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Choi J, Jang H, Xuan Z, Park D. Emerging roles of ATG9/ATG9A in autophagy: implications for cell and neurobiology. Autophagy 2024; 20:2373-2387. [PMID: 39099167 DOI: 10.1080/15548627.2024.2384349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 07/01/2024] [Accepted: 07/22/2024] [Indexed: 08/06/2024] Open
Abstract
Atg9, the only transmembrane protein among many autophagy-related proteins, was first identified in the year 2000 in yeast. Two homologs of Atg9, ATG9A and ATG9B, have been found in mammals. While ATG9B shows a tissue-specific expression pattern, such as in the placenta and pituitary gland, ATG9A is ubiquitously expressed. Additionally, ATG9A deficiency leads to severe defects not only at the molecular and cellular levels but also at the organismal level, suggesting key and fundamental roles for ATG9A. The subcellular localization of ATG9A on small vesicles and its functional relevance to autophagy have suggested a potential role for ATG9A in the lipid supply during autophagosome biogenesis. Nevertheless, the precise role of ATG9A in the autophagic process has remained a long-standing mystery, especially in neurons. Recent findings, however, including structural, proteomic, and biochemical analyses, have provided new insights into its function in the expansion of the phagophore membrane. In this review, we aim to understand various aspects of ATG9 (in invertebrates and plants)/ATG9A (in mammals), including its localization, trafficking, and other functions, in nonneuronal cells and neurons by comparing recent discoveries related to ATG9/ATG9A and proposing directions for future research.Abbreviation: AP-4: adaptor protein complex 4; ATG: autophagy related; cKO: conditional knockout; CLA-1: CLArinet (functional homolog of cytomatrix at the active zone proteins piccolo and fife); cryo-EM: cryogenic electron microscopy; ER: endoplasmic reticulum; KO: knockout; PAS: phagophore assembly site; PtdIns3K: class III phosphatidylinositol 3-kinase; PtdIns3P: phosphatidylinositol-3-phosphate; RB1CC1/FIP200: RB1 inducible coiled-coil 1; SV: synaptic vesicle; TGN: trans-Golgi network; ULK: unc-51 like autophagy activating kinase; WIPI2: WD repeat domain, phosphoinositide interacting 2.
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Affiliation(s)
- Jiyoung Choi
- Department of Medical and Biological Sciences, The Catholic University of Korea, Bucheon, South Korea
- Department of Biotechnology, The Catholic University of Korea, Bucheon, South Korea
| | - Haeun Jang
- Department of Medical and Biological Sciences, The Catholic University of Korea, Bucheon, South Korea
| | - Zhao Xuan
- School of Biology and Ecology, University of Maine, Orono, ME, USA
| | - Daehun Park
- Department of Medical and Biological Sciences, The Catholic University of Korea, Bucheon, South Korea
- Department of Biotechnology, The Catholic University of Korea, Bucheon, South Korea
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2
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Song S, Zhang J. In search of the genetic variants of human sex ratio at birth: was Fisher wrong about sex ratio evolution? Proc Biol Sci 2024; 291:20241876. [PMID: 39406345 PMCID: PMC11479764 DOI: 10.1098/rspb.2024.1876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 09/06/2024] [Accepted: 09/09/2024] [Indexed: 10/20/2024] Open
Abstract
The human sex ratio (fraction of males) at birth is close to 0.5 at the population level, an observation commonly explained by Fisher's principle. However, past human studies yielded conflicting results regarding the existence of sex ratio-influencing mutations-a prerequisite to Fisher's principle, raising the question of whether the nearly even population sex ratio is instead dictated by the random X/Y chromosome segregation in male meiosis. Here we show that, because a person's offspring sex ratio (OSR) has an enormous measurement error, a gigantic sample is required to detect OSR-influencing genetic variants. Conducting a UK Biobank-based genome-wide association study that is more powerful than previous studies, we detect an OSR-associated genetic variant, which awaits verification in independent samples. Given the abysmal precision in measuring OSR, it is unsurprising that the estimated heritability of OSR is effectively zero. We further show that OSR's estimated heritability would remain virtually zero even if OSR is as genetically variable as the highly heritable human standing height. These analyses, along with simulations of human sex ratio evolution under selection, demonstrate the compatibility of the observed genetic architecture of human OSR with Fisher's principle and render it plausible that multiple OSR-influencing genetic variants segregate among humans.
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Affiliation(s)
- Siliang Song
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI48109, USA
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI48109, USA
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3
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Van Sciver RE, Caspary T. A prioritization tool for cilia-associated genes and their in vivo resources unveils new avenues for ciliopathy research. Dis Model Mech 2024; 17:dmm052000. [PMID: 39263856 PMCID: PMC11512102 DOI: 10.1242/dmm.052000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 09/04/2024] [Indexed: 09/13/2024] Open
Abstract
Defects in ciliary signaling or mutations in proteins that localize to primary cilia lead to a class of human diseases known as ciliopathies. Approximately 10% of mammalian genes encode cilia-associated proteins, and a major gap in the cilia research field is knowing which genes to prioritize to study and finding the in vivo vertebrate mutant alleles and reagents available for their study. Here, we present a unified resource listing the cilia-associated human genes cross referenced to available mouse and zebrafish mutant alleles, and their associated phenotypes, as well as expression data in the kidney and functional data for vertebrate Hedgehog signaling. This resource empowers researchers to easily sort and filter genes based on their own expertise and priorities, cross reference with newly generated -omics datasets, and quickly find in vivo resources and phenotypes associated with a gene of interest.
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Affiliation(s)
- Robert E. Van Sciver
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Tamara Caspary
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
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4
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Ehrhardt B, Roeder T, Krauss-Etschmann S. Drosophila melanogaster as an Alternative Model to Higher Organisms for In Vivo Lung Research. Int J Mol Sci 2024; 25:10324. [PMID: 39408654 PMCID: PMC11476989 DOI: 10.3390/ijms251910324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Revised: 09/19/2024] [Accepted: 09/20/2024] [Indexed: 10/20/2024] Open
Abstract
COPD and asthma are lung diseases that cause considerable burden to more than 800 million people worldwide. As both lung diseases are so far incurable, it is mandatory to understand the mechanisms underlying disease development and progression for developing novel therapeutic approaches. Exposures to environmental cues such as cigarette smoke in earliest life are known to increase disease risks in the individual's own future. To explore the pathomechanisms leading to later airway disease, mammalian models are instrumental. However, such in vivo experiments are time-consuming and burdensome for the animals, which applies in particular to transgenerational studies. Along this line, the fruit fly Drosophila melanogaster comes with several advantages for research in this field. The short lifespan facilitates transgenerational studies. A high number of evolutionary conserved signaling pathways, together with a large toolbox for tissue-specific gene modification, has the potential to identify novel target genes involved in disease development. A well-defined airway microbiome could help to untangle interactions between disease development and microbiome composition. In the following article, Drosophila melanogaster is therefore presented and discussed as an alternative in vivo model to investigate airway diseases that can complement and/or replace models in higher organisms.
