat Microbiol 2023; 8:2196-2212. [PMID: 37770760 PMCID: PMC10627819 DOI: 10.1038/s41564-023-01486-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 08/30/2023] [Indexed: 09/30/2023]
Abstract
Drug combinations can expand options for antibacterial therapies but have not been systematically tested in Gram-positive species. We profiled ~8,000 combinations of 65 antibacterial drugs against the model species Bacillus subtilis and two prominent pathogens, Staphylococcus aureus and Streptococcus pneumoniae. Thereby, we recapitulated previously known drug interactions, but also identified ten times more novel interactions in the pathogen S. aureus, including 150 synergies. We showed that two synergies were equally effective against multidrug-resistant S. aureus clinical isolates in vitro and in vivo. Interactions were largely species-specific and synergies were distinct from those of Gram-negative species, owing to cell surface and drug uptake differences. We also tested 2,728 combinations of 44 commonly prescribed non-antibiotic drugs with 62 drugs with antibacterial activity against S. aureus and identified numerous antagonisms that might compromise the efficacy of antimicrobial therapies. We identified even more synergies and showed that the anti-aggregant ticagrelor synergized with cationic antibiotics by modifying the surface charge of S. aureus. All data can be browsed in an interactive interface ( https://apps.embl.de/combact/ ).
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Affiliation(s)
- Elisabetta Cacace
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Vladislav Kim
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, Heidelberg, Germany
| | - Vallo Varik
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Michael Knopp
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Manuela Tietgen
- Goethe University Frankfurt, University Hospital, Institute for Medical Microbiology and Infection Control, Frankfurt am Main, Germany
| | | | - Kemal Inecik
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - André Mateus
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Alessio Milanese
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
- Department of Biology, Institute of Microbiology, and Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland
| | - Marita Torrissen Mårli
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
| | - Karin Mitosch
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Joel Selkrig
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- Institute of Medical Microbiology, University Hospital of RWTH, Aachen, Germany
| | - Ana Rita Brochado
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
- Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections, University of Tübingen, Tübingen, Germany
- Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany
| | - Oscar P Kuipers
- Department of Molecular Genetics, Groningen Molecular Biology and Biotechnology Institute, University of Groningen, Groningen, the Netherlands
| | - Morten Kjos
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway
| | - Georg Zeller
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Mikhail M Savitski
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Stephan Göttig
- Goethe University Frankfurt, University Hospital, Institute for Medical Microbiology and Infection Control, Frankfurt am Main, Germany
| | - Wolfgang Huber
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Athanasios Typas
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
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2
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Fullam A, Letunic I, Schmidt TSB, Ducarmon QR, Karcher N, Khedkar S, Kuhn M, Larralde M, Maistrenko OM, Malfertheiner L, Milanese A, Rodrigues JFM, Sanchis-López C, Schudoma C, Szklarczyk D, Sunagawa S, Zeller G, Huerta-Cepas J, von Mering C, Bork P, Mende DR. proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes. Nucleic Acids Res 2023; 51:D760-D766. [PMID: 36408900 PMCID: PMC9825469 DOI: 10.1093/nar/gkac1078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/15/2022] [Accepted: 11/07/2022] [Indexed: 11/22/2022] Open
Abstract
The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.
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Affiliation(s)
- Anthony Fullam
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Ivica Letunic
- Biobyte solutions GmbH, Bothestr. 142, 69117 Heidelberg, Germany
| | - Thomas S B Schmidt
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Quinten R Ducarmon
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Nicolai Karcher
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Supriya Khedkar
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Michael Kuhn
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Martin Larralde
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Oleksandr M Maistrenko
- Royal Netherlands Institute for Sea Research (NIOZ), Department of Marine Microbiology & Biogeochemistry, 1797 SZ, 't Horntje (Texel), Netherlands
| | - Lukas Malfertheiner
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
| | - Alessio Milanese
- Institute of Microbiology, Department of Biology and Swiss Institute of Bioinformatics, ETH Zurich, Vladimir-Prelog-Weg 4, 8093 Zurich, Switzerland
| | | | - Claudia Sanchis-López
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Campus de Montegancedo-UPM, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Christian Schudoma
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Damian Szklarczyk
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
| | - Shinichi Sunagawa
- Institute of Microbiology, Department of Biology and Swiss Institute of Bioinformatics, ETH Zurich, Vladimir-Prelog-Weg 4, 8093 Zurich, Switzerland
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Jaime Huerta-Cepas
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Campus de Montegancedo-UPM, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Christian von Mering
- Department of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, 8057 Zurich, Switzerland
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.,Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany.,Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany.,Yonsei Frontier Lab (YFL), Yonsei University, 03722 Seoul, South Korea
| | - Daniel R Mende
- Department of Medical Microbiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
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3
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Ruscheweyh HJ, Milanese A, Paoli L, Karcher N, Clayssen Q, Keller MI, Wirbel J, Bork P, Mende DR, Zeller G, Sunagawa S. Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments. Microbiome 2022; 10:212. [PMID: 36464731 PMCID: PMC9721005 DOI: 10.1186/s40168-022-01410-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 11/03/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes. RESULTS We present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies. CONCLUSIONS We developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.
