scholarly journals Dormancy-to-death transition in yeast spores occurs due to gradual loss of gene-expressing ability

2019 ◽  
Author(s):  
Théo Maire ◽  
Tim Allertz ◽  
Max A. Betjes ◽  
Hyun Youk
Keyword(s):  
Gene Expression ◽  
List Type ◽  
Cell Level ◽  
Open Questions ◽  
Germination Ability ◽  
Gradual Loss ◽  
Inhibit Gene Expression ◽  
Synthetic Circuit ◽  
Dormant Spore ◽  
Gene Expressing

ABSTRACTDormancy is colloquially considered as extending lifespan by being still. Starved yeasts form dormant spores that wake-up (germinate) when nutrients reappear but cannot germinate (die) after some time. What sets their lifespans and how they age are open questions because what processes occur - and by how much - within each dormant spore remains unclear. With single-cell-level measurements, we discovered how dormant yeast spores age and die: spores have a quantifiable gene-expressing ability during dormancy that decreases over days to months until it vanishes, causing death. Specifically, each spore has a different probability of germinating that decreases because its ability to - without nutrients - express genes decreases, as revealed by a synthetic circuit that forces GFP expression during dormancy. Decreasing amounts of molecules required for gene expression - including RNA polymerases - decreases gene-expressing ability which then decreases chances of germinating. Spores gradually lose these molecules because they are produced too slowly compared to their degradations, causing gene-expressing ability to eventually vanish and, thus, death. Our work provides a systems-level view of dormancy-to-death transition.Short summaryThis study identifies systems-level quantities that decay during dormancy in Saccharomyces cerevisiae spores and thereby reveals the meaning of ageing for dormant yeast spores and shows that they die when their gene-expressing ability is irreversibly lost.HighlightsFor a given glucose concentration, a dormant yeast spore has a well-defined probability of germinating (“germination ability”).A spore’s germination ability positively correlates with its RNAP I-III levels and the gene-expression (GFP) level it can realize when the expression is forced without nutrients.Ageing during dormancy means gradual decreases in germination ability, RNAP levels, and GFP-level realizable when expression is forced.Spores die after sufficiently losing gene-expressing ability and drugs that inhibit gene expression during dormancy shorten spores’ lifespans (e.g., from months to a day).

scholarly journals SARS-CoV-2 in severe COVID-19 induces a TGF-β-dominated chronic immune response that does not target itself

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Marta Ferreira-Gomes ◽  
Andrey Kruglov ◽  
Pawel Durek ◽  
Frederik Heinrich ◽  
Caroline Tizian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Immune Reaction ◽  
Adaptive Immune Response ◽  
Gene Expression Signature ◽  
Spike Protein ◽  
Single Cell Level ◽  
Cell Level ◽  
Adaptive Immune

AbstractThe pathogenesis of severe COVID-19 reflects an inefficient immune reaction to SARS-CoV-2. Here we analyze, at the single cell level, plasmablasts egressed into the blood to study the dynamics of adaptive immune response in COVID-19 patients requiring intensive care. Before seroconversion in response to SARS-CoV-2 spike protein, peripheral plasmablasts display a type 1 interferon-induced gene expression signature; however, following seroconversion, plasmablasts lose this signature, express instead gene signatures induced by IL-21 and TGF-β, and produce mostly IgG1 and IgA1. In the sustained immune reaction from COVID-19 patients, plasmablasts shift to the expression of IgA2, thereby reflecting an instruction by TGF-β. Despite their continued presence in the blood, plasmablasts are not found in the lungs of deceased COVID-19 patients, nor does patient IgA2 binds to the dominant antigens of SARS-CoV-2. Our results thus suggest that, in severe COVID-19, SARS-CoV-2 triggers a chronic immune reaction that is instructed by TGF-β, and is distracted from itself.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

2003 ◽  
Vol 01 (03) ◽  
pp. 541-586 ◽  
Author(s):  
Tero Aittokallio ◽  
Markus Kurki ◽  
Olli Nevalainen ◽  
Tuomas Nikula ◽  
Anne West ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Microarray Data ◽  
Microarray Data Analysis ◽  
Biological Research ◽  
Microarray Experiments ◽  
Dna Microarray Data ◽  
Open Questions ◽  
Analysis Technique ◽  
Wide Range