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Affiliation(s)
- Birte Ehrhardt
- Division of Early Life Origins of Chronic Lung Diseases, Research Center Borstel-Leibniz Lung Center, Airway Research Center North (ARCN), German Center for Lung Research (DZL), 23845 Borstel, Germany
| | - Thomas Roeder
- Division of Molecular Physiology, Institute of Zoology, Christian-Albrechts University Kiel, Airway Research Center North (ARCN), German Center for Lung Research (DZL), 24118 Kiel, Germany
| | - Susanne Krauss-Etschmann
- Division of Early Life Origins of Chronic Lung Diseases, Research Center Borstel-Leibniz Lung Center, Airway Research Center North (ARCN), German Center for Lung Research (DZL), 23845 Borstel, Germany
- DZL Laboratory for Experimental Microbiome Research, Research Center Borstel, Airway Research Center North (ARCN), German Center for Lung Research (DZL), 23845 Borstel, Germany
- Institute of Experimental Medicine, Christian-Albrechts-University Kiel, 24105 Kiel, Germany
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Matentzoglu N, Bello SM, Stefancsik R, Alghamdi SM, Anagnostopoulos AV, Balhoff JP, Balk MA, Bradford YM, Bridges Y, Callahan TJ, Caufield H, Cuzick A, Carmody LC, Caron AR, de Souza V, Engel SR, Fey P, Fisher M, Gehrke S, Grove C, Hansen P, Harris NL, Harris MA, Harris L, Ibrahim A, Jacobsen JO, Köhler S, McMurry JA, Munoz-Fuentes V, Munoz-Torres MC, Parkinson H, Pendlington ZM, Pilgrim C, Robb SMC, Robinson PN, Seager J, Segerdell E, Smedley D, Sollis E, Toro S, Vasilevsky N, Wood V, Haendel MA, Mungall CJ, McLaughlin JA, Osumi-Sutherland D. The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.18.613276. [PMID: 39345458 PMCID: PMC11429889 DOI: 10.1101/2024.09.18.613276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.
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Affiliation(s)
| | | | | | | | | | - James P. Balhoff
- Renaissance Computing Institute, University of North Carolina, Chapel Hill, NC USA
| | - Meghan A. Balk
- Natural History Museum, University of Oslo, Oslo, Norway
| | | | | | - Tiffany J. Callahan
- Department of Biomedical Informatics, Columbia University Irving Medical Center
| | - Harry Caufield
- Lawrence Berkeley National. Laboratory, Berkeley, CA, USA
| | | | | | | | | | | | | | - Malcolm Fisher
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, US
| | | | | | | | - Nomi L. Harris
- Lawrence Berkeley National. Laboratory, Berkeley, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Erik Segerdell
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, US
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Bell M, Kane MS, Ouyang X, Young ME, Jegga AG, Chatham JC, Darley-Usmar V, Zhang J. Acute increase of protein O-GlcNAcylation in mice leads to transcriptome changes in the brain opposite to what is observed in Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.19.613769. [PMID: 39345543 PMCID: PMC11429956 DOI: 10.1101/2024.09.19.613769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Enhancing protein O-GlcNAcylation by pharmacological inhibition of the enzyme O-GlcNAcase (OGA) is explored as a strategy to decrease tau and amyloid-beta phosphorylation, aggregation, and pathology in Alzheimer's disease (AD). There is still more to be learned about the impact of enhancing global protein O-GlcNAcylation, which is important for understanding the mechanistic path of using OGA inhibition to treat AD. In this study, we investigated the acute effect of pharmacologically increasing O-GlcNAc levels, using OGA inhibitor Thiamet G (TG), on normal mouse brains. We hypothesized that the transcritome signature in respones to TG treatment provides a comprehensive view of the effect of OGA inhibition. We sacrificed the mice and dissected their brains after 3 hours of saline or 50 mg/kg TG treatment, and then performed mRNA sequencing using NovaSeq PE 150 (n=5 each group). We identified 1,234 significant differentially expressed genes with TG versus saline treatment. Functional enrichment analysis of the upregulated genes identified several upregulated pathways, including genes normally down in AD. Among the downregulated pathways were the cell adhesion pathway as well as genes normally up in AD and aging. When comparing acute to chronic TG treatment, protein autophosphorylation and kinase activity pathways were upregulated, whereas cell adhesion and astrocyte markers were downregulated in both datasets. Interestingly, mitochondrial genes and genes normally down in AD were up in acute treatment and down in chronic treatment. Data from this analysis will enable the evaluation of the mechanisms underlying the potential benefits of OGA inhibition in the treatment of AD. In particular, although OGA inhibitors are promising to treat AD, their downstream chronic effects related to bioenergetics may be a limiting factor. Abstract Figure
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7
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El Kassaby B, Castellanos F, Gerring M, Kunde-Ramamoorthy G, Bult CJ. MVAR: A Mouse Variation Registry. J Mol Biol 2024; 436:168518. [PMID: 38458603 DOI: 10.1016/j.jmb.2024.168518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 03/01/2024] [Indexed: 03/10/2024]
Abstract
The Mouse Variation Registry (MVAR) resource is a scalable registry of mouse single nucleotide variants and small indels and variant annotation. The resource accepts data in standard Variant Call Format (VCF) and assesses the uniqueness of the submitted variants via a canonicalization process. Novel variants are assigned a unique, persistent MVAR identifier; variants that are equivalent to an existing variant in the resource are associated with the existing identifier. Annotations for variant type, molecular consequence, impact, and genomic region in the context of specific transcripts and protein sequences are generated using Ensembl's Variant Effect Predictor (VEP) and Jannovar. Access to the data and annotations in MVAR are supported via an Application Programming Interface (API) and web application. Researchers can search the resource by gene symbol, genomic region, variant (expressed in Human Genome Variation Society syntax), refSNP identifiers, or MVAR identifiers. Tabular search results can be filtered by variant annotations (variant type, molecular consequence, impact, variant region) and viewed according to variant distribution across mouse strains. The registry currently comprises more than 99 million canonical single nucleotide variants for 581 strains of mice. MVAR is accessible from https://mvar.jax.org.