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Affiliation(s)
- Hans-Joachim Ruscheweyh
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093 Zürich, Switzerland
| | - Alessio Milanese
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093 Zürich, Switzerland
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Lucas Paoli
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093 Zürich, Switzerland
| | - Nicolai Karcher
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Quentin Clayssen
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093 Zürich, Switzerland
| | - Marisa Isabell Keller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Jakob Wirbel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
- Max Delbrück Centre for Molecular Medicine, Robert-Rössle-Str. 10, 13092 Berlin, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074 Würzburg, Germany
| | - Daniel R. Mende
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Shinichi Sunagawa
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, 8093 Zürich, Switzerland
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4
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Candela V, Di Lucia P, Carnevali C, Milanese A, Spagnoli A, Villani C, Gumina S. Epidemiology of distal radius fractures: a detailed survey on a large sample of patients in a suburban area. J Orthop Traumatol 2022; 23:43. [PMID: 36040542 PMCID: PMC9428104 DOI: 10.1186/s10195-022-00663-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 08/03/2022] [Indexed: 11/28/2022] Open
Abstract
Background Literature lacks data on correlations between epidemiology and clinical data of patients with distal radius fractures (DRFs). Aim The aim of this study was to present a detailed epidemiologic survey of a large consecutive series of patient with DRFs. Materials and Methods This retrospective study included 827 consecutive patients (579 females, 248 men) who sustained a DRFs in the last 5 years. All fractures were radiographically evaluated. DRFs were classified according to Association of Osteosynthesis classification. Data on age, gender, side, period in which fracture occurred, and fracture mechanism were collected. Statistical analysis was performed. Results The patients’ mean age was 60.23 [standard deviation (SD) 16.65] years, with the left side being most frequently involved (56.1%). The mean age of females at the time of fracture was significantly higher than that of males. The most frequent pattern of fracture was the complete articular fracture (64.3%), while the most represented fracture type was 2R3A2.2 (21.5%). Regarding the period in which the fracture occurred, 305 DRFs (37.5%) were observed in the warmer months and 272 (33.4%) in the colder months. Low-energy trauma occurring outside home was found to be the major cause of DRF throughout the year. In both genders, trauma mechanism 2 was more frequent (59.4% F; 31.9% M; p < 0.01). A bimodal distribution of fracture mechanisms was found in males when considering the patient’s age with a high-energy mechanism of fracture (3 and 4), identified in 21% (n = 52) of males aged 18–45 years, and a low-energy mechanism (1 and 2) was observed in 39.9% (n = 99) of males aged > 45 years. A significant correlation between all trauma mechanisms (from 1 to 6) and different fracture patterns (complete, partial, and extraarticular) was found (p value < 0.001). The mean age of patients with extraarticular fractures (mean age 61.75 years; SD 18.18 years) was higher than that of those with complete (mean age 59.84 years; SD 15.67 years) and partial fractures (mean age 55.26 years; SD 18.31 years). Furthermore, considering different fracture patterns and patient age groups, a statistically significant difference was found (p < 0.001). Conclusions DRFs have a higher prevalence in females, an increase in incidence with older age, and no seasonal predisposition. Low-energy trauma occurring at home is the main cause of fracture among younger males sustaining fractures after sports trauma; Complete articular is the most frequent fracture pattern, while 2R3A2.2 is most frequent fracture type. Level of evidence Level IV; case series; descriptive epidemiology study.
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Affiliation(s)
- V Candela
- Dept. of Anatomical, Histological, Forensic Medicine and Orthopaedics Sciences, Sapienza University of Rome, Istituto Clinico Ortopedico Traumatologico (ICOT), Latina, Italy
| | - P Di Lucia
- Dept. of Anatomical, Histological, Forensic Medicine and Orthopaedics Sciences, Sapienza University of Rome, Istituto Clinico Ortopedico Traumatologico (ICOT), Latina, Italy
| | - C Carnevali
- Dept. of Anatomical, Histological, Forensic Medicine and Orthopaedics Sciences, Sapienza University of Rome, Istituto Clinico Ortopedico Traumatologico (ICOT), Latina, Italy
| | - A Milanese
- Dept. of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | - A Spagnoli
- Dept. of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
| | - C Villani
- Dept. of Anatomical, Histological, Forensic Medicine and Orthopaedics Sciences, Sapienza University of Rome, Umberto I Hospital, Rome, Italy
| | - Stefano Gumina
- Dept. of Anatomical, Histological, Forensic Medicine and Orthopaedics Sciences, Sapienza University of Rome, Istituto Clinico Ortopedico Traumatologico (ICOT), Latina, Italy.
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5
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Meyer F, Fritz A, Deng ZL, Koslicki D, Lesker TR, Gurevich A, Robertson G, Alser M, Antipov D, Beghini F, Bertrand D, Brito JJ, Brown CT, Buchmann J, Buluç A, Chen B, Chikhi R, Clausen PTLC, Cristian A, Dabrowski PW, Darling AE, Egan R, Eskin E, Georganas E, Goltsman E, Gray MA, Hansen LH, Hofmeyr S, Huang P, Irber L, Jia H, Jørgensen TS, Kieser SD, Klemetsen T, Kola A, Kolmogorov M, Korobeynikov A, Kwan J, LaPierre N, Lemaitre C, Li C, Limasset A, Malcher-Miranda F, Mangul S, Marcelino VR, Marchet C, Marijon P, Meleshko D, Mende DR, Milanese A, Nagarajan N, Nissen J, Nurk S, Oliker L, Paoli L, Peterlongo P, Piro VC, Porter JS, Rasmussen S, Rees ER, Reinert K, Renard B, Robertsen EM, Rosen GL, Ruscheweyh HJ, Sarwal V, Segata N, Seiler E, Shi L, Sun F, Sunagawa S, Sørensen SJ, Thomas A, Tong C, Trajkovski M, Tremblay J, Uritskiy G, Vicedomini R, Wang Z, Wang Z, Wang Z, Warren A, Willassen NP, Yelick K, You R, Zeller G, Zhao Z, Zhu S, Zhu J, Garrido-Oter R, Gastmeier P, Hacquard S, Häußler S, Khaledi A, Maechler F, Mesny F, Radutoiu S, Schulze-Lefert P, Smit N, Strowig T, Bremges A, Sczyrba A, McHardy AC. Critical Assessment of Metagenome Interpretation: the second round of challenges. Nat Methods 2022; 19:429-440. [PMID: 35396482 PMCID: PMC9007738 DOI: 10.1038/s41592-022-01431-4] [Citation(s) in RCA: 89] [Impact Index Per Article: 44.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 02/14/2022] [Indexed: 12/20/2022]
Abstract
Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses. This study presents the results of the second round of the Critical Assessment of Metagenome Interpretation challenges (CAMI II), which is a community-driven effort for comprehensively benchmarking tools for metagenomics data analysis.
