16 results on '"Chris M. Rands"'
Search Results
2. Deciphering the origins and fates of steroidogenic lineages in the mouse testis
- Author
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Herta Ademi, Cyril Djari, Chloé Mayère, Yasmine Neirijnck, Pauline Sararols, Chris M. Rands, Isabelle Stévant, Béatrice Conne, and Serge Nef
- Subjects
CP: Developmental biology ,Biology (General) ,QH301-705.5 - Abstract
Summary: Leydig cells (LCs) are the major androgen-producing cells in the testis. They arise from steroidogenic progenitors (SPs), whose origins, maintenance, and differentiation dynamics remain largely unknown. Single-cell transcriptomics reveal that the mouse steroidogenic lineage is specified as early as embryonic day 12.5 (E12.5) and has a dual mesonephric and coelomic origin. SPs specifically express the Wnt5a gene and evolve rapidly. At E12.5 and E13.5, they give rise first to an intermediate population of pre-LCs, and finally to fetal LCs. At E16.5, SPs possess the characteristics of the dormant progenitors at the origin of adult LCs and are also transcriptionally closely related to peritubular myoid cells (PMCs). In agreement with our in silico analysis, in vivo lineage tracing indicates that Wnt5a-expressing cells are bona fide progenitors of PMCs as well as fetal and adult LCs, contributing to most of the LCs present in the fetal and adult testis.
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- 2022
- Full Text
- View/download PDF
3. Phigaro: high-throughput prophage sequence annotation.
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Elizaveta V. Starikova, Polina O. Tikhonova, Nikita A. Prianichnikov, Chris M. Rands, Evgeny M. Zdobnov, Elena N. Ilina, and Vadim M. Govorun
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- 2020
- Full Text
- View/download PDF
4. TRIM28-dependent SUMOylation protects the adult ovary from activation of the testicular pathway
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Robin Lovell-Badge, Francis Poulat, Moïra Rossitto, Le Gallic L, Dagmar Wilhelm, Alain Pruvost, Brigitte Boizet-Bonhoure, Legras S, Mahmoud-Reza Rafiee, Florence Cammas, Migale R, Serge Nef, Yasmine Neirijnck, Anvi Laetitia Nguyen, Guillaume Bossis, Chris M Rands, Stéphanie Déjardin, Institut de génétique humaine (IGH), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Nutrition et Neurobiologie intégrée (NutriNeuro), Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Ecole nationale supérieure de chimie, biologie et physique-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Genève = University of Geneva (UNIGE), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), The Francis Crick Institute [London], Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique Moléculaire de Montpellier (IGMM), Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), University of Melbourne, cammas, florence, and ANR-16-CE14-0020,SexMaintain,Rôle de TRIM28 dans le maintien de l'identité ovarienne et dans la détermination du sexe(2016)
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Male ,Model organisms ,endocrine system ,Somatic cell ,[SDV]Life Sciences [q-bio] ,SUMO protein ,General Physics and Astronomy ,Tripartite Motif-Containing Protein 28 ,Biology ,General Biochemistry, Genetics and Molecular Biology ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Testis ,medicine ,Animals ,Ligase activity ,Transcription factor ,030304 developmental biology ,Mammals ,0303 health sciences ,Sertoli Cells ,Multidisciplinary ,urogenital system ,FOS: Clinical medicine ,Stem Cells ,Ovary ,Transdifferentiation ,Neurosciences ,Sumoylation ,General Chemistry ,Tumour Biology ,Sertoli cell ,Embryonic stem cell ,Chromatin ,Cell biology ,[SDV] Life Sciences [q-bio] ,medicine.anatomical_structure ,Female ,Genetics & Genomics ,030217 neurology & neurosurgery ,Transcription Factors ,Developmental Biology - Abstract
Summary Gonadal sexual fate in mammals is determined during embryonic development and must be actively maintained in adulthood. Therefore, gonadal sex-specific transcription factors are required to prevent transdifferentiation of gonadal somatic cells to the other sexual fate. Mouse genetic experiments have shown that oestrogen receptor signalling and the transcription factor FOXL2 protect ovarian granulosa cells from transdifferentiation into Sertoli cells, their testicular counterpart. However, the mechanism underlying this protective mechanism is unknown. Here, we show that one post-translational modification (i.e. SUMOylation catalysed by TRIM28) is sufficient to prevent female-to-male sex reversal of the mouse ovary after birth. We found that upon loss of TRIM28 SUMO-E3 ligase activity, ovarian granulosa cells transdifferentiate to Sertoli cells through an intermediate cell type different from gonadal embryonic progenitors. TRIM28 binds to chromatin close to the critical transcription factor FOXL2 to maintain the female pathway through SUMOylation of specific chromatin regions. Therefore, FOXL2 signalling might maintain the adult ovary cell fate via TRIM28-dependent SUMOylation. Improper SUMOylation of chromatin regions in granulosa cells might lead to female reproductive disorders and infertility, the incidence of which is currently increasing.
