scholarly journals The 14-3-3 Proteins Bmh1 and Bmh2 Are Key Regulators of Meiotic Commitment

2021 ◽  
Author(s):  
Janardan Gavade ◽  
Chris M Puccia ◽  
S. Grace Herod ◽  
Jon Trinidad ◽  
Luke E. Berchowitz ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Rna Binding ◽  
Budding Yeast ◽  
Nutrient Sensing ◽  
Yeast Cells ◽  
A Genome ◽  
Multiple Processes ◽  
Internal Gene ◽  
Genome Scale ◽  
I Cells

Induction of meiosis requires exogenous signals that activate internal gene regulatory networks. Meiotic commitment ensures the irreversible continuation of meiosis, even upon withdrawal of the meiosis inducing signals. Budding yeast cells have a unique property in that cells enter meiosis when starved, but if given nutrient-rich medium prior to the commitment point, they exit meiosis and enter mitosis. After the meiotic commitment point in prometaphase I, cells remain in meiosis even with addition of nutrients. Despite the importance of meiotic commitment in ensuring the production of gametes, only a few genes involved in the commitment process are known. We performed a genome-scale screen in budding yeast and discovered new regulators of meiotic commitment including Bcy1, which is involved in nutrient sensing, the meiosis-specific kinase Ime2, Polo kinase Cdc5, and the 14-3-3 proteins Bmh1 and Bmh2. Importantly, we found that Bmh1 and Bmh2 are involved in multiple processes throughout meiosis including the maintenance of the middle meiosis transcription factor Ndt80, activation of Cdc5, and interaction with an RNA-binding protein Pes4, which is important for regulating the timing of translation of several mRNAs in meiosis II. This study identifies a meiotic commitment regulatory network with the 14-3-3 proteins functioning as central regulators.

scholarly journals Computational Analysis of Reciprocal Association of Metabolism and Epigenetics in the Budding Yeast: A Genome-Scale Metabolic Model (GSMM) Approach

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e111686 ◽  
Author(s):  
Ali Salehzadeh-Yazdi ◽  
Yazdan Asgari ◽  
Ali Akbar Saboury ◽  
Ali Masoudi-Nejad
Keyword(s):  
Computational Analysis ◽  
Budding Yeast ◽  
Metabolic Model ◽  
A Genome ◽  
Genome Scale

scholarly journals EXO1 Plays a Role in Generating Type I and Type II Survivors in Budding Yeast

Genetics ◽  
2004 ◽  
Vol 166 (4) ◽  
pp. 1641-1649
Author(s):  
Laura Maringele ◽  
David Lydall
Keyword(s):  
Homologous Recombination ◽  
Budding Yeast ◽  
Human Cells ◽  
Telomere Maintenance ◽  
Recombination Process ◽  
Yeast Cells ◽  
Type I ◽  
Type Ii ◽  
Recombination Proteins

Abstract Telomerase-defective budding yeast cells escape senescence by using homologous recombination to amplify telomeric or subtelomeric structures. Similarly, human cells that enter senescence can use homologous recombination for telomere maintenance, when telomerase cannot be activated. Although recombination proteins required to generate telomerase-independent survivors have been intensively studied, little is known about the nucleases that generate the substrates for recombination. Here we demonstrate that the Exo1 exonuclease is an initiator of the recombination process that allows cells to escape senescence and become immortal in the absence of telomerase. We show that EXO1 is important for generating type I survivors in yku70Δ mre11Δ cells and type II survivors in tlc1Δ cells. Moreover, in tlc1Δ cells, EXO1 seems to contribute to the senescence process itself.

scholarly journals Cell-type-specific profiling of loaded miRNAs from Caenorhabditis elegans reveals spatial and temporal flexibility in Argonaute loading

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher A. Brosnan ◽  
Alexander J. Palmer ◽  
Steven Zuryn
Keyword(s):  
Caenorhabditis Elegans ◽  
Regulatory Networks ◽  
Regulatory Mechanisms ◽  
Cell Type ◽  
A Genome ◽  
Temporal Flexibility ◽  
Small Regulatory Rnas ◽  
Cell Type Specific ◽  
Single Cell Type ◽  
Regulated Gene Expression