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Affiliation(s)
- Fernando Meyer
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany
| | - Adrian Fritz
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.,German Center for Infection Research (DZIF), Hannover-Braunschweig Site, Braunschweig, Germany
| | - Zhi-Luo Deng
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany.,Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany
| | | | - Till Robin Lesker
- German Center for Infection Research (DZIF), Hannover-Braunschweig Site, Braunschweig, Germany.,Helmholtz Centre for Infection Research, Braunschweig, Germany
| | | | - Gary Robertson
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.,Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany
| | - Mohammed Alser
- Department of Information Technology and Electrical Engineering, ETH Zürich, Zurich, Switzerland
| | - Dmitry Antipov
- Center for Algorithmic Biotechnology, Saint Petersburg State University, Saint Petersburg, Russia
| | | | | | | | | | - Jan Buchmann
- Institute for Biological Data Science, Heinrich-Heine-University, Düsseldorf, Germany
| | - Aydin Buluç
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,University of California, Berkeley, Berkeley, CA, USA
| | - Bo Chen
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,University of California, Berkeley, Berkeley, CA, USA
| | | | - Philip T L C Clausen
- National Food Institute, Division of Global Surveillance, Technical University of Denmark, Lyngby, Denmark
| | - Alexandru Cristian
- Drexel University, Philadelphia, PA, USA.,Google Inc., Philadelphia, PA, USA
| | - Piotr Wojciech Dabrowski
- Robert Koch-Institut, Berlin, Germany.,Hochschule für Technik und Wirtschaft Berlin, Berlin, Germany
| | | | - Rob Egan
- DOE Joint Genome Institute, Berkeley, CA, USA.,Lawrence Berkeley National Laboratories, Berkeley, CA, USA
| | - Eleazar Eskin
- University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Eugene Goltsman
- DOE Joint Genome Institute, Berkeley, CA, USA.,Lawrence Berkeley National Laboratories, Berkeley, CA, USA
| | - Melissa A Gray
- Drexel University, Philadelphia, PA, USA.,Ecological and Evolutionary Signal-Processing and Informatics Laboratory, Philadelphia, PA, USA
| | - Lars Hestbjerg Hansen
- University of Copenhagen, Department of Plant and Environmental Science, Frederiksberg, Denmark
| | - Steven Hofmeyr
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,University of California, Berkeley, Berkeley, CA, USA
| | - Pingqin Huang
- School of Computer Science, Fudan University, Shanghai, China
| | - Luiz Irber
- University of California, Davis, Davis, CA, USA
| | - Huijue Jia
- BGI-Shenzhen, Shenzhen, China.,Shenzhen Key Laboratory of Human Commensal Microorganisms and Health Research, BGI-Shenzhen, Shenzhen, China
| | - Tue Sparholt Jørgensen
- Technical University of Denmark, Novo Nordisk Foundation Center for Biosustainability, Lyngby, Denmark.,Aarhus University, Department of Environmental Science, Roskilde, Denmark
| | - Silas D Kieser
- Department of Cell Physiology and Metabolism, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Swiss Institute of Bioinformatics, Geneva, Switzerland
| | | | - Axel Kola
- Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Anton Korobeynikov
- Center for Algorithmic Biotechnology, Saint Petersburg State University, Saint Petersburg, Russia.,Department of Statistical Modelling, Saint Petersburg State University, Saint Petersburg, Russia
| | - Jason Kwan
- University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Chenhao Li
- Genome Institute of Singapore, Singapore, Singapore
| | | | - Fabio Malcher-Miranda
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | | | - Vanessa R Marcelino
- Sydney Medical School, The University of Sydney, Sydney, Australia.,Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Clayton, Australia
| | | | - Pierre Marijon
- Department of Computer Science, Inria, University of Lille, CNRS, Lille, France
| | - Dmitry Meleshko
- Center for Algorithmic Biotechnology, Saint Petersburg State University, Saint Petersburg, Russia
| | - Daniel R Mende
- Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Alessio Milanese
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland.,Structural and Computational Biology Unit, EMBL, Heidelberg, Germany
| | - Niranjan Nagarajan
- Genome Institute of Singapore, A*STAR, Singapore, Singapore.,National University of Singapore, Singapore, Singapore
| | | | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Leonid Oliker
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,University of California, Berkeley, Berkeley, CA, USA
| | - Lucas Paoli
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | | | - Vitor C Piro
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | | | - Simon Rasmussen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Evan R Rees
- University of Wisconsin-Madison, Madison, WI, USA
| | - Knut Reinert
- Institute for Bioinformatics, FU Berlin, Berlin, Germany
| | - Bernhard Renard
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany.,Bioinformatics Unit (MF1), Robert Koch Institute, Berlin, Germany
| | | | - Gail L Rosen
- Drexel University, Philadelphia, PA, USA.,Ecological and Evolutionary Signal-Processing and Informatics Laboratory, Philadelphia, PA, USA.,Center for Biological Discovery from Big Data, Philadelphia, PA, USA
| | - Hans-Joachim Ruscheweyh
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | - Varuni Sarwal
- University of California, Los Angeles, Los Angeles, CA, USA
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
| | - Enrico Seiler
- Institute for Bioinformatics, FU Berlin, Berlin, Germany
| | - Lizhen Shi
- Florida Polytechnic University, Lakeland, FL, USA
| | - Fengzhu Sun
- Quantitative and Computational Biology Department, University of Southern California, Los Angeles, CA, USA
| | - Shinichi Sunagawa
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | | | - Ashleigh Thomas
- DOE Joint Genome Institute, Berkeley, CA, USA.,University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Mirko Trajkovski
- Department of Cell Physiology and Metabolism, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Diabetes Center, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Julien Tremblay
- Energy, Mining and Environment, National Research Council Canada, Montreal, Quebec, Canada
| | | | | | - Zhengyang Wang
- School of Computer Science, Fudan University, Shanghai, China
| | - Ziye Wang
- School of Mathematical Sciences, Fudan University, Shanghai, China
| | - Zhong Wang
- Department of Energy Joint Genome Institute, Berkeley, CA, USA.,Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,School of Natural Sciences, University of California at Merced, Merced, CA, USA
| | | | | | - Katherine Yelick
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,University of California, Berkeley, Berkeley, CA, USA
| | - Ronghui You
- School of Computer Science, Fudan University, Shanghai, China
| | - Georg Zeller
- Structural and Computational Biology Unit, EMBL, Heidelberg, Germany
| | | | - Shanfeng Zhu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhu
- BGI-Shenzhen, Shenzhen, China.,Shenzhen Key Laboratory of Human Commensal Microorganisms and Health Research, BGI-Shenzhen, Shenzhen, China
| | | | | | | | - Susanne Häußler
- Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Ariane Khaledi
- Helmholtz Centre for Infection Research, Braunschweig, Germany
| | | | - Fantin Mesny
- Max Planck Institute for Plant Breeding Research, Köln, Germany
| | | | | | - Nathiana Smit
- Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Till Strowig
- Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Andreas Bremges
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany.,German Center for Infection Research (DZIF), Hannover-Braunschweig Site, Braunschweig, Germany
| | - Alexander Sczyrba
- Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
| | - Alice Carolyn McHardy
- Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany. .,Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany. .,German Center for Infection Research (DZIF), Hannover-Braunschweig Site, Braunschweig, Germany. .,Cluster of Excellence RESIST (EXC 2155), Hannover Medical School, Hannover, Germany.