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- 2022
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5. 8.2% of the Human genome is constrained: variation in rates of turnover across functional element classes in the human lineage.
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Chris M Rands, Stephen Meader, Chris P Ponting, and Gerton Lunter
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Genetics ,QH426-470 - Abstract
Ten years on from the finishing of the human reference genome sequence, it remains unclear what fraction of the human genome confers function, where this sequence resides, and how much is shared with other mammalian species. When addressing these questions, functional sequence has often been equated with pan-mammalian conserved sequence. However, functional elements that are short-lived, including those contributing to species-specific biology, will not leave a footprint of long-lasting negative selection. Here, we address these issues by identifying and characterising sequence that has been constrained with respect to insertions and deletions for pairs of eutherian genomes over a range of divergences. Within noncoding sequence, we find increasing amounts of mutually constrained sequence as species pairs become more closely related, indicating that noncoding constrained sequence turns over rapidly. We estimate that half of present-day noncoding constrained sequence has been gained or lost in approximately the last 130 million years (half-life in units of divergence time, d1/2 = 0.25-0.31). While enriched with ENCODE biochemical annotations, much of the short-lived constrained sequences we identify are not detected by models optimized for wider pan-mammalian conservation. Constrained DNase 1 hypersensitivity sites, promoters and untranslated regions have been more evolutionarily stable than long noncoding RNA loci which have turned over especially rapidly. By contrast, protein coding sequence has been highly stable, with an estimated half-life of over a billion years (d1/2 = 2.1-5.0). From extrapolations we estimate that 8.2% (7.1-9.2%) of the human genome is presently subject to negative selection and thus is likely to be functional, while only 2.2% has maintained constraint in both human and mouse since these species diverged. These results reveal that the evolutionary history of the human genome has been highly dynamic, particularly for its noncoding yet biologically functional fraction.
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- 2014
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6. Single‐cell transcriptomics reveal temporal dynamics of critical regulators of germ cell fate during mouse sex determination
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Anne-Amandine Chassot, Chloé Mayère, Isabelle Stévant, Emmanouil T. Dermitzakis, Pauline Sararols, Yasmine Neirijnck, Françoise Kühne, Chris M Rands, Marie-Christine Chaboissier, Serge Nef, University of Geneva [Switzerland], Institut de Biologie Valrose (IBV), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Université Côte d'Azur (UCA), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Genève (UNIGE), Université de Genève = University of Geneva (UNIGE), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Chaboissier, Marie-Christine, and CHASSOT, Anne Amandine
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Male ,0301 basic medicine ,endocrine system ,Time Factors ,X Chromosome ,Somatic cell ,[SDV]Life Sciences [q-bio] ,Gene regulatory network ,Mice, Transgenic ,Biology ,Biochemistry ,Mice ,03 medical and health sciences ,0302 clinical medicine ,ddc:590 ,Downregulation and upregulation ,Y Chromosome ,Gene expression ,Genetics ,medicine ,Animals ,ddc:576.5 ,Molecular Biology ,Gene ,ComputingMilieux_MISCELLANEOUS ,Gene Expression Profiling ,Intron ,Gene Expression Regulation, Developmental ,Sex Determination Processes ,Cell biology ,[SDV] Life Sciences [q-bio] ,Germ Cells ,030104 developmental biology ,medicine.anatomical_structure ,Lineage differentiation ,RNA splicing ,Female ,Single-Cell Analysis ,Germ cell ,030217 neurology & neurosurgery ,Biotechnology - Abstract
Despite the importance of germ cell (GC) differentiation for sexual reproduction, the gene networks underlying their fate remain unclear. Here, we comprehensively characterize the gene expression dynamics during sex determination based on single-cell RNA sequencing of 14 914 XX and XY mouse GCs between embryonic days (E) 9.0 and 16.5. We found that XX and XY GCs diverge transcriptionally as early as E11.5 with upregulation of genes downstream of the bone morphogenic protein (BMP) and nodal/Activin pathways in XY and XX GCs, respectively. We also identified a sex-specific upregulation of genes associated with negative regulation of mRNA processing and an increase in intron retention consistent with a reduction in mRNA splicing in XY testicular GCs by E13.5. Using computational gene regulation network inference analysis, we identified sex-specific, sequential waves of putative key regulator genes during GC differentiation and revealed that the meiotic genes are regulated by positive and negative master modules acting in an antagonistic fashion. Finally, we found that rare adrenal GCs enter meiosis similarly to ovarian GCs but display altered expression of master genes controlling the female and male genetic programs, indicating that the somatic environment is important for GC function. Our data are available on a web platform and provide a molecular roadmap of GC sex determination at single-cell resolution, which will serve as a valuable resource for future studies of gonad development, function, and disease.
