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Nodelman IM, Das S, Faustino AM, Fried SD, Bowman GD, Armache JP. Nucleosome recognition and DNA distortion by the Chd1 remodeler in a nucleotide-free state. Nat Struct Mol Biol 2022; 29:121-129. [PMID: 35173352 DOI: 10.1038/s41594-021-00719-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 12/23/2021] [Indexed: 12/12/2022]
Abstract
Chromatin remodelers are ATP-dependent enzymes that reorganize nucleosomes within all eukaryotic genomes. Here we report a complex of the Chd1 remodeler bound to a nucleosome in a nucleotide-free state, determined by cryo-EM to 2.3 Å resolution. The remodeler stimulates the nucleosome to absorb an additional nucleotide on each strand at two different locations: on the tracking strand within the ATPase binding site and on the guide strand one helical turn from the ATPase motor. Remarkably, the additional nucleotide on the tracking strand is associated with a local transformation toward an A-form geometry, explaining how sequential ratcheting of each DNA strand occurs. The structure also reveals a histone-binding motif, ChEx, which can block opposing remodelers on the nucleosome and may allow Chd1 to participate in histone reorganization during transcription.
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Affiliation(s)
- Ilana M Nodelman
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA
| | - Sayan Das
- Department of Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA
| | | | - Stephen D Fried
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA.,Department of Chemistry, Johns Hopkins University, Baltimore, MD, USA
| | - Gregory D Bowman
- Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA.
| | - Jean-Paul Armache
- Department of Biochemistry and Molecular Biology and the Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA.
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2
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Vijayakumar P, Raut AA, Chingtham S, Murugkar HV, Kulkarni DD, Sood R, Singh VP, Mishra A. Proteomic analysis of differential expression of lung proteins in response to highly pathogenic avian influenza virus infection in chickens. Arch Virol 2021; 167:141-152. [PMID: 34786609 DOI: 10.1007/s00705-021-05287-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 09/16/2021] [Indexed: 12/21/2022]
Abstract
Elucidation of the molecular pathogenesis underlying virus-host interactions is important for the development of new diagnostic and therapeutic strategies against highly pathogenic avian influenza (HPAI) virus infection in chickens. However, the pathogenesis of HPAI virus in chickens is not completely understood. To identify the intracellular signaling pathways and critical host proteins associated with influenza pathogenesis, we analyzed the lung proteome of a chicken infected with HPAI H5N1 virus (A/duck/India/02CA10/2011/Agartala). Mass spectrometry data sets were searched against the chicken UniProt reference database. At the local false discovery rate level of 5%, a total of 3313 proteins with the presence of at least one unique peptide were identified in the chicken lung proteome datasets. Differential expression analysis of these proteins showed that 247 and 1754 proteins were downregulated at 12 h and 48 h postinfection, respectively. We observed expression of proteins of the predominant signaling pathways, including Toll-like receptors (TLRs), retinoic acid-inducible gene I-like receptors (RLRs), NOD-like receptors (NLRs), and JAK-STAT signaling. Activation of these pathways is associated with the cytokine storm effect and thus may be the cause of the severity of HPAI H5N1 infection in chickens. We also observed the expression of myeloid differentiation primary response protein (MyD88), inhibitor of nuclear factor kappa B kinase subunit beta (IKBKB), interleukin 1 receptor associated kinase 4 (IRAK4), RELA proto-oncogene NF-κB subunit (RELA), and mitochondrial antiviral signaling protein (MAVS), which are involved in critical signaling pathways, as well as other, less-commonly identified proteins such as hepatocyte nuclear factor 4 alpha (HNF4A), ELAV-like RNA binding protein 1 (ELAVL1), fibronectin 1 (FN1), COP9 signalosome subunit 5 (COPS5), cullin 1 (CUL1), breast cancer type 1 susceptibility protein (BRCA1), and the FYN proto-oncogene Src family tyrosine kinase (FYN) as main hub proteins that might play important roles in influenza pathogenesis in chickens. In summary, we identified the signaling pathways and the proteomic determinants associated with disease pathogenesis in chickens infected with HPAI H5N1 virus.
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Affiliation(s)
- Periyasamy Vijayakumar
- Pathogenomics Laboratory, ICAR-National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India.,Veterinary College and Research Institute, Tamil Nadu Veterinary and Animal Sciences University, Orathanadu, 614625, Tamil Nadu, India
| | - Ashwin Ashok Raut
- Pathogenomics Laboratory, ICAR-National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Santhalembi Chingtham
- Pathogenomics Laboratory, ICAR-National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Harshad V Murugkar
- ICAR -National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Diwakar D Kulkarni
- ICAR -National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Richa Sood
- ICAR -National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Vijendra Pal Singh
- ICAR -National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India
| | - Anamika Mishra
- Pathogenomics Laboratory, ICAR-National Institute of High-Security Animal Diseases, OIE Reference lab for Avian Influenza, Bhopal, 462021, Madhya Pradesh, India.