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6
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Sowah SA, Milanese A, Schübel R, Wirbel J, Kartal E, Johnson TS, Hirche F, Grafetstätter M, Nonnenmacher T, Kirsten R, López-Nogueroles M, Lahoz A, Schwarz KV, Okun JG, Ulrich CM, Nattenmüller J, von Eckardstein A, Müller D, Stangl GI, Kaaks R, Kühn T, Zeller G. Calorie restriction improves metabolic state independently of gut microbiome composition: a randomized dietary intervention trial. Genome Med 2022; 14:30. [PMID: 35287713 PMCID: PMC8919571 DOI: 10.1186/s13073-022-01030-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 02/14/2022] [Indexed: 12/12/2022] Open
Abstract
Background The gut microbiota has been suggested to play a significant role in the development of overweight and obesity. However, the effects of calorie restriction on gut microbiota of overweight and obese adults, especially over longer durations, are largely unexplored. Methods Here, we longitudinally analyzed the effects of intermittent calorie restriction (ICR) operationalized as the 5:2 diet versus continuous calorie restriction (CCR) on fecal microbiota of 147 overweight or obese adults in a 50-week parallel-arm randomized controlled trial, the HELENA Trial. The primary outcome of the trial was the differential effects of ICR versus CCR on gene expression in subcutaneous adipose tissue. Changes in the gut microbiome, which are the focus of this publication, were defined as exploratory endpoint of the trial. The trial comprised a 12-week intervention period, a 12-week maintenance period, and a final follow-up period of 26 weeks. Results Both diets resulted in ~5% weight loss. However, except for Lactobacillales being enriched after ICR, post-intervention microbiome composition did not significantly differ between groups. Overall weight loss was associated with significant metabolic improvements, but not with changes in the gut microbiome. Nonetheless, the abundance of the Dorea genus at baseline was moderately predictive of subsequent weight loss (AUROC of 0.74 for distinguishing the highest versus lowest weight loss quartiles). Despite the lack of consistent intervention effects on microbiome composition, significant study group-independent co-variation between gut bacterial families and metabolic biomarkers, anthropometric measures, and dietary composition was detectable. Our analysis in particular revealed associations between insulin sensitivity (HOMA-IR) and Akkermansiaceae, Christensenellaceae, and Tanerellaceae. It also suggests the possibility of a beneficial modulation of the latter two intestinal taxa by a diet high in vegetables and fiber, and low in processed meat. Conclusions Overall, our results suggest that the gut microbiome remains stable and highly individual-specific under dietary calorie restriction. Trial registration The trial, including the present microbiome component, was prospectively registered at ClinicalTrials.govNCT02449148 on May 20, 2015. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01030-0.
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Affiliation(s)
- Solomon A Sowah
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany.,Medical Faculty, Heidelberg University, Heidelberg, Germany.,European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, Heidelberg, Germany
| | - Alessio Milanese
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, Heidelberg, Germany
| | - Ruth Schübel
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Jakob Wirbel
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, Heidelberg, Germany
| | - Ece Kartal
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, Heidelberg, Germany.,Molecular Medicine Partnership Unit, Heidelberg, Germany
| | - Theron S Johnson
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Frank Hirche
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Mirja Grafetstätter
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Tobias Nonnenmacher
- Heidelberg University Hospital, Diagnostic and Interventional Radiology, Heidelberg, Germany
| | - Romy Kirsten
- Biobank of the National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Marina López-Nogueroles
- Analytical Unit, Biomarkers and Precision Medicine Unit, Health Research Institute Hospital La Fe, Valencia, Spain
| | - Agustín Lahoz
- Analytical Unit, Biomarkers and Precision Medicine Unit, Health Research Institute Hospital La Fe, Valencia, Spain
| | - Kathrin V Schwarz
- Department of General Paediatrics, Division of Neuropediatrics and Metabolic Medicine, University Hospital Heidelberg, Dietmar-Hopp Metabolic Center, Heidelberg, Germany
| | - Jürgen G Okun
- Department of General Paediatrics, Division of Neuropediatrics and Metabolic Medicine, University Hospital Heidelberg, Dietmar-Hopp Metabolic Center, Heidelberg, Germany
| | - Cornelia M Ulrich
- Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Johanna Nattenmüller
- Heidelberg University Hospital, Diagnostic and Interventional Radiology, Heidelberg, Germany
| | | | - Daniel Müller
- Institute of Clinical Chemistry (IGFS), University Hospital Zurich, Zurich, Switzerland
| | - Gabriele I Stangl
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Tilman Kühn
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany. .,Institute for Global Food Security, Queen's University Belfast, Belfast, Northern Ireland, UK. .,Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg, Germany.
| | - Georg Zeller
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, Heidelberg, Germany.
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7
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Maier L, Goemans CV, Wirbel J, Kuhn M, Eberl C, Pruteanu M, Müller P, Garcia-Santamarina S, Cacace E, Zhang B, Gekeler C, Banerjee T, Anderson EE, Milanese A, Löber U, Forslund SK, Patil KR, Zimmermann M, Stecher B, Zeller G, Bork P, Typas A. Unravelling the collateral damage of antibiotics on gut bacteria. Nature 2021; 599:120-124. [PMID: 34646011 PMCID: PMC7612847 DOI: 10.1038/s41586-021-03986-2] [Citation(s) in RCA: 128] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 09/01/2021] [Indexed: 12/15/2022]
Abstract
Antibiotics are used to fight pathogens but also target commensal bacteria, disturbing the composition of gut microbiota and causing dysbiosis and disease1. Despite this well-known collateral damage, the activity spectrum of different antibiotic classes on gut bacteria remains poorly characterized. Here we characterize further 144 antibiotics from a previous screen of more than 1,000 drugs on 38 representative human gut microbiome species2. Antibiotic classes exhibited distinct inhibition spectra, including generation dependence for quinolones and phylogeny independence for β-lactams. Macrolides and tetracyclines, both prototypic bacteriostatic protein synthesis inhibitors, inhibited nearly all commensals tested but also killed several species. Killed bacteria were more readily eliminated from in vitro communities than those inhibited. This species-specific killing activity challenges the long-standing distinction between bactericidal and bacteriostatic antibiotic classes and provides a possible explanation for the strong effect of macrolides on animal3-5 and human6,7 gut microbiomes. To mitigate this collateral damage of macrolides and tetracyclines, we screened for drugs that specifically antagonized the antibiotic activity against abundant Bacteroides species but not against relevant pathogens. Such antidotes selectively protected Bacteroides species from erythromycin treatment in human-stool-derived communities and gnotobiotic mice. These findings illluminate the activity spectra of antibiotics in commensal bacteria and suggest strategies to circumvent their adverse effects on the gut microbiota.
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Affiliation(s)
- Lisa Maier
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany.
- Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany.
| | - Camille V Goemans
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jakob Wirbel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Michael Kuhn
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Claudia Eberl
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site LMU Munich, Munich, Germany
| | - Mihaela Pruteanu
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Biology, Humboldt University Berlin, Berlin, Germany
| | - Patrick Müller
- Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany
- Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany
| | | | - Elisabetta Cacace
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Boyao Zhang
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Cordula Gekeler
- Interfaculty Institute of Microbiology and Infection Medicine, University of Tübingen, Tübingen, Germany
- Cluster of Excellence 'Controlling Microbes to Fight Infections', University of Tübingen, Tübingen, Germany
| | - Tisya Banerjee
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Chemistry, TU Munich, Munich, Germany
| | - Exene Erin Anderson
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- NYU School of Medicine, New York, NY, USA
| | - Alessio Milanese
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Ulrike Löber
- Experimental and Clinical Research Center, a cooperation of Charité - Universitätsmedizin Berlin and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
| | - Sofia K Forslund
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Experimental and Clinical Research Center, a cooperation of Charité - Universitätsmedizin Berlin and Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
| | - Kiran Raosaheb Patil
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Michael Zimmermann
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Bärbel Stecher
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site LMU Munich, Munich, Germany
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
- Yonsei Frontier Lab (YFL), Yonsei University, Seoul, South Korea
- Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany
| | - Athanasios Typas
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
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8
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Ruscheweyh HJ, Milanese A, Paoli L, Sintsova A, Mende DR, Zeller G, Sunagawa S. mOTUs: Profiling Taxonomic Composition, Transcriptional Activity and Strain Populations of Microbial Communities. Curr Protoc 2021; 1:e218. [PMID: 34387940 DOI: 10.1002/cpz1.218] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The mOTU profiler, or mOTUs for short, is a software tool that enables the profiling of microbial communities in terms of their taxonomic composition, relative abundance of metabolically active members, and diversity of strain populations. To this end, it maintains a database of single-copy phylogenetic marker gene sequences, which are used as a reference to which short read metagenomic and metatranscriptomic reads are mapped for the identification and quantification of microbial taxa. Here, we describe the most common use cases of the mOTU profiler in two basic protocols. Additional supporting protocols provide information on its installation and in-depth guidance on adjusting its settings for increasing or decreasing the stringency with which taxa are detected and quantified, as well as for customizing the output file format. Guidelines for understanding the profiling results are provided, along with additional information on unique features, methodological details, and the development history of the tool. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Metagenomic and metatranscriptomic mOTU profiling Basic Protocol 2: Metagenomic SNV profiling Support Protocol 1: Installing mOTUs Support Protocol 2: Profiling pipeline-step by step Support Protocol 3: The mOTUs profiling routine using advanced parameters Support Protocol 4: Metagenomic SNV calling: advanced parameters.
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Affiliation(s)
- Hans-Joachim Ruscheweyh
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | - Alessio Milanese
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland.,Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Lucas Paoli
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | - Anna Sintsova
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
| | - Daniel R Mende
- Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Shinichi Sunagawa
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich, Switzerland
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9
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Blasche S, Kim Y, Mars RAT, Machado D, Maansson M, Kafkia E, Milanese A, Zeller G, Teusink B, Nielsen J, Benes V, Neves R, Sauer U, Patil KR. Metabolic cooperation and spatiotemporal niche partitioning in a kefir microbial community. Nat Microbiol 2021; 6:196-208. [PMID: 33398099 PMCID: PMC7610452 DOI: 10.1038/s41564-020-00816-5] [Citation(s) in RCA: 116] [Impact Index Per Article: 38.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 10/19/2020] [Indexed: 01/28/2023]
Abstract
Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures or synthetic assemblies. Here, we show how kefir, a natural milk-fermenting community of prokaryotes (predominantly lactic and acetic acid bacteria) and yeasts (family Saccharomycetaceae), realizes stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microorganisms) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open the niche for the followers by making available metabolites such as amino acids and lactate. Through metabolomics, transcriptomics and large-scale mapping of inter-species interactions, we show how microorganisms poorly suited for milk survive in-and even dominate-the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.
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Affiliation(s)
- Sonja Blasche
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Yongkyu Kim
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Ruben A T Mars
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Daniel Machado
- European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Eleni Kafkia
- European Molecular Biology Laboratory, Heidelberg, Germany
- The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK
| | | | - Georg Zeller
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Bas Teusink
- Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jens Nielsen
- Chalmers University of Technology, Gothenburg, Sweden
| | - Vladimir Benes
- European Molecular Biology Laboratory, Heidelberg, Germany
| | | | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Kiran Raosaheb Patil
- European Molecular Biology Laboratory, Heidelberg, Germany.
- The Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, UK.
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10
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Pastori D, Antonucci E, Milanese A, Violi F, Pignatelli P, Palareti G, Farcomeni A. Clinical phenotypes of atrial fibrillation and risk of mortality: a cluster analysis. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehaa946.2893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Patients with atrial fibrillation (AF) experience a high mortality rate despite optimal antithrombotic treatment. Characteristics of AF patients at higher mortality risk have been barely described so far and no risk score has been specifically developed at this aim. Furthermore, a clinical approach based on risk scores present some limits such as to not consider some important risk factors for mortality, and many available scores have poor predictive value. Cluster analysis may play a role in overcoming limitations of risk scores, especially in the case of overlapping risk factors.
Purpose
To identify of clinical phenotypes by using an unbiased statistical approach, such as the cluster analysis.
Methods
Cluster analysis was used to identify clinical phenotypes of AF patients associated with all-cause mortality in 5,171 AF patients from the START registry. Clinical variables used for the analysis were age, sex, diabetes, previous cerebrovascular events, previous cardiovascular events, heart failure, peripheral artery disease, use of non-vitamin K oral anticoagulants, cancer, pulmonary disease, smoking habit, previous major bleeding. The risk of all-cause mortality in each cluster was analyzed.
Results
We identified 4 clusters (Figure 1). Cluster 1 was composed by youngest patients, with obesity and paroxysmal AF; Cluster 2 by patients with low cardiovascular risk factors and high proportion of cancer; Cluster 3 by men with diabetes and coronary and peripheral artery disease, a high proportion of thrombocytopenia, and a high use of aspirin, proton pump inhibitors, and statins; Cluster 4 included the oldest patients, mainly women, with previous cerebrovascular disease, persistent/ permanent AF, heart failure, kidney disease and anemia. In this cluster there was the highest use of digoxin and NOACs.
During 9856,84 patient/years of observation, 386 deaths (3.92%/year) occurred. Mortality rates significantly increased across clusters: 0.42%/year (cluster 1, reference group), 2.12%/year (cluster 2, adjusted hazard ratio [aHR] 3.306, 95% confidence interval [CI] 1.204–9.077, p=0.020), 4.41%/year (cluster 3, aHR 6.702, 95% CI 2.433–18.461, p<0.001) and 8.71%/year (cluster 4, aHR 8.927, 95% CI 3.238–24.605, p<0.001).
Conclusions
We identified different clinical phenotypes of AF patients by cluster analysis which were specifically associated with mortality. This approach may help identify patients at higher risk of mortality.