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- 2021
- Full Text
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7. The Role of Bacteriophages in Bacterial Evolution
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Chris M. Rands and Harald Brüssow
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- 2021
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8. Deciphering the origins and fates of steroidogenic lineages in the mouse testis
- Author
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Herta, Ademi, Cyril, Djari, Chloé, Mayère, Yasmine, Neirijnck, Pauline, Sararols, Chris M, Rands, Isabelle, Stévant, Béatrice, Conne, and Serge, Nef
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Male ,Mice ,Fetus ,Testis ,Androgens ,Animals ,Leydig Cells ,Cell Differentiation - Abstract
Leydig cells (LCs) are the major androgen-producing cells in the testis. They arise from steroidogenic progenitors (SPs), whose origins, maintenance, and differentiation dynamics remain largely unknown. Single-cell transcriptomics reveal that the mouse steroidogenic lineage is specified as early as embryonic day 12.5 (E12.5) and has a dual mesonephric and coelomic origin. SPs specifically express the Wnt5a gene and evolve rapidly. At E12.5 and E13.5, they give rise first to an intermediate population of pre-LCs, and finally to fetal LCs. At E16.5, SPs possess the characteristics of the dormant progenitors at the origin of adult LCs and are also transcriptionally closely related to peritubular myoid cells (PMCs). In agreement with our in silico analysis, in vivo lineage tracing indicates that Wnt5a-expressing cells are bona fide progenitors of PMCs as well as fetal and adult LCs, contributing to most of the LCs present in the fetal and adult testis.
- Published
- 2020
9. Expression ofWnt5adefines the major progenitors of fetal and adult Leydig cells
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Isabelle Stévant, Serge Nef, Béatrice Conne, Chris M Rands, and Herta Ademi
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WNT5A ,Fetus ,In vivo ,Fetal mouse ,Lineage tracing ,embryonic structures ,Biology ,Progenitor cell ,Cell biology - Abstract
SummaryLeydig cells (LCs) are the major androgen-producing cells in the testes. They arise from steroidogenic progenitors, whose origins, maintenance and differentiation dynamics remain largely unknown. Here, we identifiedWnt5aas a specific marker of steroidogenic progenitors, whose expression begins at around E11.5-E12.5 in interstitial cells of the fetal mouse testis.In vivolineage tracing indicates thatWnt5a-expressing progenitors are initially present in large numbers in the fetal testis and then progressively decrease as development progresses. We provide evidence thatWnt5a-expressing cells arebona fideprogenitors of peritubular myoid cells as well as fetal and adult LCs, contributing to most of the LCs present in the fetal and adult testis. Additionally, we show in the adult testis thatWnt5aexpression is restricted to a subset of LCs exhibiting a slow but noticeable clonal expansion, revealing hitherto unappreciated proliferation of fully differentiated LCs as a contribution to the adult LC pool.