AbstractMulticellularity has coincided with the evolution of microRNAs (miRNAs), small regulatory RNAs that are integrated into cellular differentiation and homeostatic gene-regulatory networks. However, the regulatory mechanisms underpinning miRNA activity have remained largely obscured because of the precise, and thus difficult to access, cellular contexts under which they operate. To resolve these, we have generated a genome-wide map of active miRNAs in Caenorhabditis elegans by revealing cell-type-specific patterns of miRNAs loaded into Argonaute (AGO) silencing complexes. Epitope-labelled AGO proteins were selectively expressed and immunoprecipitated from three distinct tissue types and associated miRNAs sequenced. In addition to providing information on biological function, we define adaptable miRNA:AGO interactions with single-cell-type and AGO-specific resolution. We demonstrate spatial and temporal dynamicism, flexibility of miRNA loading, and suggest miRNA regulatory mechanisms via AGO selectivity in different tissues and during ageing. Additionally, we resolve widespread changes in AGO-regulated gene expression by analysing translatomes specifically in neurons.

scholarly journals Arabidopsis Genes Essential for Seedling Viability: Isolation of Insertional Mutants and Molecular Cloning

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1765-1778
Author(s):  
Gregory J Budziszewski ◽  
Sharon Potter Lewis ◽  
Lyn Wegrich Glover ◽  
Jennifer Reineke ◽  
Gary Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Protein Translocation ◽  
Gene Families ◽  
Mutant Phenotype ◽  
Lethal Mutant ◽  
A Genome ◽  
Genes Encoding ◽  
High Level ◽  
Mutant Lines ◽  
Genome Scale

Abstract We have undertaken a large-scale genetic screen to identify genes with a seedling-lethal mutant phenotype. From screening ~38,000 insertional mutant lines, we identified >500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for >200 mutants, molecularly characterized 54 mutants, and provided a detailed description for 22 of them. Most of the seedling-lethal mutants seem to affect chloroplast function because they display altered pigmentation and affect genes encoding proteins predicted to have chloroplast localization. Although a high level of functional redundancy in Arabidopsis might be expected because 65% of genes are members of gene families, we found that 41% of the essential genes found in this study are members of Arabidopsis gene families. In addition, we isolated several interesting classes of mutants and genes. We found three mutants in the recently discovered nonmevalonate isoprenoid biosynthetic pathway and mutants disrupting genes similar to Tic40 and tatC, which are likely to be involved in chloroplast protein translocation. Finally, we directly compared T-DNA and Ac/Ds transposon mutagenesis methods in Arabidopsis on a genome scale. In each population, we found only about one-third of the insertion mutations cosegregated with a mutant phenotype.

scholarly journals RNA-Centric Approaches to Profile the RNA–Protein Interaction Landscape on Selected RNAs

2021 ◽  
Vol 7 (1) ◽  
pp. 11 ◽  
Author(s):  
André P. Gerber
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Protein Complexes ◽  
Cell Protein ◽  
Transcriptional Regulatory Networks ◽  
Technological Advances

RNA–protein interactions frame post-transcriptional regulatory networks and modulate transcription and epigenetics. While the technological advances in RNA sequencing have significantly expanded the repertoire of RNAs, recently developed biochemical approaches combined with sensitive mass-spectrometry have revealed hundreds of previously unrecognized and potentially novel RNA-binding proteins. Nevertheless, a major challenge remains to understand how the thousands of RNA molecules and their interacting proteins assemble and control the fate of each individual RNA in a cell. Here, I review recent methodological advances to approach this problem through systematic identification of proteins that interact with particular RNAs in living cells. Thereby, a specific focus is given to in vivo approaches that involve crosslinking of RNA–protein interactions through ultraviolet irradiation or treatment of cells with chemicals, followed by capture of the RNA under study with antisense-oligonucleotides and identification of bound proteins with mass-spectrometry. Several recent studies defining interactomes of long non-coding RNAs, viral RNAs, as well as mRNAs are highlighted, and short reference is given to recent in-cell protein labeling techniques. These recent experimental improvements could open the door for broader applications and to study the remodeling of RNA–protein complexes upon different environmental cues and in disease.