Figure 1
Funding Acknowledgement
Type of funding source: None
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Affiliation(s)
- D Pastori
- Sapienza University of Rome, Department of Internal Medicine and Medical Specialties, Rome, Italy
| | | | - A Milanese
- Sapienza University of Rome, Department of Public Health and Infectious Diseases, Rome, Italy
| | - F Violi
- Sapienza University of Rome, Department of Clinical Internal, Anesthesiologic, and Cardiovascular Sciences, Rome, Italy
| | - P Pignatelli
- Sapienza University of Rome, Department of Clinical Internal, Anesthesiologic, and Cardiovascular Sciences, Rome, Italy
| | | | - A Farcomeni
- University of Rome Tor Vergata, Department of Economics & Finance, Rome, Italy
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11
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Sowah SA, Hirche F, Milanese A, Johnson TS, Grafetstätter M, Schübel R, Kirsten R, Ulrich CM, Kaaks R, Zeller G, Kühn T, Stangl GI. Changes in Plasma Short-Chain Fatty Acid Levels after Dietary Weight Loss Among Overweight and Obese Adults over 50 Weeks. Nutrients 2020; 12:nu12020452. [PMID: 32053988 PMCID: PMC7071291 DOI: 10.3390/nu12020452] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 02/05/2020] [Accepted: 02/06/2020] [Indexed: 12/14/2022] Open
Abstract
Gut microbial-derived short-chain fatty acids (SCFAs) may regulate energy homeostasis and exert anti-carcinogenic, immunomodulatory and anti-inflammatory effects. Smaller trials indicate that dietary weight loss may lead to decreased SCFA production, but findings have been inconclusive. SCFA concentrations were measured by HPLC-MS/MS in plasma samples of 150 overweight or obese adults in a trial initially designed to evaluate the metabolic effects of intermittent (ICR) versus continuous (CCR) calorie restriction (NCT02449148). For the present post hoc analyses, participants were classified by quartiles of weight loss, irrespective of the dietary intervention. Linear mixed models were used to analyze weight-loss-induced changes in SCFA concentrations after 12, 24 and 50 weeks. There were no differential changes in SCFA levels across the initial study arms (ICR versus CCR versus control) after 12 weeks, but acetate concentrations significantly decreased with overall weight loss (mean log-relative change of −0.7 ± 1.8 in the lowest quartile versus. −7.6 ± 2 in the highest, p = 0.026). Concentrations of propionate, butyrate and other SCFAs did not change throughout the study. Our results show that weight-loss, achieved through calorie restriction, may lead to smaller initial decreases in plasma acetate, while plasma SCFAs generally remain remarkably stable over time.
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Affiliation(s)
- Solomon A. Sowah
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
- Medical Faculty, Heidelberg University, 69120 Heidelberg, Germany
- Correspondence:
| | - Frank Hirche
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany; (F.H.); (G.I.S.)
| | - Alessio Milanese
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, 69117 Heidelberg, Germany; (A.M.); (G.Z.)
| | - Theron S. Johnson
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
| | - Mirja Grafetstätter
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
- Medical Faculty, Heidelberg University, 69120 Heidelberg, Germany
| | - Ruth Schübel
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
| | - Romy Kirsten
- Biobank of the National Center for Tumor Diseases (NCT) Heidelberg, 69120 Heidelberg, Germany;
| | - Cornelia M. Ulrich
- Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112-5550, USA;
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
| | - Georg Zeller
- European Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, 69117 Heidelberg, Germany; (A.M.); (G.Z.)
| | - Tilman Kühn
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120 Heidelberg, Germany; (T.S.J.); (M.G.); (R.S.); (R.K.); (T.K.)
| | - Gabriele I. Stangl
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, 06120 Halle (Saale), Germany; (F.H.); (G.I.S.)
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12
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Mende DR, Letunic I, Maistrenko OM, Schmidt TSB, Milanese A, Paoli L, Hernández-Plaza A, Orakov AN, Forslund SK, Sunagawa S, Zeller G, Huerta-Cepas J, Coelho LP, Bork P. proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes. Nucleic Acids Res 2020; 48:D621-D625. [PMID: 31647096 PMCID: PMC7145564 DOI: 10.1093/nar/gkz1002] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 10/15/2019] [Accepted: 10/18/2019] [Indexed: 12/16/2022] Open
Abstract
Microbiology depends on the availability of annotated microbial genomes for many applications. Comparative genomics approaches have been a major advance, but consistent and accurate annotations of genomes can be hard to obtain. In addition, newer concepts such as the pan-genome concept are still being implemented to help answer biological questions. Hence, we present proGenomes2, which provides 87 920 high-quality genomes in a user-friendly and interactive manner. Genome sequences and annotations can be retrieved individually or by taxonomic clade. Every genome in the database has been assigned to a species cluster and most genomes could be accurately assigned to one or multiple habitats. In addition, general functional annotations and specific annotations of antibiotic resistance genes and single nucleotide variants are provided. In short, proGenomes2 provides threefold more genomes, enhanced habitat annotations, updated taxonomic and functional annotation and improved linkage to the NCBI BioSample database. The database is available at http://progenomes.embl.de/.
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Affiliation(s)
- Daniel R Mende
- Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Ivica Letunic
- Biobyte solutions GmbH, Bothestr, 142, 69117 Heidelberg, Germany
| | - Oleksandr M Maistrenko
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Thomas S B Schmidt
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Alessio Milanese
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Lucas Paoli
- Institute of Microbiology, Department of Biology, ETH Zurich, Vladimir-Prelog-Weg 4, 8093 Zurich, Switzerland
| | - Ana Hernández-Plaza
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Askarbek N Orakov
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Sofia K Forslund
- Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany
| | - Shinichi Sunagawa
- Institute of Microbiology, Department of Biology, ETH Zurich, Vladimir-Prelog-Weg 4, 8093 Zurich, Switzerland
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Jaime Huerta-Cepas
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Luis Pedro Coelho
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany
- Max Delbrück Centre for Molecular Medicine, 13125 Berlin, Germany
- Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, 69120 Heidelberg, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, 97074 Würzburg, Germany
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13
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Wirbel J, Pyl PT, Kartal E, Zych K, Kashani A, Milanese A, Fleck JS, Voigt AY, Palleja A, Ponnudurai R, Sunagawa S, Coelho LP, Schrotz-King P, Vogtmann E, Habermann N, Niméus E, Thomas AM, Manghi P, Gandini S, Serrano D, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Waldron L, Naccarati A, Segata N, Sinha R, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med 2019; 25:679-689. [PMID: 30936547 PMCID: PMC7984229 DOI: 10.1038/s41591-019-0406-6] [Citation(s) in RCA: 570] [Impact Index Per Article: 114.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 02/20/2019] [Indexed: 02/07/2023]
Abstract
Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.