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- 2020
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10. ACI‐1 beta‐lactamase is widespread across human gut microbiomes in Negativicutes due to transposons harboured by tailed prophages
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Evgeny M. Zdobnov, Harald Brüssow, Evgenia V. Kriventseva, Elizaveta V. Starikova, Chris M Rands, and Vadim M. Govorun
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0301 basic medicine ,China ,Gene Transfer, Horizontal ,Prophages ,Bacteria/classification/drug effects/genetics/metabolism ,030106 microbiology ,Drug Resistance ,Bacterial/genetics ,Gene Transfer ,Firmicutes ,Context (language use) ,Biology ,Microbiology ,beta-Lactamases ,Anti-Bacterial Agents/pharmacology ,Horizontal ,03 medical and health sciences ,Antibiotic resistance ,Drug Resistance, Bacterial ,Humans ,ddc:576.5 ,Phylogeny ,Ecology, Evolution, Behavior and Systematics ,Prophage ,Genetics ,Acidaminococcus intestini ,Negativicutes ,Bacteria ,Prophages/genetics ,Human microbiome ,biology.organism_classification ,United States ,Anti-Bacterial Agents ,Gastrointestinal Microbiome ,Beta-Lactamases/genetics/metabolism ,Europe ,030104 developmental biology ,Horizontal gene transfer ,Metagenome ,Firmicutes/genetics ,Mobile genetic elements - Abstract
Antibiotic resistance is increasing among pathogens, and the human microbiome contains a reservoir of antibiotic resistance genes. Acidaminococcus intestini is the first Negativicute bacterium (Gram-negative Firmicute) shown to be resistant to beta-lactam antibiotics. Resistance is conferred by the aci1 gene, but its evolutionary history and prevalence remain obscure. We discovered that ACI-1 proteins are phylogenetically distinct from beta-lactamases of Gram-positive Firmicutes and that aci1 occurs in bacteria scattered across the Negativicute clade, suggesting lateral gene transfer. In the reference A. intestini RyC-MR95 genome, we found transposons residing within a tailed prophage context are likely vehicles for aci1's mobility. We found aci1 in 56 (4.4%) of 1,267 human gut metagenomes, mostly hosted within A. intestini, and, where could be determined, mostly within a consistent mobile element constellation. These samples are from Europe, China and the USA, showing that aci1 is distributed globally. We found that for most Negativicute assemblies with aci1, the prophage observed in A. instestini is absent, but in all cases aci1 is flanked by varying transposons. The chimeric mobile elements we identify here likely have a complex evolutionary history and potentially provide multiple complementary mechanisms for antibiotic resistance gene transfer both within and between cells.
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- 2018
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11. Single cell transcriptomics reveal temporal dynamics of critical regulators of germ cell fate during mouse sex determination
- Author
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Chloé Mayère, Yasmine Neirijnck, Pauline Sararols, Chris M Rands, Isabelle Stévant, Françoise Kühne, Anne-Amandine Chassot, Marie-Christine Chaboissier, Emmanouil T. Dermitzakis, and Serge Nef
- Subjects
endocrine system ,medicine.anatomical_structure ,Meiosis ,Somatic cell ,Gene expression ,medicine ,Gene regulatory network ,Biology ,Embryonic stem cell ,Gene ,Germ cell ,Cell biology ,Sexual reproduction - Abstract
SummaryDespite the importance of germ cell (GC) differentiation for sexual reproduction, the gene networks underlying their fate remain unclear. Here, we comprehensively characterize the gene expression dynamics during sex determination based on single-cell RNA sequencing of 14,914 XX and XY mouse GCs between embryonic days (E) 9.0 and 16.5. We found that XX and XY GCs diverge transcriptionally as early as E11.5 with upregulation of genes downstream of the Bone morphogenic protein (BMP) and Nodal/Activin pathways in XY and XX GCs, respectively. We also identified a sex-specific upregulation of genes associated with negative regulation of mRNA processing and an increase in intron retention consistent with a reduction in mRNA splicing in XY testicular GCs by E13.5. Using computational gene regulation network inference analysis, we identified sex-specific, sequential waves of putative key regulator genes during GC differentiation and revealed that the meiotic genes are regulated by positive and negative master modules acting in an antagonistic fashion. Finally, we found that rare adrenal GCs enter meiosis similarly to ovarian GCs but display altered expression of master genes controlling the female and male genetic programs, indicating that the somatic environment is important for GC function. Our data is available on a web platform and provides a molecular roadmap of GC sex determination at single-cell resolution, which will serve as a valuable resource for future studies of gonad development, function and disease.