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8
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Le HH, Shorey-Kendrick LE, Hinds MT, McCarty OJT, Lo JO, Anderson DEJ. Effects of in utero exposure to Δ-9-tetrahydrocannabinol on cardiac extracellular matrix expression and vascular transcriptome in rhesus macaques. Am J Physiol Heart Circ Physiol 2024; 327:H701-H714. [PMID: 39028280 PMCID: PMC11442028 DOI: 10.1152/ajpheart.00181.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 06/27/2024] [Accepted: 07/07/2024] [Indexed: 07/20/2024]
Abstract
Delta-9-tetrahydrocannabinol (THC), the psychoactive component of cannabis, remains a schedule I substance, thus safety data regarding the effects on the cardiovascular and prenatal health are limited. Importantly, there is evidence showing prenatal cannabis exposure can negatively impact fetal organ development, including the cardiovascular system. THC can cross the placenta and bind to cannabinoid receptors expressed in the developing fetus, including on endothelial cells. To understand the impact of prenatal THC exposure on the fetal cardiovascular system, we used our rhesus macaque model of prenatal daily edible THC consumption. Before conception, animals were acclimated to THC (2.5 mg/7 kg/day, equivalent to a heavy medical cannabis dose) and maintained on this dose daily throughout pregnancy. Fetal tissue samples were collected at gestational day 155 (full term is 168 days). Our model showed that in utero THC exposure was associated with a decreased heart weight-to-body weight ratio in offspring, warranting further mechanistic investigation. Histological examination of the fetal cardiac and vascular tissues did not reveal any significant effect of THC exposure on the maturity of collagen within the fetal heart or the aorta. Total collagen III expression and elastin production and organization were unchanged. However, bulk RNA-sequencing of vascular cells in the umbilical vein, umbilical artery, and fetal aorta demonstrated that THC alters the fetal vascular transcriptome and is associated with upregulated expression of genes involved in carbohydrate metabolism and inflammation. The long-term consequences of these findings are unknown but suggest that prenatal THC exposure may affect cardiovascular development in offspring.NEW & NOTEWORTHY Prenatal cannabis use is increasing and despite the public health relevance, there is limited safety data regarding its impact on offspring cardiovascular health outcomes. We used a translational, nonhuman primate model of daily edible Δ-9-tetrahydrocannabinol (THC) consumption during pregnancy to assess its effects on the fetal cardiovascular system. THC-exposed fetal vascular tissues displayed upregulation of genes involved in cellular metabolism and inflammation, suggesting that prenatal THC exposure may impact fetal vascular tissues.
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Affiliation(s)
- Hillary H Le
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
| | - Lyndsey E Shorey-Kendrick
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, United States
| | - Monica T Hinds
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
- Center for Developmental Health, Oregon Health & Science University, Portland, Oregon, United States
- Knight Cardiovascular Institute, Oregon Health & Science University, Portland, Oregon, United States
- Division of Metabolic Health and Disease, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, United States
| | - Owen J T McCarty
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
| | - Jamie O Lo
- Division of Reproductive and Developmental Sciences, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, United States
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, Oregon, United States
| | - Deirdre E J Anderson
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
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9
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Moskalenko AM, Ikrin AN, Kozlova AV, Mukhamadeev RR, de Abreu MS, Riga V, Kolesnikova TO, Kalueff AV. Decoding Molecular Bases of Rodent Social Hetero-Grooming Behavior Using in Silico Analyses and Bioinformatics Tools. Neuroscience 2024; 554:146-155. [PMID: 38876356 DOI: 10.1016/j.neuroscience.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 06/03/2024] [Accepted: 06/06/2024] [Indexed: 06/16/2024]
Abstract
Highly prevalent in laboratory rodents, 'social' hetero-grooming behavior is translationally relevant to modeling a wide range of neuropsychiatric disorders. Here, we comprehensively evaluated all known to date mouse genes linked to aberrant hetero-grooming phenotype, and applied bioinformatics tools to construct a network of their established protein-protein interactions (PPI). We next identified several distinct molecular clusters within this complex network, including neuronal differentiation, cytoskeletal, WNT-signaling and synapsins-associated pathways. Using additional bioinformatics analyses, we further identified 'central' (hub) proteins within these molecular clusters, likely key for mouse hetero-grooming behavior. Overall, a more comprehensive characterization of intricate molecular pathways linked to aberrant rodent grooming may markedly advance our understanding of underlying cellular mechanisms and related neurological disorders, eventually helping discover novel targets for their pharmacological or gene therapy interventions.
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Affiliation(s)
- Anastasia M Moskalenko
- Graduate Program in Genetics and Genetic Technologies, Sirius University of Science and Technology, Sochi 354340, Russia; Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Aleksey N Ikrin
- Graduate Program in Genetics and Genetic Technologies, Sirius University of Science and Technology, Sochi 354340, Russia; Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Alena V Kozlova
- Graduate Program in Genetics and Genetic Technologies, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Radmir R Mukhamadeev
- Graduate Program in Bioinformatics and Genomics, Sirius University of Science and Technology, Sochi 354340, Russia; Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Murilo S de Abreu
- Graduate Program in Health Sciences, Federal University of Health Sciences of Porto Alegre, Porto Alegre 90050, Brazil.
| | - Vyacheslav Riga
- Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Tatiana O Kolesnikova
- Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia
| | - Allan V Kalueff
- Neuroscience Department, Sirius University of Science and Technology, Sochi 354340, Russia; Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg 199034, Russia; Institute of Experimental Medicine, Almazov National Medical Research Centre, Ministry of Healthcare of Russian Federation, St. Petersburg 194021, Russia; Suzhou Key Laboratory of Neurobiology and Cell Signaling, Department of Biological Sciences, School of Science, Xi'an Jiaotong-Liverpool University (XJTLU), Suzhou 215123, China.
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Zhong X, Moresco JJ, SoRelle JA, Song R, Jiang Y, Nguyen MT, Wang J, Bu CH, Moresco EMY, Beutler B, Choi JH. Disruption of the ZFP574-THAP12 complex suppresses B cell malignancies in mice. Proc Natl Acad Sci U S A 2024; 121:e2409232121. [PMID: 39047044 PMCID: PMC11295075 DOI: 10.1073/pnas.2409232121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 06/24/2024] [Indexed: 07/27/2024] Open
Abstract
Despite the availability of life-extending treatments for B cell leukemias and lymphomas, many of these cancers remain incurable. Thus, the development of new molecular targets and therapeutics is needed to expand treatment options. To identify new molecular targets, we used a forward genetic screen in mice to identify genes required for development or survival of lymphocytes. Here, we describe Zfp574, an essential gene encoding a zinc finger protein necessary for normal and malignant lymphocyte survival. We show that ZFP574 interacts with zinc finger protein THAP12 and promotes the G1-to-S-phase transition during cell cycle progression. Mutation of ZFP574 impairs nuclear localization of the ZFP574-THAP12 complex. ZFP574 or THAP12 deficiency results in cell cycle arrest and impaired lymphoproliferation. Germline mutation, acute gene deletion, or targeted degradation of ZFP574 suppressed Myc-driven B cell leukemia in mice, but normal B cells were largely spared, permitting long-term survival, whereas complete lethality was observed in control animals. Our findings support the identification of drugs targeting ZFP574-THAP12 as a unique strategy to treat B cell malignancies.