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Affiliation(s)
- Jakob Wirbel
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Paul Theodor Pyl
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine, University of Copenhagen, Copenhagen, Denmark.,Division of Surgery, Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
| | - Ece Kartal
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Molecular Medicine Partnership Unit, Heidelberg, Germany
| | - Konrad Zych
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Alireza Kashani
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Alessio Milanese
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Jonas S Fleck
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Anita Y Voigt
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Albert Palleja
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Ruby Ponnudurai
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Shinichi Sunagawa
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Department of Biology, ETH Zürich, Zürich, Switzerland
| | - Luis Pedro Coelho
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.,Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Petra Schrotz-King
- Division of Preventive Oncology, National Center for Tumor Diseases and German Cancer Research Center, Heidelberg, Germany
| | - Emily Vogtmann
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Nina Habermann
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Emma Niméus
- Division of Surgery, Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden.,Division of Surgery, Department of Clinical Sciences Lund, Faculty of Medicine, Skane University Hospital, Lund, Sweden
| | - Andrew M Thomas
- Department CIBIO, University of Trento, Trento, Italy.,Biochemistry Department, Chemistry Institute, University of São Paulo, São Paulo, Brazil
| | - Paolo Manghi
- Department CIBIO, University of Trento, Trento, Italy
| | - Sara Gandini
- IEO, European Institute of Oncology IRCCS, Milan, Italy
| | | | - Sayaka Mizutani
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan.,Research Fellow of Japan Society for the Promotion of Science, Tokyo, Japan
| | - Hirotsugu Shiroma
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan
| | - Satoshi Shiba
- Division of Cancer Genomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Tatsuhiro Shibata
- Division of Cancer Genomics, National Cancer Center Research Institute, Tokyo, Japan.,Laboratory of Molecular Medicine, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Shinichi Yachida
- Division of Cancer Genomics, National Cancer Center Research Institute, Tokyo, Japan.,Department of Cancer Genome Informatics, Graduate School of Medicine/Faculty of Medicine, Osaka University, Osaka, Japan
| | - Takuji Yamada
- School of Life Science and Technology, Tokyo Institute of Technology, Tokyo, Japan.,PRESTO, Japan Science and Technology Agency, Saitama, Japan
| | - Levi Waldron
- Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA.,Institute for Implementation Science in Population Health, City University of New York, New York, NY, USA
| | - Alessio Naccarati
- Italian Institute for Genomic Medicine, Turin, Italy.,Department of Molecular Biology of Cancer, Institute of Experimental Medicine, Prague, Czech Republic
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
| | - Rashmi Sinha
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Cornelia M Ulrich
- Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Hermann Brenner
- Division of Preventive Oncology, National Center for Tumor Diseases and German Cancer Research Center, Heidelberg, Germany.,Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.,German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Manimozhiyan Arumugam
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medicine, University of Copenhagen, Copenhagen, Denmark. .,Faculty of Healthy Sciences, University of Southern Denmark, Odense, Denmark.
| | - Peer Bork
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany. .,Molecular Medicine Partnership Unit, Heidelberg, Germany. .,Max Delbrück Centre for Molecular Medicine, Berlin, Germany. .,Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany.
| | - Georg Zeller
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
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14
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Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh HJ, Cuenca M, Hingamp P, Alves R, Costea PI, Coelho LP, Schmidt TSB, Almeida A, Mitchell AL, Finn RD, Huerta-Cepas J, Bork P, Zeller G, Sunagawa S. Microbial abundance, activity and population genomic profiling with mOTUs2. Nat Commun 2019; 10:1014. [PMID: 30833550 PMCID: PMC6399450 DOI: 10.1038/s41467-019-08844-4] [Citation(s) in RCA: 195] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 02/02/2019] [Indexed: 12/21/2022] Open
Abstract
Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces estimation biases. We present an updated and functionally extended tool based on universal (i.e., reference-independent), phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) enabling the profiling of >7700 microbial species. As more than 30% of them could not previously be quantified at this taxonomic resolution, relative abundance estimates based on mOTUs are more accurate compared to other methods. As a new feature, we show that mOTUs, which are based on essential housekeeping genes, are demonstrably well-suited for quantification of basal transcriptional activity of community members. Furthermore, single nucleotide variation profiles estimated using mOTUs reflect those from whole genomes, which allows for comparing microbial strain populations (e.g., across different human body sites).
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Affiliation(s)
- Alessio Milanese
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Daniel R Mende
- Daniel K. Inouye Center for Microbial Oceanography Research and Education, University of Hawai'i at Mānoa, 1950 East West Road, Honolulu, USA, 96822, United States
| | - Lucas Paoli
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland
- Department of Biology, École normale supérieure, 46 rue d'Ulm, 75005, Paris, France
| | - Guillem Salazar
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland
| | - Hans-Joachim Ruscheweyh
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland
| | - Miguelangel Cuenca
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland
| | - Pascal Hingamp
- Aix Marseille Univ, Université de Toulon, CNRS, IRD, MIO UM 110, 13288, Marseille, France
| | - Renato Alves
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
- Candidate for Joint PhD degree from EMBL and Heidelberg University, Faculty of Biosciences, Heidelberg, Germany
| | - Paul I Costea
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Luis Pedro Coelho
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Thomas S B Schmidt
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
| | - Alexandre Almeida
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Alex L Mitchell
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CB10 1 SD, UK
| | - Jaime Huerta-Cepas
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223, Pozuelo de Alarcón, Madrid, Spain
| | - Peer Bork
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
- Max Delbrück Centre for Molecular Medicine, Robert-Rössle-Str. 10, 13092, Berlin, Germany
- Molecular Medicine Partnership Unit, Heidelberg, Germany
- Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, 97074, Würzburg, Germany
| | - Georg Zeller
- European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany.
| | - Shinichi Sunagawa
- Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Vladimir-Prelog-Weg 4, 8093, Zürich, Switzerland.
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15
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Abstract
Several dermatologic abnormalities have been described in anorexia nervosa, but only rare associations have been made with perniosis. We recently saw two teenage girls and one woman with anorexia nervosa who had symptoms of perniosis. We suggest that altered thermoregulation and a hyperreactive peripheral vascular response to cold in anorexia nervosa may predispose these patients to perniosis.