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- 2019
- Full Text
- View/download PDF
12. Comparative genomics groups phages of Negativicutes and classical Firmicutes despite different Gram-staining properties
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Chris M Rands, Evgeny M. Zdobnov, and Harald Brüssow
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ddc:025.063/570 ,Firmicutes ,Prophages ,Genome, Viral ,Microbiology ,Genome ,03 medical and health sciences ,ddc:590 ,Caudovirales ,Gram-Negative Bacteria ,Proteobacteria ,Human virome ,Ecology, Evolution, Behavior and Systematics ,Prophage ,Phylogeny ,030304 developmental biology ,Genetics ,Comparative genomics ,0303 health sciences ,Negativicutes ,biology ,Staining and Labeling ,030306 microbiology ,Genomics ,biology.organism_classification - Abstract
Negativicutes are gram-negative bacteria characterized by two cell membranes, but they are phylogenetically a side-branch of gram-positive Firmicutes that contain only a single membrane. We asked whether viruses (phages) infecting Negativicutes were horizontally acquired from gram-negative Proteobacteria, given the shared outer cell structure of their bacterial hosts, or if Negativicute phages co-evolved vertically with their hosts and thus resemble gram-positive Firmicute prophages. We predicted and characterized 485 prophages (mostly Caudovirales) from gram-negative Firmicute genomes plus 2977 prophages from other bacterial clades, and we used virome sequence data from 183 human stool samples to support our predictions. The majority of identified Negativicute prophages were lambdoids closer related to prophages from other Firmicutes than Proteobacteria by sequence relationship and genome organization (position of the lysis module). Only a single Mu-like candidate prophage and no clear P2-like prophages were identified in Negativicutes, both common in Proteobacteria. Given this collective evidence, it is unlikely that Negativicute phages were acquired from Proteobacteria. Sequence-related prophages, which occasionally harboured antibiotic resistance genes, were identified in two distinct Negativicute orders (Veillonellales and Acidaminococcales), possibly suggesting horizontal cross-order phage infection between human gut commensals. Our results reveal ancient genomic signatures of phage and bacteria co-evolution despite horizontal phage mobilization.
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- 2019
13. Phigaro: high throughput prophage sequence annotation
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Evgeny M. Zdobnov, Nikita A. Prianichnikov, Elizaveta V. Starikova, Vadim M. Govorun, Chris M Rands, and P. O. Tikhonova
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Transposable element ,0303 health sciences ,Source code ,Computer science ,media_common.quotation_subject ,030302 biochemistry & molecular biology ,Computational biology ,Python (programming language) ,Genome ,03 medical and health sciences ,Sequence annotation ,Metagenomics ,computer ,Throughput (business) ,Prophage ,030304 developmental biology ,media_common ,computer.programming_language - Abstract
SummaryPhigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It provides putative taxonomic annotations that can distinguish tailed from non-tailed phages. It is applicable for mining prophage regions from large metagenomic datasets.AvailabilitySource code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.
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- 2019
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14. Novel non-terminal tumor sampling procedure using fine needle aspiration supports immuno-oncology biomarker discovery in preclinical mouse models
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Kathy Mulgrew, Sophie Munnings-Tomes, Simon J. Dovedi, Chris M Rands, Matthew J Robinson, Judit España Agustí, Tianhui Zhang, Hormas Ghadially, Suzanne I. Sitnikova, Kristina M. Ilieva, Tim Slidel, Guglielmo Rosignoli, Elena Galvani, Robert W. Wilkinson, and Stacy Kentner
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0301 basic medicine ,Oncology ,Cancer Research ,medicine.medical_specialty ,Treatment response ,medicine.medical_treatment ,Biopsy, Fine-Needle ,Immunology ,immunologic techniques ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Immunologic Technique ,drug evaluation ,Cell Line, Tumor ,Internal medicine ,Immunotherapy Biomarkers ,Biopsy ,preclinical ,Biomarkers, Tumor ,medicine ,tumor microenvironment ,Animals ,Humans ,Immunology and Allergy ,Biomarker discovery ,RC254-282 ,Pharmacology ,Tumor microenvironment ,medicine.diagnostic_test ,business.industry ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Cancer ,Immunotherapy ,medicine.disease ,Disease Models, Animal ,030104 developmental biology ,Fine-needle aspiration ,tumor biomarkers ,030220 oncology & carcinogenesis ,Molecular Medicine ,business - Abstract
BackgroundImmuno-oncology therapies are now part of the standard of care for cancer in many indications. However, durable objective responses remain limited to a subset of patients. As such, there is a critical need to identify biomarkers that can predict or enrich for treatment response. So far, the majority of putative biomarkers consist of features of the tumor microenvironment (TME). However, in preclinical mouse models, the collection of tumor tissue for this type of analysis is a terminal procedure, obviating the ability to directly link potential biomarkers to long-term treatment outcomes.MethodsTo address this, we developed and validated a novel non-terminal tumor sampling method to enable biopsy of the TME in mouse models based on fine needle aspiration.ResultsWe show that this technique enables repeated in-life sampling of subcutaneous flank tumors and yields sufficient material to support downstream analyses of tumor-infiltrating immune cells using methods such as flow cytometry and single-cell transcriptomics. Moreover, using this technique we demonstrate that we can link TME biomarkers to treatment response outcomes, which is not possible using the current method of terminal tumor sampling.ConclusionThus, this minimally invasive technique is an important refinement for the pharmacodynamic analysis of the TME facilitating paired evaluation of treatment response biomarkers with outcomes and reducing the number of animals used in preclinical research.
