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Dive into the research topics where Peter Cimermancic is active.

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Featured researches published by Peter Cimermancic.


Nucleic Acids Research | 2011

antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences

Marnix H. Medema; Kai Blin; Peter Cimermancic; Victor de Jager; Piotr Zakrzewski; Michael A. Fischbach; Tilmann Weber; Eriko Takano; Rainer Breitling

Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs. To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes. However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources. Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others). It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view. antiSMASH is available at http://antismash.secondarymetabolites.org.


Nature | 2012

Global landscape of HIV-human protein complexes

Stefanie Jäger; Peter Cimermancic; Natali Gulbahce; Jeffrey R. Johnson; Kathryn E. McGovern; Starlynn C. Clarke; Michael Shales; Gaelle Mercenne; Lars Pache; Kathy H. Li; Hilda Hernandez; Gwendolyn M. Jang; Shoshannah L. Roth; Eyal Akiva; John Marlett; Melanie Stephens; Iván D’Orso; Jason Fernandes; Marie Fahey; Cathal Sean Mahon; Anthony J. O’Donoghue; Aleksandar Todorovic; John H. Morris; David A. Maltby; Tom Alber; Gerard Cagney; Frederic D. Bushman; John A. T. Young; Sumit K. Chanda; Wesley I. Sundquist

Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host’s cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV–human protein–protein interactions involving 435 individual human proteins, with ∼40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.


Cell | 2014

Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters.

Peter Cimermancic; Marnix H. Medema; Jan Claesen; Kenji L. Kurita; Laura C. Wieland Brown; Konstantinos Mavrommatis; Amrita Pati; Paul A. Godfrey; Michael Koehrsen; Jon Clardy; Bruce W. Birren; Eriko Takano; Andrej Sali; Roger G. Linington; Michael A. Fischbach

Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the predicted BGCs revealed large gene cluster families, the vast majority uncharacterized. We experimentally characterized the most prominent family, consisting of two subfamilies of hundreds of BGCs distributed throughout the Proteobacteria; their products are aryl polyenes, lipids with an aryl head group conjugated to a polyene tail. We identified a distant relationship to a third subfamily of aryl polyene BGCs, and together the three subfamilies represent the largest known family of biosynthetic gene clusters, with more than 1,000 members. Although these clusters are widely divergent in sequence, their small molecule products are remarkably conserved, indicating for the first time the important roles these compounds play in Gram-negative cell biology.


Nature Chemical Biology | 2011

A mass spectrometry-guided genome mining approach for natural product peptidogenomics

Roland Kersten; Yu-Liang Yang; Yuquan Xu; Peter Cimermancic; Sang-Jip Nam; William Fenical; Michael A. Fischbach; Bradley S. Moore; Pieter C. Dorrestein

Peptide natural products exhibit broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce Natural Product Peptidogenomics (NPP), a new mass spectrometry-guided genome mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo MSn structures to genomics-based structures following current biosynthetic logic. In this study we demonstrate that NPP enabled the rapid characterization of >10 chemically diverse ribosomal and nonribosomal peptide natural products of novel composition from streptomycete bacteria as a proof of concept to begin automating the genome mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which from well-characterized model streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.


Nature | 2012

Vif hijacks CBF-β to degrade APOBEC3G and promote HIV-1 infection

Stefanie Jäger; Dong Young Kim; Judd F. Hultquist; Keisuke Shindo; Rebecca S. LaRue; Eunju Kwon; Ming Li; Brett D. Anderson; Linda Yen; David J. Stanley; Cathal Sean Mahon; Joshua Kane; Kathy Franks-Skiba; Peter Cimermancic; Alma L. Burlingame; Andrej Sali; Charles S. Craik; Reuben S. Harris; John D. Gross; Nevan J. Krogan

Restriction factors, such as the retroviral complementary DNA deaminase APOBEC3G, are cellular proteins that dominantly block virus replication. The AIDS virus, human immunodeficiency virus type 1 (HIV-1), produces the accessory factor Vif, which counteracts the host’s antiviral defence by hijacking a ubiquitin ligase complex, containing CUL5, ELOC, ELOB and a RING-box protein, and targeting APOBEC3G for degradation. Here we reveal, using an affinity tag/purification mass spectrometry approach, that Vif additionally recruits the transcription cofactor CBF-β to this ubiquitin ligase complex. CBF-β, which normally functions in concert with RUNX DNA binding proteins, allows the reconstitution of a recombinant six-protein assembly that elicits specific polyubiquitination activity with APOBEC3G, but not the related deaminase APOBEC3A. Using RNA knockdown and genetic complementation studies, we also demonstrate that CBF-β is required for Vif-mediated degradation of APOBEC3G and therefore for preserving HIV-1 infectivity. Finally, simian immunodeficiency virus (SIV) Vif also binds to and requires CBF-β to degrade rhesus macaque APOBEC3G, indicating functional conservation. Methods of disrupting the CBF-β–Vif interaction might enable HIV-1 restriction and provide a supplement to current antiviral therapies that primarily target viral proteins.


Cell | 2014

Molecular Architecture of the 40S⋅eIF1⋅eIF3 Translation Initiation Complex

Jan P. Erzberger; Florian Stengel; Riccardo Pellarin; Suyang Zhang; Tanja Schaefer; Christopher H S Aylett; Peter Cimermancic; Daniel Boehringer; Andrej Sali; Ruedi Aebersold; Nenad Ban

Summary Eukaryotic translation initiation requires the recruitment of the large, multiprotein eIF3 complex to the 40S ribosomal subunit. We present X-ray structures of all major components of the minimal, six-subunit Saccharomyces cerevisiae eIF3 core. These structures, together with electron microscopy reconstructions, cross-linking coupled to mass spectrometry, and integrative structure modeling, allowed us to position and orient all eIF3 components on the 40S⋅eIF1 complex, revealing an extended, modular arrangement of eIF3 subunits. Yeast eIF3 engages 40S in a clamp-like manner, fully encircling 40S to position key initiation factors on opposite ends of the mRNA channel, providing a platform for the recruitment, assembly, and regulation of the translation initiation machinery. The structures of eIF3 components reported here also have implications for understanding the architecture of the mammalian 43S preinitiation complex and the complex of eIF3, 40S, and the hepatitis C internal ribosomal entry site RNA.