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Affiliation(s)
- Xue Zhong
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - James J. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jeffrey A. SoRelle
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Ran Song
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Yiao Jiang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Mylinh T. Nguyen
- Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jianhui Wang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Chun Hui Bu
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Eva Marie Y. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Bruce Beutler
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jin Huk Choi
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX75390
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11
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Kong JN, Dipon Ghosh D, Savvidis A, Sando SR, Droste R, Robert Horvitz H. Transcriptional landscape of a hypoxia response identifies cell-specific pathways for adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.02.601765. [PMID: 39005398 PMCID: PMC11245032 DOI: 10.1101/2024.07.02.601765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
How the HIF-1 (Hypoxia-Inducible) transcription factor drives and coordinates distinct responses to low oxygen across diverse cell types is poorly understood. We present a multi-tissue single-cell gene-expression atlas of the hypoxia response of the nematode Caenorhabditis elegans . This atlas highlights how cell-type-specific HIF-1 responses overlap and diverge among and within neuronal, intestinal, and muscle tissues. Using the atlas to guide functional analyses of candidate muscle-specific HIF-1 effectors, we discovered that HIF-1 activation drives downregulation of the tspo-1 ( TSPO, Translocator Protein) gene in vulval muscle cells to modulate a hypoxia-driven change in locomotion caused by contraction of body-wall muscle cells. We further showed that in human cardiomyocytes HIF-1 activation decreases levels of TSPO and thereby alters intracellular cholesterol transport and the mitochondrial network. We suggest that TSPO-1 is an evolutionarily conserved mediator of HIF-1-dependent modulation of muscle and conclude that our gene-expression atlas can help reveal how HIF-1 drives cell-specific adaptations to hypoxia.
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12
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Tan CH, Wang TY, Park H, Lomenick B, Chou TF, Sternberg PW. Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles. Proc Natl Acad Sci U S A 2024; 121:e2322588121. [PMID: 38861598 PMCID: PMC11194598 DOI: 10.1073/pnas.2322588121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 05/06/2024] [Indexed: 06/13/2024] Open
Abstract
The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.
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Affiliation(s)
- Chieh-Hsiang Tan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
| | - Ting-Yu Wang
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Heenam Park
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
| | - Brett Lomenick
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Tsui-Fen Chou
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, Pasadena, CA 91125
| | - Paul W Sternberg
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125
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13
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Brown AL, Meiborg AB, Franz-Wachtel M, Macek B, Gordon S, Rog O, Weadick CJ, Werner MS. Characterization of the Pristionchus pacificus "epigenetic toolkit" reveals the evolutionary loss of the histone methyltransferase complex PRC2. Genetics 2024; 227:iyae041. [PMID: 38513719 PMCID: PMC11075575 DOI: 10.1093/genetics/iyae041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 12/04/2023] [Accepted: 03/05/2024] [Indexed: 03/23/2024] Open
Abstract
Comparative approaches have revealed both divergent and convergent paths to achieving shared developmental outcomes. Thus, only through assembling multiple case studies can we understand biological principles. Yet, despite appreciating the conservation-or lack thereof-of developmental networks, the conservation of epigenetic mechanisms regulating these networks is poorly understood. The nematode Pristionchus pacificus has emerged as a model system of plasticity and epigenetic regulation as it exhibits a bacterivorous or omnivorous morph depending on its environment. Here, we determined the "epigenetic toolkit" available to P. pacificus as a resource for future functional work on plasticity, and as a comparison with Caenorhabditis elegans to investigate the conservation of epigenetic mechanisms. Broadly, we observed a similar cast of genes with putative epigenetic function between C. elegans and P. pacificus. However, we also found striking differences. Most notably, the histone methyltransferase complex PRC2 appears to be missing in P. pacificus. We described the deletion/pseudogenization of the PRC2 genes mes-2 and mes-6 and concluded that both were lost in the last common ancestor of P. pacificus and a related species P. arcanus. Interestingly, we observed the enzymatic product of PRC2 (H3K27me3) by mass spectrometry and immunofluorescence, suggesting that a currently unknown methyltransferase has been co-opted for heterochromatin silencing. Altogether, we have provided an inventory of epigenetic genes in P. pacificus to compare with C. elegans. This inventory will enable reverse-genetic experiments related to plasticity and has revealed the first loss of PRC2 in a multicellular organism.
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Affiliation(s)
- Audrey L Brown
- School of Biological Sciences, The University of Utah, Salt Lake City, UT 84112, USA
| | - Adriaan B Meiborg
- Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
- Faculty of Biosciences, Collaboration for joint PhD degree between EMBL and Heidelberg University, 69120 Heidelberg, Germany
| | | | - Boris Macek
- Proteome Center Tübingen, University of Tübingen, 72074 Tübingen, Germany
| | - Spencer Gordon
- School of Biological Sciences, The University of Utah, Salt Lake City, UT 84112, USA
| | - Ofer Rog
- School of Biological Sciences, The University of Utah, Salt Lake City, UT 84112, USA
| | | | - Michael S Werner
- School of Biological Sciences, The University of Utah, Salt Lake City, UT 84112, USA
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14
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Aleksander SA, Anagnostopoulos AV, Antonazzo G, Arnaboldi V, Attrill H, Becerra A, Bello SM, Blodgett O, Bradford YM, Bult CJ, Cain S, Calvi BR, Carbon S, Chan J, Chen WJ, Cherry JM, Cho J, Crosby MA, De Pons JL, D’Eustachio P, Diamantakis S, Dolan ME, dos Santos G, Dyer S, Ebert D, Engel SR, Fashena D, Fisher M, Foley S, Gibson AC, Gollapally VR, Gramates LS, Grove CA, Hale P, Harris T, Hayman GT, Hu Y, James-Zorn C, Karimi K, Karra K, Kishore R, Kwitek AE, Laulederkind SJF, Lee R, Longden I, Luypaert M, Markarian N, Marygold SJ, Matthews B, McAndrews MS, Millburn G, Miyasato S, Motenko H, Moxon S, Muller HM, Mungall CJ, Muruganujan A, Mushayahama T, Nash RS, Nuin P, Paddock H, Pells T, Perrimon N, Pich C, Quinton-Tulloch M, Raciti D, Ramachandran S, Richardson JE, Gelbart SR, Ruzicka L, Schindelman G, Shaw DR, Sherlock G, Shrivatsav A, Singer A, Smith CM, Smith CL, Smith JR, Stein L, Sternberg PW, Tabone CJ, Thomas PD, Thorat K, Thota J, Tomczuk M, Trovisco V, Tutaj MA, Urbano JM, Van Auken K, Van Slyke CE, Vize PD, Wang Q, Weng S, Westerfield M, Wilming LG, Wong ED, Wright A, Yook K, Zhou P, Zorn A, Zytkovicz M. Updates to the Alliance of Genome Resources central infrastructure. Genetics 2024; 227:iyae049. [PMID: 38552170 PMCID: PMC11075569 DOI: 10.1093/genetics/iyae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/09/2024] Open
Abstract
The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).