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- 2021
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15. ACI-1 class A beta-lactamase is widespread across human gut microbiomes due to transposons harboured by tailed prophages
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Vadim M. Govorun, Evgenia V. Kriventseva, Elizaveta V. Starikova, Harald Brüssow, Evgeny M. Zdobnov, and Chris M Rands
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Genetics ,Transposable element ,0303 health sciences ,Acidaminococcus intestini ,Negativicutes ,030306 microbiology ,Context (language use) ,Biology ,biology.organism_classification ,Genome ,03 medical and health sciences ,Mobile genetic elements ,Gene ,Prophage ,030304 developmental biology - Abstract
Antibiotic resistance is increasing among pathogens at unprecedented rates and the human body contains a large pool of antibiotic resistance genes that can be spread among bacteria by mobile genetic elements. Acidaminococcus intestini, a bacterium found in the human gut that belongs to the class of Negativicutes, is the first gram-negative coccus shown to be resistant to beta-lactam antibiotics. Resistance is conferred by aci1, a gene encoding the ACI-1 class A beta-lactamase, but the evolutionary history of aci1 and its distribution across other Negativicutes and in the human gut microbiota remains obscure. We discovered that ACI-1 proteins are phylogenetically distinct from class A beta-lactamases of gram-positive Firmicutes and that the aci1 gene occurs in bacteria scattered across the Negativicutes clade, suggesting possible mobilization. In the reference A. intestini RyC-MR95 strain, we found that aci1 is surrounded by mobile DNA, transposon derived sequences directly flank aci1 and are likely the vehicle for its mobility. These transposon sequences reside within a prophage context consisting of two likely degraded tailed prophages, the first prophages to be characterised in A. intestini. We found aci1 in at least 56 (4.4%) out of 1,267 human gut metagenome samples, mostly hosted within A. intestini, and, where could be determined, mostly within a similar constellation of mobile elements to that found in the reference A. intestini genome. These human samples are from individuals in Europe, China and the USA, showing that aci1 is widely distributed globally. Additionally, we examined the nine different Negativicute genome assemblies that contain aci1, and found that only two of these strains show a similar mobile element context around aci1 to the reference A. intestini with transposons adjacent to a tailed prophage. However, in all nine cases aci1 is flanked by transposon derived sequences, and these sequences are diverse, suggesting the activity and degradation of multiple transposons. Overall, we show that ACI-1 proteins form a distinct class A beta lactamase family, and that the aci1 gene is present in human guts worldwide within Negativicute bacterial hosts, due to transposons, sometimes inserted into tailed prophages.