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Rawlinson C, Jones D, Rakshit S, Meka S, Moffat CS, Moolhuijzen P. Hierarchical clustering of MS/MS spectra from the firefly metabolome identifies new lucibufagin compounds. Sci Rep 2020; 10:6043. [PMID: 32269256 PMCID: PMC7142086 DOI: 10.1038/s41598-020-63036-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 03/24/2020] [Indexed: 01/09/2023] Open
Abstract
Metabolite identification is the greatest challenge when analysing metabolomics data, as only a small proportion of metabolite reference standards exist. Clustering MS/MS spectra is a common method to identify similar compounds, however interrogation of underlying signature fragmentation patterns within clusters can be problematic. Previously published high-resolution LC-MS/MS data from the bioluminescent beetle (Photinus pyralis) provided an opportunity to mine new specialized metabolites in the lucibufagin class, compounds important for defense against predation. We aimed to 1) provide a workflow for hierarchically clustering MS/MS spectra for metabolomics data enabling users to cluster, visualise and easily interrogate the identification of underlying cluster ion profiles, and 2) use the workflow to identify key fragmentation patterns for lucibufagins in the hemolymph of P. pyralis. Features were aligned to their respective MS/MS spectra, then product ions were dynamically binned and resulting spectra were hierarchically clustered and grouped based on a cutoff distance threshold. Using the simplified visualization and the interrogation of cluster ion tables the number of lucibufagins was expanded from 17 to a total of 29.
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Affiliation(s)
- Catherine Rawlinson
- Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia.
| | - Darcy Jones
- Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Suman Rakshit
- Statistics for the Australian Grains Industry-West, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Shiv Meka
- Curtin Institute for Computation, Curtin University, Bentley, Western Australia, Australia
| | - Caroline S Moffat
- Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Paula Moolhuijzen
- Centre for Crop and Disease Management, School of Molecular and Life Sciences, Curtin University, Bentley, Western Australia, Australia.
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Searle BC, Swearingen KE, Barnes CA, Schmidt T, Gessulat S, Küster B, Wilhelm M. Generating high quality libraries for DIA MS with empirically corrected peptide predictions. Nat Commun 2020; 11:1548. [PMID: 32214105 PMCID: PMC7096433 DOI: 10.1038/s41467-020-15346-1] [Citation(s) in RCA: 126] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 02/28/2020] [Indexed: 11/09/2022] Open
Abstract
Data-independent acquisition approaches typically rely on experiment-specific spectrum libraries, requiring offline fractionation and tens to hundreds of injections. We demonstrate a library generation workflow that leverages fragmentation and retention time prediction to build libraries containing every peptide in a proteome, and then refines those libraries with empirical data. Our method specifically enables rapid, experiment-specific library generation for non-model organisms, which we demonstrate using the malaria parasite Plasmodium falciparum, and non-canonical databases, which we show by detecting missense variants in HeLa.
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Affiliation(s)
- Brian C Searle
- Institute for Systems Biology, Seattle, WA, USA.
- Proteome Software, Inc., Portland, OR, USA.
| | | | | | | | - Siegfried Gessulat
- Technical University of Munich, Freising, Germany
- SAP SE, Potsdam, Germany
| | - Bernhard Küster
- Technical University of Munich, Freising, Germany
- Bavarian Center for Biomolecular Mass Spectrometry, Freising, Germany
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Sex Differences in Colon Cancer Metabolism Reveal A Novel Subphenotype. Sci Rep 2020; 10:4905. [PMID: 32184446 PMCID: PMC7078199 DOI: 10.1038/s41598-020-61851-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Accepted: 03/04/2020] [Indexed: 11/09/2022] Open
Abstract
Women have a lower incidence of colorectal cancer (CRC) than men, however, they have a higher incidence of right-sided colon cancer (RCC). This is of concern as patients with RCC have the poorest clinical outcomes among all CRC patients. Aberrant metabolism is a known hallmark and therapeutic target for cancer. We propose that metabolic subphenotypes exist between CRCs due to intertumoral molecular and genomic variation, and differences in environmental milieu of the colon which vary between the sexes. Metabolomics analysis of patient colon tumors (n = 197) and normal tissues (n = 39) revealed sex-specific metabolic subphenotypes dependent on anatomic location. Tumors from women with RCC were nutrient-deplete, showing enhanced energy production to fuel asparagine synthesis and amino acid uptake. The clinical importance of our findings were further investigated in an independent data set from The Cancer Genomic Atlas, and demonstrated that high asparagine synthetase (ASNS) expression correlated with poorer survival for women. This is the first study to show a unique, nutrient-deplete metabolic subphenotype in women with RCC, with implications for tumor progression and outcomes in CRC patients.