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Affiliation(s)
| | | | | | - Giulia Antonazzo
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Valerio Arnaboldi
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Helen Attrill
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Andrés Becerra
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Susan M Bello
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Olin Blodgett
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | | | - Carol J Bult
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Scott Cain
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Brian R Calvi
- Department of Biology, Indiana University , Bloomington, IN 47408 , USA
| | - Seth Carbon
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Juancarlos Chan
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Wen J Chen
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - J Michael Cherry
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Jaehyoung Cho
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Madeline A Crosby
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Jeffrey L De Pons
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | | | - Stavros Diamantakis
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Mary E Dolan
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gilberto dos Santos
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Sarah Dyer
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Dustin Ebert
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Stacia R Engel
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - David Fashena
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Malcolm Fisher
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Saoirse Foley
- Department of Biological Sciences, Carnegie Mellon University , 5000 Forbes Ave, Pittsburgh, PA 15203
| | - Adam C Gibson
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Varun R Gollapally
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - L Sian Gramates
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Christian A Grove
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Paul Hale
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Todd Harris
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - G Thomas Hayman
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Yanhui Hu
- Department of Genetics, Howard Hughes Medical Institute , Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115 , USA
| | - Christina James-Zorn
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Kamran Karimi
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Kalpana Karra
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Ranjana Kishore
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Anne E Kwitek
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Stanley J F Laulederkind
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Raymond Lee
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Ian Longden
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Manuel Luypaert
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Nicholas Markarian
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Steven J Marygold
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Beverley Matthews
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Monica S McAndrews
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gillian Millburn
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Stuart Miyasato
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Howie Motenko
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Sierra Moxon
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Hans-Michael Muller
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Christopher J Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory , Berkeley, CA
| | - Anushya Muruganujan
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Tremayne Mushayahama
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Robert S Nash
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Paulo Nuin
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Holly Paddock
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Troy Pells
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Norbert Perrimon
- Department of Genetics, Howard Hughes Medical Institute , Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115 , USA
| | - Christian Pich
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Mark Quinton-Tulloch
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD , UK
| | - Daniela Raciti
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | | | | | - Susan Russo Gelbart
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Leyla Ruzicka
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Gary Schindelman
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - David R Shaw
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Gavin Sherlock
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Ajay Shrivatsav
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Amy Singer
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Constance M Smith
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Cynthia L Smith
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Jennifer R Smith
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Lincoln Stein
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Paul W Sternberg
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Christopher J Tabone
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California , Los Angeles, CA 90033 , USA
| | - Ketaki Thorat
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Jyothi Thota
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Monika Tomczuk
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Vitor Trovisco
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Marek A Tutaj
- Medical College of Wisconsin—Rat Genome Database, Departments of Physiology and Biomedical Engineering , Medical College of Wisconsin, Milwaukee, WI 53226 , USA
| | - Jose-Maria Urbano
- Department of Physiology, Development and Neuroscience , University of Cambridge, Downing Street, Cambridge CB2 3DY , UK
| | - Kimberly Van Auken
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Ceri E Van Slyke
- Institute of Neuroscience, University of Oregon , Eugene, OR 97403
| | - Peter D Vize
- Department of Biological Sciences, University of Calgary , 507 Campus Dr NW, Calgary, AB T2N 4V8 , Canada
| | - Qinghua Wang
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Shuai Weng
- Department of Genetics, Stanford University , Stanford, CA 94305
| | | | - Laurens G Wilming
- The Jackson Laboratory for Mammalian Genomics, Bar Harbor , ME 04609 , USA
| | - Edith D Wong
- Department of Genetics, Stanford University , Stanford, CA 94305
| | - Adam Wright
- Informatics and Bio-computing Platform, Ontario Institute for Cancer Research , Toronto, ON M5G0A3 , Canada
| | - Karen Yook
- Division of Biology and Biological Engineering 140-18, California Institute of Technology , Pasadena, CA 91125 , USA
| | - Pinglei Zhou
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
| | - Aaron Zorn
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center , 3333 Burnet Ave, Cincinnati, OH 45229 , USA
| | - Mark Zytkovicz
- The Biological Laboratories, Harvard University , 16 Divinity Avenue, Cambridge, MA 02138 , USA
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15
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Pottmeier P, Nikolantonaki D, Lanner F, Peuckert C, Jazin E. Sex-biased gene expression during neural differentiation of human embryonic stem cells. Front Cell Dev Biol 2024; 12:1341373. [PMID: 38764741 PMCID: PMC11101176 DOI: 10.3389/fcell.2024.1341373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 04/16/2024] [Indexed: 05/21/2024] Open
Abstract
Sex differences in the developing human brain are primarily attributed to hormonal influence. Recently however, genetic differences and their impact on the developing nervous system have attracted increased attention. To understand genetically driven sexual dimorphisms in neurodevelopment, we investigated genome-wide gene expression in an in vitro differentiation model of male and female human embryonic stem cell lines (hESC), independent of the effects of human sex hormones. Four male and four female-derived hESC lines were differentiated into a population of mixed neurons over 37 days. Differential gene expression and gene set enrichment analyses were conducted on bulk RNA sequencing data. While similar differentiation tendencies in all cell lines demonstrated the robustness and reproducibility of our differentiation protocol, we found sex-biased gene expression already in undifferentiated ESCs at day 0, but most profoundly after 37 days of differentiation. Male and female cell lines exhibited sex-biased expression of genes involved in neurodevelopment, suggesting that sex influences the differentiation trajectory. Interestingly, the highest contribution to sex differences was found to arise from the male transcriptome, involving both Y chromosome and autosomal genes. We propose 13 sex-biased candidate genes (10 upregulated in male cell lines and 3 in female lines) that are likely to affect neuronal development. Additionally, we confirmed gene dosage compensation of X/Y homologs escaping X chromosome inactivation through their Y homologs and identified a significant overexpression of the Y-linked demethylase UTY and KDM5D in male hESC during neuron development, confirming previous results in neural stem cells. Our results suggest that genetic sex differences affect neuronal differentiation trajectories, which could ultimately contribute to sex biases during human brain development.