scholarly journals Predicting changes in renal metabolism after compound exposure with a genome-scale metabolic model

2021 ◽  
Vol 412 ◽  
pp. 115390
Author(s):  
Kristopher D. Rawls ◽  
Bonnie V. Dougherty ◽  
Kalyan C. Vinnakota ◽  
Venkat R. Pannala ◽  
Anders Wallqvist ◽  
...  
Keyword(s):  
Metabolic Model ◽  
Renal Metabolism ◽  
A Genome ◽  
Compound Exposure ◽  
Genome Scale

scholarly journals Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1

2008 ◽  
Vol 190 (8) ◽  
pp. 2790-2803 ◽  
Author(s):  
Matthew A. Oberhardt ◽  
Jacek Puchałka ◽  
Kimberly E. Fryer ◽  
Vítor A. P. Martins dos Santos ◽  
Jason A. Papin
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
Opportunistic Pathogen ◽  
Scale Model ◽  
Modeling Framework ◽  
Major Life ◽  
Metabolic Versatility ◽  
A Genome ◽  
Scale Properties ◽  
Genome Scale

ABSTRACT Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.

scholarly journals Single cell RNA-seq reveals genes vital to in vitro fertilized embryos and parthenotes in pigs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhi-Qiang Du ◽  
Hao Liang ◽  
Xiao-Man Liu ◽  
Yun-Hua Liu ◽  
Chonglong Wang ◽  
...  
Keyword(s):  
Embryo Development ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Expression Patterns ◽  
Early Embryo ◽  
Specific Factor ◽  
Early Embryos ◽  
Genome Activation

AbstractSuccessful early embryo development requires the correct reprogramming and configuration of gene networks by the timely and faithful execution of zygotic genome activation (ZGA). However, the regulatory principle of molecular elements and circuits fundamental to embryo development remains largely obscure. Here, we profiled the transcriptomes of single zygotes and blastomeres, obtained from in vitro fertilized (IVF) or parthenogenetically activated (PA) porcine early embryos (1- to 8-cell), focusing on the gene expression dynamics and regulatory networks associated with maternal-to-zygote transition (MZT) (mainly maternal RNA clearance and ZGA). We found that minor and major ZGAs occur at 1-cell and 4-cell stages for both IVF and PA embryos, respectively. Maternal RNAs gradually decay from 1- to 8-cell embryos. Top abundantly expressed genes (CDV3, PCNA, CDR1, YWHAE, DNMT1, IGF2BP3, ARMC1, BTG4, UHRF2 and gametocyte-specific factor 1-like) in both IVF and PA early embryos identified are of vital roles for embryo development. Differentially expressed genes within IVF groups are different from that within PA groups, indicating bi-parental and maternal-only embryos have specific sets of mRNAs distinctly decayed and activated. Pathways enriched from DEGs showed that RNA associated pathways (RNA binding, processing, transport and degradation) could be important. Moreover, mitochondrial RNAs are found to be actively transcribed, showing dynamic expression patterns, and for DNA/H3K4 methylation and transcription factors as well. Taken together, our findings provide an important resource to investigate further the epigenetic and genome regulation of MZT events in early embryos of pigs.

scholarly journals Evaluation of a Genome-ScaleIn SilicoMetabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

2012 ◽  
Vol 78 (24) ◽  
pp. 8735-8742 ◽  
Author(s):  
Yilin Fang ◽  
Michael J. Wilkins ◽  
Steven B. Yabusaki ◽  
Mary S. Lipton ◽  
Philip E. Long
Keyword(s):  
Proteomic Analysis ◽  
In Silico ◽  
Field Experiments ◽  
Metabolic Model ◽  
Geobacter Metallireducens ◽  
Content Type ◽  
Proteomic Data ◽  
Subsurface Environment ◽  
A Genome ◽  
Genome Scale

ABSTRACTAccurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within anin silicomodel using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model ofGeobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-basedin silicomodelof G. metallireducensrelates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637G. metallireducensproteins detected during the 2008 experiment were associated with specific metabolic reactions in thein silicomodel. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through thein silicomodel reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in thein silicomodel that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

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