Cell Host & Microbe | 2014

Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine.

Brianna B. Williams; Andrew H. Van Benschoten; Peter Cimermancic; Mohamed S. Donia; Michael B. Zimmermann; Mao Taketani; Atsushi Ishihara; Purna C. Kashyap; J.S. Fraser; Michael A. Fischbach

Several recent studies describe the influence of the gut microbiota on host brain and behavior. However, the mechanisms responsible for microbiota-nervous system interactions are largely unknown. Using a combination of genetics, biochemistry, and crystallography, we identify and characterize two phylogenetically distinct enzymes found in the human microbiome that decarboxylate tryptophan to form the β-arylamine neurotransmitter tryptamine. Although this enzymatic activity is exceedingly rare among bacteria more broadly, analysis of the Human Microbiome Project data demonstrate that at least 10% of the human population harbors at least one bacterium encoding a tryptophan decarboxylase in their gut community. Our results uncover a previously unrecognized enzymatic activity that can give rise to host-modulatory compounds and suggests a potential direct mechanism by which gut microbiota can influence host physiology, including behavior.


Molecular & Cellular Proteomics | 2012

Host Cell Interactome of HIV-1 Rev Includes RNA Helicases Involved in Multiple Facets of Virus Production

Souad Naji; Géza Ambrus; Peter Cimermancic; Jason R. Reyes; Jeffrey R. Johnson; Rebecca Filbrandt; Michael Huber; Nevan J. Krogan; John R. Yates; Andrew C. S. Saphire; Larry Gerace

The HIV-1 Rev protein plays a key role in the late phase of virus replication. It binds to the Rev Response Element found in underspliced HIV mRNAs, and drives their nuclear export by the CRM1 receptor pathway. Moreover, mounting evidence suggests that Rev has additional functions in viral replication. Here we employed proteomics and statistical analysis to identify candidate host cell factors that interact with Rev. For this we studied Rev complexes assembled in vitro with nuclear or cytosolic extracts under conditions emulating various intracellular environments of Rev. We ranked the protein-protein interactions by combining several statistical features derived from pairwise comparison of conditions in which the abundance of the binding partners changed. As a validation set, we selected the eight DEAD/H box proteins of the RNA helicase family from the top-ranking 5% of the proteins. These proteins all associate with ectopically expressed Rev in immunoprecipitates of cultured cells. From gene knockdown approaches, our work in combination with previous studies indicates that six of the eight DEAD/H proteins are linked to HIV production in our cell model. In a more detailed analysis of infected cells where either DDX3X, DDX5, DDX17, or DDX21 was silenced, we observed distinctive phenotypes for multiple replication features, variously involving virus particle release, the levels of unspliced and spliced HIV mRNAs, and the nuclear and cytoplasmic concentrations of these transcripts. Altogether the work indicates that our top-scoring data set is enriched in Rev-interacting proteins relevant to HIV replication. Our more detailed analysis of several Rev-interacting DEAD proteins suggests a complex set of functions for the helicases in regulation of HIV mRNAs. The strategy used here for identifying Rev interaction partners should prove effective for analyzing other viral and cellular proteins.


Nature Chemical Biology | 2014

Covalent docking of large libraries for the discovery of chemical probes

Nir London; Rand M. Miller; Shyam Krishnan; Kenji Uchida; John J. Irwin; Oliv Eidam; Lucie Gibold; Peter Cimermancic; Richard Bonnet; Brian K. Shoichet; Jack Taunton

Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency, and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1, and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org).


PLOS Computational Biology | 2014

A systematic computational analysis of biosynthetic gene cluster evolution: lessons for engineering biosynthesis.

Marnix H. Medema; Peter Cimermancic; Andrej Sali; Eriko Takano; Michael A. Fischbach

Bacterial secondary metabolites are widely used as antibiotics, anticancer drugs, insecticides and food additives. Attempts to engineer their biosynthetic gene clusters (BGCs) to produce unnatural metabolites with improved properties are often frustrated by the unpredictability and complexity of the enzymes that synthesize these molecules, suggesting that genetic changes within BGCs are limited by specific constraints. Here, by performing a systematic computational analysis of BGC evolution, we derive evidence for three findings that shed light on the ways in which, despite these constraints, nature successfully invents new molecules: 1) BGCs for complex molecules often evolve through the successive merger of smaller sub-clusters, which function as independent evolutionary entities. 2) An important subset of polyketide synthases and nonribosomal peptide synthetases evolve by concerted evolution, which generates sets of sequence-homogenized domains that may hold promise for engineering efforts since they exhibit a high degree of functional interoperability, 3) Individual BGC families evolve in distinct ways, suggesting that design strategies should take into account family-specific functional constraints. These findings suggest novel strategies for using synthetic biology to rationally engineer biosynthetic pathways.

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Andrej Sali

University of California

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Michael A. Fischbach

California Institute for Quantitative Biosciences

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Marnix H. Medema

Wageningen University and Research Centre

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Eriko Takano

University of Manchester

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Riccardo Pellarin

California Institute for Quantitative Biosciences

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Amrita Pati

Joint Genome Institute

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