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16
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Abstract
The effect of obesity on pulmonary function was studied in 13 children, aged 8-15 years, with 147-300% ideal body weight (IBW). Measurements included lung volumes, airflow rates pre- and post-bronchodilator nebulization, diffusing capacity (DLCO), maximal voluntary ventilation (MVV), minute ventilation VE), and resting energy expenditure (REE). When compared with predicted normal values for sex, height, and body surface area (BSA), decreases (mean % predicted, +/- SE) were observed in expiratory reserve volume (ERV, 36 +/- 5); forced expiratory volume in 1 second (FEV1, 73 +/- 5); forced expiratory flow between 25% and 75% of vital capacity (FEF25-75%, 70 +/- 6); DLCO, absolute (52 +/- 3) and corrected (DLCO/VA, 71 +/- 5); and MVV (62 +/- 5). Residual volume (RV), RV/total lung capacity (TLC), VE, and REE were elevated. Other lung volumes were normal. Thus, obese children have altered pulmonary function, which is characterized by reductions in DLCO and ventilatory muscle endurance and airway narrowing. These alterations may reflect extrinsic mechanical compression on the lung and thorax, and/or intrinsic changes within the lung. The reduced DLCO may result from decreases in alveolar surface area relative to lung volume.
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Affiliation(s)
- L S Inselma
- Department of Pediatrics, Newington Children's Hospital, Connecticut
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17
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Camana GP, Gortan L, Vigliani R, Milanese A, Vergara E, Carbone P. [Bilateral renal angiomyolipoma. Operative approach in a case with Wunderlich syndrome]. MINERVA UROL NEFROL 1992; 44:35-42. [PMID: 1529396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
After a wide-ranging review of the literature on the topic, the case of a 33-year-old woman is reported who, after an emergency right nephrectomy performed six years earlier due to renal angiomyolipoma with Wunderlich's syndrome, was admitted with anemia and acute shock following left renal hemorrhage. Having overcome the acute stage, a number of tests were carried out (echography, urography, abdominal CT, aortography) before the patient underwent conservative surgery in the form of lower heminephrectomy. The postoperative urography is presented showing satisfactory residual renal function which enabled the patient to live normally. The Authors discuss the criteria which lead them to select conservative surgical treatment.
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Affiliation(s)
- G P Camana
- Divisione di Urologia, USSL 44, Ospedale Civile E. Agnelli, Pinerolo, Torino
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18
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Milanese A, Camana GP, Carbone P. [Echinococcosis cyst in the pelvic cavity. Presentation of a case]. MINERVA UROL NEFROL 1991; 43:301-3. [PMID: 1812575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The incidence of echinococcal cysts and their percentage occurrence in different human organs is reported. A case of hydatid cyst localisation in the pelvic cavity is reported and the pathogenesis of this infrequent localisation discussed. The various hypotheses: haematogenous and fall into the peritoneal cavity are examined; then the diagnostic approach and conservative surgical therapy employed.
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Affiliation(s)
- A Milanese
- Divisione di Urologia, Ospedale Civile E. Agnelli, Pinerolo, Torino
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19
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Abstract
Eight malnourished children with neuromuscular spinal deformity were treated with jejunostomy tubes for supplemental feeding to attain appropriate weight before reconstructive surgery. All patients had significant gastro-esophageal reflux and had failed to gain weight during an eight-month oral supplementation program. There were no complications associated with the placement or use of the jejunostomy feeding tubes and all patients gained weight in a safe and predictable fashion, had successful spinal fusion and have maintained satisfactory weight at follow-up. Jejunostomy feeding is a safe and effective method of correcting malnutrition in patients with spinal deformity which precludes gastrostomy and Nissen fundoplication.
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Affiliation(s)
- J S Jaivin
- Department of Orthopaedics, University of Connecticut School of Medicine, Farmington 06032
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20
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Milanese A, Camana G, Carbone P. [Diagnostic problems in pyelo-ureteral duplication. Presentation of a case]. MINERVA UROL NEFROL 1990; 42:163-6. [PMID: 2080443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A case of left pyeloureteral duplication with half a kidney functionally excluded is reported. After some mention of embryology to evidence the pathogenetic moments of the malformation, the clinical case is described, particular reference being made to the problems encountered in reaching diagnosis, in spite of the patient having undergone varied and repeated investigations. Superior heminephrectomy and total ureterectomy led to the clinical wellbeing of the patient.
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Affiliation(s)
- A Milanese
- Divisione di Urologia, USSL n. 44, Ospedale Civile E. Agnelli, Pinerolo, Torino
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21
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Abstract
This case report describes a 14-year-old boy presenting with a barrel-chested appearance and a complaint of shortness of breath on exertion. The patient had a long history of severe constipation with overflow incontinence. Physical examination suggested limited diaphragmatic excursion. Initial pulmonary function studies showed a restrictive pattern. Catharsis resulted in an 11-lb weight loss and normalization of pulmonary function. We speculate that the extrinsic upward pressure imposed on the diaphragm by a full bowel resulted in increased anteroposterior diameter, decreased lung height, and a reversible restrictive pattern on pulmonary function studies.
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22
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Stradi R, Rossi E, Dubini F, Balsari A, Desideri D, Milanese A. [Synthesis and microbiologic activity of a new class of imidazole derivatives]. Farmaco Sci 1986; 41:558-65. [PMID: 3743748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The synthesis of a new class of imidazole derivatives with the structure of 1-[2-(2,4-dichlorophenyl)-2-tert.amino]ethylimidazoles is described. Preliminary data on their antimicrobial activity are reported.
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23
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Milanese A, Scattolin F, Camana G. Esiti a Distanza Della Nefrolitotomia Bivalve in Ipotermia. Urologia 1983. [DOI: 10.1177/039156038305000417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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24
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Scattolin F, Milanese A, Camana G, Peyrot G. Uretroplastica Secondo Kishev Nelle Stenosi Dell'Uretra Maschile. Urologia 1982. [DOI: 10.1177/039156038204900615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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25
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Vercesi E, Milanese A, Rizzello N. Tumori Intrascrotali Non Testicolari: Presentazione Di Tre Casi E Revisione Della Letteratura. Urologia 1981. [DOI: 10.1177/039156038104800426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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26
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Rizzello N, Rossini FP, Carbone P, Milanese A. [Sigmoid neoplasms in patients with ureterosigmoidostomy]. Minerva Urol 1981; 33:149-52. [PMID: 6275255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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27
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Rizzello N, Carbone P, Milanese A, Lasaponara F. [Analysis of 140 renal neoplasms. Survival evaluated on the basis of various parameters]. Minerva Urol 1981; 33:143-8. [PMID: 7322107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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28
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Carbone P, Milanese A, Rizzello N. La Nostra Esperienza in Tema Di Ureterocutaneostomia. Urologia 1981. [DOI: 10.1177/039156038104800126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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29
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Lasaponara F, Milanese A, Rizzello N. [Neoplasia in vesical hernia]. Minerva Urol 1979; 31:137-9. [PMID: 90329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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