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

Abstract 5953: Flow Pulsation Affect Distal Pulmonary Artery Endothelial Cell mRNA Expression

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Min Li ◽  
Kurt Stenmark ◽  
Robin Shandas ◽  
Wei Tan
Keyword(s):  
Gene Expression ◽  
Pulmonary Artery ◽  
Pulsatile Flow ◽  
Static Condition ◽  
Flow Chamber ◽  
Physical Characteristics ◽  
List Type ◽  
Flow Pulsation ◽  
Individual Gene ◽  
Speed Flow

Background: Due to the development of pulmonary arterial hypertension (PAH), distal pulmonary artery endothelial cells (dPAEC) are exposed to wall shear stress (SS) that is different in physical characteristics compared to normal condition. The effect of individual components of SS on PAEC biology has not been thoroughly examined. Thus the current study was designed to examine how dPAEC respond to different component of SS in regarding to gene expression including adhesion molecules: ICAM, VCAM, E-selectin; chemokine: MCP-1 and growth factors:VEGF, Flt-1. Methods: Bovine dPAEC were cultured and placed on fibronectin-coated slides till confluent. Cells were then exposed to SS with different frequency (1Hz, 2Hz), pulsation (low, medium and high with an average SS of 14 dynes/cm 2 ) and time (1hr or 6hrs). The flow studies were carried out using a flow chamber connected to a variable speed flow pump. All data was represented as fold change relative to static condition. Results: As shown in table below, The effect of flow frequency on gene expression depends on individual gene. There was no difference of ICAM expression between 1Hz and 2Hz. Frequency of 2Hz significantly increased VCAM and MCP-1 expression compared to frequency of 1Hz. Compared to static condition, steady flow increased all gene expression. One hour pulsatile flow further increased ICAM, VCAM, E-selectin and MCP-1 but not VEGF or Flt-1 expression as pulsation increased. 3) Prolonged pulsatile flow further increased all gene expression. Conclusion: Physical characteristics of flow, especially flow pulsation stimulate dPAEC gene expression which can contribute to the development of PAH.

scholarly journals Characterization, modelling and mitigation of gene expression burden in mammalian cells

2019 ◽  
Author(s):  
T Frei ◽  
F Cella ◽  
F Tedeschi ◽  
J Gutierrez ◽  
GB Stan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mammalian Cells ◽  
Genome Engineering ◽  
Host Cells ◽  
Genetic Circuits ◽  
Circuit Performance ◽  
Resource Requirements ◽  
Synthetic Circuit ◽  
Resource Aware

AbstractDespite recent advances in genome engineering, the design of genetic circuits in mammalian cells is still painstakingly slow and fraught with inexplicable failures. Here we demonstrate that competition for limited transcriptional and translational resources dynamically couples otherwise independent co-expressed exogenous genes, leading to diminished performance and contributing to the divergence between intended and actual function. We also show that the expression of endogenous genes is likewise impacted when genetic payloads are expressed in the host cells. Guided by a resource-aware mathematical model and our experimental finding that post-transcriptional regulators have a large capacity for resource redistribution, we identify and engineer natural and synthetic miRNA-based incoherent feedforward loop (iFFL) circuits that mitigate gene expression burden. The implementation of these circuits features the novel use of endogenous miRNAs as integral components of the engineered iFFL device, a versatile hybrid design that allows burden mitigation to be achieved across different cell-lines with minimal resource requirements. This study establishes the foundations for context-aware prediction and improvement of in vivo synthetic circuit performance, paving the way towards more rational synthetic construct design in mammalian cells.

scholarly journals 77 Prevalence of secondary immunotherapeutic targets in the absence of established immune biomarkers in solid tumors

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A86-A86
Author(s):  
Paul DePietro ◽  
Mary Nesline ◽  
Yong Hee Lee ◽  
RJ Seager ◽  
Erik Van Roey ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Reference Population ◽  
List Type ◽  
Tumor Type ◽  
Genomic Profiling ◽  
Rna Seq ◽  
Immune Biomarkers ◽  
Cancer Types ◽  
Immune Related Genes