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Geier B, Sogin EM, Michellod D, Janda M, Kompauer M, Spengler B, Dubilier N, Liebeke M. Spatial metabolomics of in situ host-microbe interactions at the micrometre scale. Nat Microbiol 2020; 5:498-510. [PMID: 32015496 DOI: 10.1038/s41564-019-0664-6] [Citation(s) in RCA: 112] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 12/16/2019] [Indexed: 11/09/2022]
Abstract
Spatial metabolomics describes the location and chemistry of small molecules involved in metabolic phenotypes, defence molecules and chemical interactions in natural communities. Most current techniques are unable to spatially link the genotype and metabolic phenotype of microorganisms in situ at a scale relevant to microbial interactions. Here, we present a spatial metabolomics pipeline (metaFISH) that combines fluorescence in situ hybridization (FISH) microscopy and high-resolution atmospheric-pressure matrix-assisted laser desorption/ionization mass spectrometry to image host-microbe symbioses and their metabolic interactions. The metaFISH pipeline aligns and integrates metabolite and fluorescent images at the micrometre scale to provide a spatial assignment of host and symbiont metabolites on the same tissue section. To illustrate the advantages of metaFISH, we mapped the spatial metabolome of a deep-sea mussel and its intracellular symbiotic bacteria at the scale of individual epithelial host cells. Our analytical pipeline revealed metabolic adaptations of the epithelial cells to the intracellular symbionts and variation in metabolic phenotypes within a single symbiont 16S rRNA phylotype, and enabled the discovery of specialized metabolites from the host-microbe interface. metaFISH provides a culture-independent approach to link metabolic phenotypes to community members in situ and is a powerful tool for microbiologists across fields.
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Affiliation(s)
- Benedikt Geier
- Max Planck Institute for Marine Microbiology, Bremen, Germany.
| | - Emilia M Sogin
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Dolma Michellod
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Moritz Janda
- Max Planck Institute for Marine Microbiology, Bremen, Germany
| | - Mario Kompauer
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Giessen, Germany
| | - Bernhard Spengler
- Institute of Inorganic and Analytical Chemistry, Justus Liebig University Giessen, Giessen, Germany
| | - Nicole Dubilier
- Max Planck Institute for Marine Microbiology, Bremen, Germany
- MARUM, University of Bremen, Bremen, Germany
| | - Manuel Liebeke
- Max Planck Institute for Marine Microbiology, Bremen, Germany.
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Sellers TA, Kushi LH, Potter JD, Kaye SA, Nelson CL, McGovern PG, Folsom AR. Effect of family history, body-fat distribution, and reproductive factors on the risk of postmenopausal breast cancer. N Engl J Med 1992; 326:1323-9. [PMID: 1565145 DOI: 10.1056/nejm199205143262004] [Citation(s) in RCA: 162] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND A family history of breast cancer reflects shared cultural factors, genetic predisposition, or both. There is evidence that the estimated risk associated with a family history of breast cancer increases multiplicatively in combination with other risk factors. We examined the combined effect of family history and anthropometric and reproductive factors on the risk of breast cancer in postmenopausal women. METHODS Using data from a prospective cohort study, we studied 37,105 women 55 to 69 years of age to determine whether known risk factors for breast cancer are modified by a reported family history at the time of entry into the study. RESULTS During the first 4 years of follow-up, 493 new breast cancers were diagnosed. The association of the waist-to-hip ratio (the circumference of the waist divided by that of the hips) with the risk of breast cancer was limited predominantly to women with a family history of breast cancer; the age-adjusted relative risk of breast cancer for the women above the fourth quintile for waist-to-hip ratio as compared with those below the first quintile was 3.2 in women with a family history of breast cancer and 1.2 for women without such a family history. An interaction was observed between a family history of breast cancer and the number of live-born children; the protective effect of higher parity was observed primarily among women with a family history of breast cancer. Similarly, the age-adjusted relative risk of breast cancer associated with a late age at first pregnancy (i.e., greater than or equal to 30 years) was 5.8 for women with a family history of breast cancer and 2.0 for women without such a family history. CONCLUSIONS The increase in the risk of breast cancer associated with a high waist-to-hip ratio, low parity, or greater age at first pregnancy is more pronounced among women with a family history of breast cancer. These findings suggest etiologic differences between familial breast cancer and the sporadic form.
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Affiliation(s)
- T A Sellers
- Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis
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