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Affiliation(s)
- Philipp Pottmeier
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Danai Nikolantonaki
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Fredrik Lanner
- Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden
| | - Christiane Peuckert
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
- The Department of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, Stockholm, Sweden
| | - Elena Jazin
- Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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16
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Ross KE, Bastian FB, Buys M, Cook CE, D’Eustachio P, Harrison M, Hermjakob H, Li D, Lord P, Natale DA, Peters B, Sternberg PW, Su AI, Thakur M, Thomas PD, Bateman A. Perspectives on tracking data reuse across biodata resources. BIOINFORMATICS ADVANCES 2024; 4:vbae057. [PMID: 38721398 PMCID: PMC11076920 DOI: 10.1093/bioadv/vbae057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 03/13/2024] [Accepted: 04/11/2024] [Indexed: 06/14/2024]
Abstract
Motivation Data reuse is a common and vital practice in molecular biology and enables the knowledge gathered over recent decades to drive discovery and innovation in the life sciences. Much of this knowledge has been collated into molecular biology databases, such as UniProtKB, and these resources derive enormous value from sharing data among themselves. However, quantifying and documenting this kind of data reuse remains a challenge. Results The article reports on a one-day virtual workshop hosted by the UniProt Consortium in March 2023, attended by representatives from biodata resources, experts in data management, and NIH program managers. Workshop discussions focused on strategies for tracking data reuse, best practices for reusing data, and the challenges associated with data reuse and tracking. Surveys and discussions showed that data reuse is widespread, but critical information for reproducibility is sometimes lacking. Challenges include costs of tracking data reuse, tensions between tracking data and open sharing, restrictive licenses, and difficulties in tracking commercial data use. Recommendations that emerged from the discussion include: development of standardized formats for documenting data reuse, education about the obstacles posed by restrictive licenses, and continued recognition by funding agencies that data management is a critical activity that requires dedicated resources. Availability and implementation Summaries of survey results are available at: https://docs.google.com/forms/d/1j-VU2ifEKb9C-sW6l3ATB79dgHdRk5v_lESv2hawnso/viewanalytics (survey of data providers) and https://docs.google.com/forms/d/18WbJFutUd7qiZoEzbOytFYXSfWFT61hVce0vjvIwIjk/viewanalytics (survey of users).
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Affiliation(s)
- Karen E Ross
- Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, United States
| | - Frederic B Bastian
- Evolutionary Bioinformatics Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
| | | | | | - Peter D’Eustachio
- Department of Biochemistry & Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10012, United States
| | - Melissa Harrison
- Literature Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Henning Hermjakob
- Molecular Systems, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
| | - Donghui Li
- Chan Zuckerberg Initiative, Redwood City, CA 94063, United States
| | - Phillip Lord
- School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, United Kingdom
| | - Darren A Natale
- Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, United States
| | - Bjoern Peters
- Center for Vaccine Innovation, La Jolla Institute of Immunology, La Jolla, CA 92037, United States
| | - Paul W Sternberg
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
| | - Andrew I Su
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, United States
| | - Matthew Thakur
- Data Services, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SA, United Kingdom
| | - Paul D Thomas
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA 90089, United States
| | - Alex Bateman
- MSCB, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
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17
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Zhuang X, Ye R, Zhou Y, Cheng MY, Cui H, Wang L, Zhang S, Wang S, Cui Y, Zhang W. Leveraging new methods for comprehensive characterization of mitochondrial DNA in esophageal squamous cell carcinoma. Genome Med 2024; 16:50. [PMID: 38566210 PMCID: PMC10985887 DOI: 10.1186/s13073-024-01319-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 03/21/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Mitochondria play essential roles in tumorigenesis; however, little is known about the contribution of mitochondrial DNA (mtDNA) to esophageal squamous cell carcinoma (ESCC). Whole-genome sequencing (WGS) is by far the most efficient technology to fully characterize the molecular features of mtDNA; however, due to the high redundancy and heterogeneity of mtDNA in regular WGS data, methods for mtDNA analysis are far from satisfactory. METHODS Here, we developed a likelihood-based method dMTLV to identify low-heteroplasmic mtDNA variants. In addition, we described fNUMT, which can simultaneously detect non-reference nuclear sequences of mitochondrial origin (non-ref NUMTs) and their derived artifacts. Using these new methods, we explored the contribution of mtDNA to ESCC utilizing the multi-omics data of 663 paired tumor-normal samples. RESULTS dMTLV outperformed the existing methods in sensitivity without sacrificing specificity. The verification using Nanopore long-read sequencing data showed that fNUMT has superior specificity and more accurate breakpoint identification than the current methods. Leveraging the new method, we identified a significant association between the ESCC overall survival and the ratio of mtDNA copy number of paired tumor-normal samples, which could be potentially explained by the differential expression of genes enriched in pathways related to metabolism, DNA damage repair, and cell cycle checkpoint. Additionally, we observed that the expression of CBWD1 was downregulated by the non-ref NUMTs inserted into its intron region, which might provide precursor conditions for the tumor cells to adapt to a hypoxic environment. Moreover, we identified a strong positive relationship between the number of mtDNA truncating mutations and the contribution of signatures linked to tumorigenesis and treatment response. CONCLUSIONS Our new frameworks promote the characterization of mtDNA features, which enables the elucidation of the landscapes and roles of mtDNA in ESCC essential for extending the current understanding of ESCC etiology. dMTLV and fNUMT are freely available from https://github.com/sunnyzxh/dMTLV and https://github.com/sunnyzxh/fNUMT , respectively.
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Affiliation(s)
- Xuehan Zhuang
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Rui Ye
- Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Yong Zhou
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Matthew Yibo Cheng
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Heyang Cui
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Longlong Wang
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Shuangping Zhang
- The Department of Thoracic Surgery, Shanxi Cancer Hospital; Key Laboratory of Cellular Physiology of the Ministry of Education, Department of Pathology, Shanxi Medical University, Taiyuan, Shanxi, 030001, China
| | - Shubin Wang
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China
| | - Yongping Cui
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China.
- The Department of Thoracic Surgery, Shanxi Cancer Hospital; Key Laboratory of Cellular Physiology of the Ministry of Education, Department of Pathology, Shanxi Medical University, Taiyuan, Shanxi, 030001, China.
| | - Weimin Zhang
- Cancer Institute, Department of Oncology, Peking University Shenzhen Hospital, Shenzhen Peking University-the Hong Kong University of Science and Technology (PKU-HKUST) Medical Center; Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, Guangdong, 518000, China.