BackgroundImmune checkpoint inhibitor-based therapies have achieved impressive success in the treatment of several cancer types. Predictive immune biomarkers, including PD-L1, MSI and TMB are well established as surrogate markers for immune evasion and tumor-specific neoantigens across many tumors. Positive detection across cancer types varies, but overall ~50% of patients test negative for these primary immune markers.1 In this study, we investigated the prevalence of secondary immune biomarkers outside of PD-L1, TMB and MSI.MethodsComprehensive genomic and immune profiling, including PD-L1 IHC, TMB, MSI and gene expression of 395 immune related genes was performed on 6078 FFPE tumors representing 34 cancer types, predominantly composed of lung cancer (36.7%), colorectal cancer (11.9%) and breast cancer (8.5%). Expression levels by RNA-seq of 36 genes targeted by immunotherapies in solid tumor clinical trials, identified as secondary immune biomarkers, were ranked against a reference population. Genes with a rank value ≥75th percentile were considered high and values were associated with PD-L1 (positive ≥1%), MSI (MSI-H or MSS) and TMB (high ≥10 Mut/Mb) status. Additionally, secondary immune biomarker status was segmented by tumor type and cancer immune cycle roles.ResultsIn total, 41.0% of cases were PD-L1+, 6.4% TMB+, and 0.1% MSI-H. 12.6% of cases were positive for >2 of these markers while 39.9% were triple negative (PD-L1-/TMB-/MSS). Of the PD-L1-/TMB-/MSS cases, 89.1% were high for at least one secondary immune biomarker, with 69.3% having ≥3 markers. PD-L1-/TMB-/MSS tumor types with ≥50% prevalence of high secondary immune biomarkers included brain, prostate, kidney, sarcoma, gallbladder, breast, colorectal, and liver cancer. High expression of cancer testis antigen secondary immune biomarkers (e.g., NY-ESO-1, LAGE-1A, MAGE-A4) was most commonly observed in bladder, ovarian, sarcoma, liver, and prostate cancer (≥15%). Tumors demonstrating T-cell priming (e.g., CD40, OX40, CD137), trafficking (e.g., TGFB1, TLR9, TNF) and/or recognition (e.g., CTLA4, LAG3, TIGIT) secondary immune biomarkers were most represented by kidney, gallbladder, and sarcoma (≥40%), with melanoma, esophageal, head & neck, cervical, stomach, and lung cancer least represented (≥15%).ConclusionsOur studies show comprehensive tumor profiling that includes gene expression can detect secondary immune biomarkers targeted by investigational therapies in ~90% of PD-L1-/TMB-/MSS cases. While genomic profiling could also provide therapeutic choices for a percentage of these patients, detection of secondary immune biomarkers by RNA-seq provides additional options for patients without a clear therapeutic path as determined by PD-L1 testing and genomic profiling alone.ReferenceHuang R S P, Haberberger J, Severson E, et al. A pan-cancer analysis of PD-L1 immunohistochemistry and gene amplification, tumor mutation burden and microsatellite instability in 48,782 cases. Mod Pathol 2021;34: 252–263.

scholarly journals How the Avidity of Polymerase Binding to the -35/-10 Promoter Sites Affects Gene Expression

2019 ◽  
Author(s):  
Tal Einav ◽  
Rob Phillips
Keyword(s):  
Gene Expression ◽  
Rna Polymerase ◽  
Regulatory Elements ◽  
Physical Principle ◽  
Regulatory Sequences ◽  
Energy Matrix ◽  
Cellular Behavior ◽  
Inhibit Gene Expression ◽  
Small Set ◽  
Polymerase Binding

AbstractAlthough the key promoter elements necessary to drive transcription inEscherichia colihave long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad of sequenced regulatory architectures as well as to design novel synthetic circuits. This work builds on a beautiful recent experiment by Urtechoet al.who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using this data, we demonstrate that a central claim in energy matrix models of gene expression – that each promoter element contributes independently and additively to gene expression – contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the -35 and -10 RNA polymerase binding sites and develop what we call arefined energy matrixmodel that incorporates this effect. We show that this the refined energy matrix model can characterize the full suite of gene expression data and explore several applications of this framework, namely, how multivalent binding at the -35 and -10 sites can buffer RNAP kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter.Significance StatementCellular behavior is ultimately governed by the genetic program encoded in its DNA and through the arsenal of molecular machines that actively transcribe its genes, yet we lack the ability to predict how an arbitrary DNA sequence will perform. To that end, we analyze the performance of over 10,000 regulatory sequences and develop a model that can predict the behavior of any sequence based on its composition. By considering promoters that only vary by one or two elements, we can characterize how different components interact, providing fundamental insights into the mechanisms of transcription.