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- 2017
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16. Two Antarctic penguin genomes reveal insights into their evolutionary history and molecular changes related to the Antarctic environment
- Author
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Weiming He, Huanming Yang, Matthew K. Fujita, Yan Zhang, Hao Yu, Erich D. Jarvis, Simon Y. W. Ho, Lesheng Kong, Yan Chen, David D. Pollock, Stephen Meader, David W. Burt, Qiye Li, Linfeng Yang, Matthew J. Greenwold, Wanjun Gu, Shiping Liu, Lijun Jin, Kiwoong Nam, Chris M Rands, Hans Ellegren, M. Thomas P. Gilbert, Jianwen Li, Yuan Deng, David M. Lambert, Craig D. Millar, Qiong Shi, Hailin Pan, Todd A. Castoe, Haofu Hu, Jinquan Xia, Chris P. Ponting, Yongshan Lang, Binghang Liu, Jian Wang, Luohao Xu, Guojie Zhang, Yong Zhang, Cai Li, Jun Wang, Sankar Subramanian, China National GeneBank, Section for GeoGenetics, Globe Institute, Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU)-Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford [Oxford], Environmental Futures Centre, Griffith University [Brisbane], Allan Wilson Center for Molecular Ecology and Evolution, University of Auckland [Auckland]-University of Otago [Dunedin, Nouvelle-Zélande]-Massey University-University of Canterbury [Christchurch], Current address: Department of Biology, University of Texas at Arlington [Arlington], Department of Biological Sciences, University of South Carolina [Columbia], Department of Biochemistry and Molecular Genetics, School of Medicine, Department of Physics [Boulder], University of Colorado [Boulder]-University of Colorado [Boulder], Biology Department, Research Centre of Learning Sciences, SouthEast University, Department of Evolutionary Biology [Uppsala], Uppsala University, Bioinformatics Research Centre, Aarhus University [Aarhus], School of Biological Sciences, University of Sydney, Department of Genomics and Genetics, The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Department of Neurobiology, Howard Hughes Medical Institute, Duke University, Trace and Environmental DNA Laboratory, Department of Environment and Agriculture, Curtin University [Perth], Planning and Transport Research Centre (PATREC)-Planning and Transport Research Centre (PATREC), Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Department of Biology [Copenhagen], Faculty of Science [Copenhagen], Macau University of Science and Technology (MUST), Department of Medicine, The University of Hong Kong (HKU), Centre for Social Evolution (CSE), Department of Plant and Environmental Sciences [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU)-Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU)-Department of Biology [Copenhagen], and European Research Council: 249869
- Subjects
0106 biological sciences ,Evolution ,Biodiversité et Ecologie ,Population ,Zoology ,Avian genomics ,Health Informatics ,Penguins ,010603 evolutionary biology ,01 natural sciences ,Biodiversity and Ecology ,Evolutionsbiologi ,03 medical and health sciences ,Effective population size ,antarctique ,genetique des populations ,14. Life underwater ,Adaptation ,education ,Southern Hemisphere ,030304 developmental biology ,0303 health sciences ,education.field_of_study ,Evolutionary Biology ,biology ,Phylogenetic tree ,génomique comparative ,Aptenodytes ,génome ,Research ,Adelie penguin ,manchot ,phylogénie des animaux ,Antarctica ,biology.organism_classification ,Computer Science Applications ,Pygoscelis ,diversité des populations ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology - Abstract
Background Penguins are flightless aquatic birds widely distributed in the Southern Hemisphere. The distinctive morphological and physiological features of penguins allow them to live an aquatic life, and some of them have successfully adapted to the hostile environments in Antarctica. To study the phylogenetic and population history of penguins and the molecular basis of their adaptations to Antarctica, we sequenced the genomes of the two Antarctic dwelling penguin species, the Adélie penguin [Pygoscelis adeliae] and emperor penguin [Aptenodytes forsteri]. Results Phylogenetic dating suggests that early penguins arose ~60 million years ago, coinciding with a period of global warming. Analysis of effective population sizes reveals that the two penguin species experienced population expansions from ~1 million years ago to ~100 thousand years ago, but responded differently to the climatic cooling of the last glacial period. Comparative genomic analyses with other available avian genomes identified molecular changes in genes related to epidermal structure, phototransduction, lipid metabolism, and forelimb morphology. Conclusions Our sequencing and initial analyses of the first two penguin genomes provide insights into the timing of penguin origin, fluctuations in effective population sizes of the two penguin species over the past 10 million years, and the potential associations between these biological patterns and global climate change. The molecular changes compared with other avian genomes reflect both shared and diverse adaptations of the two penguin species to the Antarctic environment. Electronic supplementary material The online version of this article (doi:10.1186/2047-217X-3-27) contains supplementary material, which is available to authorized users.
- Published
- 2014
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