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory of Carcinogenesis and Translational Research, Laboratory of Molecular Oncology, Peking University Cancer Hospital & Institute; Research Unit of Molecular Cancer Research, Chinese Academy of Medical Sciences, Beijing, 100142, China.
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18
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Conforti JM, Ziegler AM, Worth CS, Nambiar AM, Bailey JT, Taube JH, Gallagher ES. Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Clean-up Techniques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.13.584881. [PMID: 38559195 PMCID: PMC10980087 DOI: 10.1101/2024.03.13.584881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identification. Single-pot, solid-phase-enhanced sample preparation (SP3) is a clean-up technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. However, recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Thus, solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer clean-up technique that employs protein-aggregation to capture proteins without modified particles. SP4 has previously enriched low-solubility proteins, though differences in protein capture could affect which proteins are detected and identified. We hypothesize that the mechanisms of capture for SP3 and SP4 are distinct. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. From these results, we recommend clean-up techniques based on protein-sample hydrophobicity to yield high proteome coverage in biological samples.
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Affiliation(s)
- Jessica M. Conforti
- Department of Chemistry and Biochemistry, Baylor University, One Bear Place #97348, Waco, Texas 76798, United States
| | - Amanda M. Ziegler
- Department of Chemistry and Biochemistry, Baylor University, One Bear Place #97348, Waco, Texas 76798, United States
| | - Charli S. Worth
- Department of Biology, Baylor University, One Bear Place #97388, Waco, Texas 76798, United States
| | - Adhwaitha M. Nambiar
- Department of Biology, Baylor University, One Bear Place #97388, Waco, Texas 76798, United States
| | - Jacob T. Bailey
- Department of Biology, Baylor University, One Bear Place #97388, Waco, Texas 76798, United States
| | - Joseph H. Taube
- Department of Chemistry and Biochemistry, Baylor University, One Bear Place #97348, Waco, Texas 76798, United States
- Department of Biology, Baylor University, One Bear Place #97388, Waco, Texas 76798, United States
| | - Elyssia S. Gallagher
- Department of Chemistry and Biochemistry, Baylor University, One Bear Place #97348, Waco, Texas 76798, United States
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19
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Zhao W, Chen Y, Hu N, Long D, Cao Y. The uses of zebrafish (Danio rerio) as an in vivo model for toxicological studies: A review based on bibliometrics. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 272:116023. [PMID: 38290311 DOI: 10.1016/j.ecoenv.2024.116023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/20/2024] [Accepted: 01/24/2024] [Indexed: 02/01/2024]
Abstract
An in vivo model is necessary for toxicology. This review analyzed the uses of zebrafish (Danio rerio) in toxicology based on bibliometrics. Totally 56,816 publications about zebrafish from 2002 to 2023 were found in Web of Science Core Collection, with Toxicology as the top 6 among all disciplines. Accordingly, the bibliometric map reveals that "toxicity" has become a hot keyword. It further reveals that the most common exposure types include acute, chronic, and combined exposure. The toxicological effects include behavioral, intestinal, cardiovascular, hepatic, endocrine toxicity, neurotoxicity, immunotoxicity, genotoxicity, and reproductive and transgenerational toxicity. The mechanisms include oxidative stress, inflammation, autophagy, and dysbiosis of gut microbiota. The toxicants commonly evaluated by using zebrafish model include nanomaterials, arsenic, metals, bisphenol, and dioxin. Overall, zebrafish provide a unique and well-accepted model to investigate the toxicological effects and mechanisms. We also discussed the possible ways to address some of the limitations of zebrafish model, such as the combination of human organoids to avoid species differences.
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Affiliation(s)
- Weichao Zhao
- Hunan Province Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, PR China
| | - Yuna Chen
- Hunan Province Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, PR China
| | - Nan Hu
- Key Discipline Laboratory for National Defense for Biotechnology in Uranium Mining and Hydrometallurgy, University of South China, Hengyang 421001, PR China.
| | - Dingxin Long
- Hunan Province Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, PR China.
| | - Yi Cao
- Hunan Province Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, Hengyang Medical School, University of South China, Hengyang 421001, PR China.
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20
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Gogianu LI, Ruta LL, Farcasanu IC. Kcs1 and Vip1: The Key Enzymes behind Inositol Pyrophosphate Signaling in Saccharomyces cerevisiae. Biomolecules 2024; 14:152. [PMID: 38397389 PMCID: PMC10886477 DOI: 10.3390/biom14020152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/19/2024] [Accepted: 01/25/2024] [Indexed: 02/25/2024] Open
Abstract
The inositol pyrophosphate pathway, a complex cell signaling network, plays a pivotal role in orchestrating vital cellular processes in the budding yeast, where it regulates cell cycle progression, growth, endocytosis, exocytosis, apoptosis, telomere elongation, ribosome biogenesis, and stress responses. This pathway has gained significant attention in pharmacology and medicine due to its role in generating inositol pyrophosphates, which serve as crucial signaling molecules not only in yeast, but also in higher eukaryotes. As targets for therapeutic development, genetic modifications within this pathway hold promise for disease treatment strategies, offering practical applications in biotechnology. The model organism Saccharomyces cerevisiae, renowned for its genetic tractability, has been instrumental in various studies related to the inositol pyrophosphate pathway. This review is focused on the Kcs1 and Vip1, the two enzymes involved in the biosynthesis of inositol pyrophosphate in S. cerevisiae, highlighting their roles in various cell processes, and providing an up-to-date overview of their relationship with phosphate homeostasis. Moreover, the review underscores the potential applications of these findings in the realms of medicine and biotechnology, highlighting the profound implications of comprehending this intricate signaling network.