scholarly journals A comprehensive analysis of vomeronasal organ transcriptome reveals variable gene expression depending on age and function in rabbits

2020 ◽  
Author(s):  
PR Villamayor ◽  
D Robledo ◽  
C Fernández ◽  
J Gullón ◽  
L Quintela ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transient Receptor Potential ◽  
Expression Patterns ◽  
Vomeronasal Organ ◽  
Receptor Potential ◽  
Transient Receptor Potential Channel ◽  
List Type ◽  
Gene Repertoire ◽  
Behavioural Responses ◽  
Transient Receptor

ABSTRACTThe vomeronasal organ (VNO) is a chemosensory organ specialized in the detection of pheromones and consequently the regulation of behavioural responses mostly related to reproduction. VNO shows a broad variation on its organization, functionality and gene expression in vertebrates, and although the species analyzed to date have shown very specific features, its expression patterns have only been well-characterized in mice. Despite rabbits represent a model of chemocommunication, unfortunately no genomic studies have been performed on VNO of this species to date. The capacity of VNO to detect a great variety of different stimuli suggests a large number of genes with complex organization to support this function. Here we provide the first comprehensive gene expression analysis of the rabbit VNO through RNA-seq across different sexual maturation stages. We characterized the VNO transcriptome, updating the number of the two main vomeronasal receptor (VR) families, 129 V1R and 70 V2R. Among others, the expression of transient receptor potential channel 2 (TRPC2), a crucial cation channel generating electrical responses to sensory stimulation in vomeronasal neurons, along with the specific expression of some fomyl-peptide receptors and H2-Mv genes, both known to have specific roles in the VNO, revealed a the particular gene expression repertoire of this organ, but also its singularity in rabbits. Moreover, juvenile and adult VNO transcriptome showed consistent differences, which may indicate that these receptors are tuned to fulfill specific functions depending on maturation age. We also identified VNO-specific genes, including most VR and TRPC2, thus confirming their functional association with the VNO. Overall, these results represent the genomic baseline for future investigations which seek to understand the genetic basis of behavioural responses canalized through the VNO.HIGHLIGHTSFirst description of the rabbit vomeronasal organ (VNO) transcriptomeVNO contains a unique gene repertoire depending on the speciesHigh fluctuation of the VNO gene expression reveals changes dependent on age and specific functionsMost vomeronasal-receptors (VR) and transient receptor potential channel 2 (TRPC2) genes are VNO-specificReproduction-related genes shows a wide expression pattern

The Circadian Clock inArabidopsisRoots Is a Simplified Slave Version of the Clock in Shoots

Science ◽  
2008 ◽  
Vol 322 (5909) ◽  
pp. 1832-1835 ◽  
Author(s):  
Allan B. James ◽  
José A. Monreal ◽  
Gillian A. Nimmo ◽  
Ciarán L. Kelly ◽  
Pawel Herzyk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Circadian Clock ◽  
Clock Genes ◽  
Plant Cells ◽  
Feedback Loops ◽  
Circadian Oscillator ◽  
Inhibit Gene Expression ◽  
Organ Specific ◽  
Plant Clock

The circadian oscillator in eukaryotes consists of several interlocking feedback loops through which the expression of clock genes is controlled. It is generally assumed that all plant cells contain essentially identical and cell-autonomous multiloop clocks. Here, we show that the circadian clock in the roots of matureArabidopsisplants differs markedly from that in the shoots and that the root clock is synchronized by a photosynthesis-related signal from the shoot. Two of the feedback loops of the plant circadian clock are disengaged in roots, because two key clock components, the transcription factors CCA1 and LHY, are able to inhibit gene expression in shoots but not in roots. Thus, the plant clock is organ-specific but not organ-autonomous.

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