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Affiliation(s)
- Larisa Ioana Gogianu
- Doctoral School of Biology, Faculty of Biology, University of Bucharest, Splaiul Independenței 91-95, 050095 Bucharest, Romania;
- National Institute for Research and Development in Microtechnologies, Erou Iancu Nicolae Str. 126A, 077190 Voluntari, Romania
| | - Lavinia Liliana Ruta
- Faculty of Chemistry, University of Bucharest, Panduri Road 90-92, 050663 Bucharest, Romania;
| | - Ileana Cornelia Farcasanu
- Doctoral School of Biology, Faculty of Biology, University of Bucharest, Splaiul Independenței 91-95, 050095 Bucharest, Romania;
- Faculty of Chemistry, University of Bucharest, Panduri Road 90-92, 050663 Bucharest, Romania;
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21
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Aleksander SA, Anagnostopoulos AV, Antonazzo G, Arnaboldi V, Attrill H, Becerra A, Bello SM, Blodgett O, Bradford YM, Bult CJ, Cain S, Calvi BR, Carbon S, Chan J, Chen WJ, Michael Cherry J, Cho J, Crosby MA, De Pons JL, D’Eustachio P, Diamantakis S, Dolan ME, Santos GD, Dyer S, Ebert D, Engel SR, Fashena D, Fisher M, Foley S, Gibson AC, Gollapally VR, Sian Gramates L, Grove CA, Hale P, Harris T, Thomas Hayman G, Hu Y, James-Zorn C, Karimi K, Karra K, Kishore R, Kwitek AE, Laulederkind SJF, Lee R, Longden I, Luypaert M, Markarian N, Marygold SJ, Matthews B, McAndrews MS, Millburn G, Miyasato S, Motenko H, Moxon S, Muller HM, Mungall CJ, Muruganujan A, Mushayahama T, Nash RS, Nuin P, Paddock H, Pells T, Perrimon N, Pich C, Quinton-Tulloch M, Raciti D, Ramachandran S, Richardson JE, Gelbart SR, Ruzicka L, Schindelman G, Shaw DR, Sherlock G, Shrivatsav A, Singer A, Smith CM, Smith CL, Smith JR, Stein L, Sternberg PW, Tabone CJ, Thomas PD, Thorat K, Thota J, Tomczuk M, Trovisco V, Tutaj MA, Urbano JM, Auken KV, Van Slyke CE, Vize PD, Wang Q, Weng S, Westerfield M, Wilming LG, Wong ED, Wright A, Yook K, Zhou P, Zorn A, Zytkovicz M. Updates to the Alliance of Genome Resources Central Infrastructure Alliance of Genome Resources Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.20.567935. [PMID: 38045425 PMCID: PMC10690154 DOI: 10.1101/2023.11.20.567935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively-studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, C. elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and APIs. Here we focus on developments over the last two years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse. We describe our progress towards a central persistent database to support curation, the data modeling that underpins harmonization, and progress towards a state-of-the art literature curation system with integrated Artificial Intelligence and Machine Learning (AI/ML).
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Soni P, Edwards H, Anupom T, Rahman M, Lesanpezeshki L, Blawzdziewicz J, Cope H, Gharahdaghi N, Scott D, Toh LS, Williams PM, Etheridge T, Szewczyk N, Willis CRG, Vanapalli SA. Spaceflight Induces Strength Decline in Caenorhabditis elegans. Cells 2023; 12:2470. [PMID: 37887314 PMCID: PMC10605753 DOI: 10.3390/cells12202470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/14/2023] [Accepted: 10/15/2023] [Indexed: 10/28/2023] Open
Abstract
Background: Understanding and countering the well-established negative health consequences of spaceflight remains a primary challenge preventing safe deep space exploration. Targeted/personalized therapeutics are at the forefront of space medicine strategies, and cross-species molecular signatures now define the 'typical' spaceflight response. However, a lack of direct genotype-phenotype associations currently limits the robustness and, therefore, the therapeutic utility of putative mechanisms underpinning pathological changes in flight. Methods: We employed the worm Caenorhabditis elegans as a validated model of space biology, combined with 'NemaFlex-S' microfluidic devices for assessing animal strength production as one of the most reproducible physiological responses to spaceflight. Wild-type and dys-1 (BZ33) strains (a Duchenne muscular dystrophy (DMD) model for comparing predisposed muscle weak animals) were cultured on the International Space Station in chemically defined media before loading second-generation gravid adults into NemaFlex-S devices to assess individual animal strength. These same cultures were then frozen on orbit before returning to Earth for next-generation sequencing transcriptomic analysis. Results: Neuromuscular strength was lower in flight versus ground controls (16.6% decline, p < 0.05), with dys-1 significantly more (23% less strength, p < 0.01) affected than wild types. The transcriptional gene ontology signatures characterizing both strains of weaker animals in flight strongly corroborate previous results across species, enriched for upregulated stress response pathways and downregulated mitochondrial and cytoskeletal processes. Functional gene cluster analysis extended this to implicate decreased neuronal function, including abnormal calcium handling and acetylcholine signaling, in space-induced strength declines under the predicted control of UNC-89 and DAF-19 transcription factors. Finally, gene modules specifically altered in dys-1 animals in flight again cluster to neuronal/neuromuscular pathways, suggesting strength loss in DMD comprises a strong neuronal component that predisposes these animals to exacerbated strength loss in space. Conclusions: Highly reproducible gene signatures are strongly associated with space-induced neuromuscular strength loss across species and neuronal changes in calcium/acetylcholine signaling require further study. These results promote targeted medical efforts towards and provide an in vivo model for safely sending animals and people into deep space in the near future.
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Affiliation(s)
- Purushottam Soni
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA; (P.S.); (M.R.); (L.L.)
| | - Hunter Edwards
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA;
| | - Taslim Anupom
- Department of Electrical Engineering, Texas Tech University, Lubbock, TX 79409, USA;
| | - Mizanur Rahman
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA; (P.S.); (M.R.); (L.L.)
| | - Leila Lesanpezeshki
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA; (P.S.); (M.R.); (L.L.)
| | - Jerzy Blawzdziewicz
- Department of Mechanical Engineering, Texas Tech University, Lubbock, TX 79409, USA;
- Department of Physics and Astronomy, Texas Tech University, Lubbock, TX 79409, USA
| | - Henry Cope
- School of Medicine, University of Nottingham, Derby DE22 3DT, UK; (H.C.); (N.G.)
| | - Nima Gharahdaghi
- School of Medicine, University of Nottingham, Derby DE22 3DT, UK; (H.C.); (N.G.)
| | - Daniel Scott
- School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, UK;
| | - Li Shean Toh
- School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK; (L.S.T.); (P.M.W.)
| | - Philip M. Williams
- School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK; (L.S.T.); (P.M.W.)
| | - Timothy Etheridge
- Department of Sport and Health Sciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX1 2LU, UK;
| | - Nathaniel Szewczyk
- School of Medicine, University of Nottingham, Derby DE22 3DT, UK; (H.C.); (N.G.)
- Ohio Musculoskeletal and Neurological Institute, Heritage College of Osteopathic Medicine, Ohio University, Athens, OH 45701, USA
| | - Craig R. G. Willis
- School of Chemistry and Biosciences, Faculty of Life Sciences, University of Bradford, Bradford BD7 1DP, UK;
| | - Siva A. Vanapalli
- Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, USA; (P.S.); (M.R.); (L.L.)
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