Does it pay off to link functional gene expression to denitrification rates via modelling?

2020 ◽  
Author(s):  
Anna Störiko ◽  
Holger Pagel ◽  
Olaf Cirpka
Keyword(s):  
Gene Expression ◽  
Mechanistic Model ◽  
Reaction Rates ◽  
Biological Data ◽  
State Variables ◽  
Turnover Rates ◽  
Using Data ◽  
Inhibition Control ◽  
Denitrification Genes ◽  
The Relationship

<p>The abundances of functional genes and transcripts have provided new insights into microbially mediated biogeochemical processes and might improve quantitative predictions of turnover rates.<br>However, the relationship between reaction rates and the gene and transcript abundances may not be a simple correlation.<br>Most mechanistic reaction models cannot predict molecular-biological data, and it is unclear how they can be informed by such data.</p><p>We developed a mechanistic model that considers transcript abundances of denitrification genes, enzyme concentrations, biomass, and solute concentrations as state variables that are interrelated by ordinary differential equations, and thus mechanistically links molecular-biological data to reaction rates.<br>Important features of transcript dynamics can be reproduced with the transcript-based model.</p><p>We calibrated the model using data from a batch experiment with a denitrifying organism at the onset of anoxia.<br>We explored the relationship between transcript abundances and reaction rates by analyzing the model results.<br>The transcript abundances reacted very quickly to substrate concentrations so that we could simplify the model by assuming a quasi steady state of the transcripts.</p><p>We compared our model to a classical Monod-type formulation, which was as good at simulating the concentrations of nitrogen species as the transcript-based model, but it cannot make use of any molecular-biological data.<br>Our results, thus, suggest that enzyme kinetics (substrate limitation, inhibition) control denitrification rates more strongly than the dynamics of gene expression.</p>

scholarly journals Does It Pay Off to Explicitly Link Functional Gene Expression to Denitrification Rates in Reaction Models?

2021 ◽  
Vol 12 ◽  
Author(s):  
Anna Störiko ◽  
Holger Pagel ◽  
Adrian Mellage ◽  
Olaf A. Cirpka
Keyword(s):  
Gene Expression ◽  
Reaction Rates ◽  
Biological Data ◽  
Functional Gene ◽  
Type Model ◽  
Enzyme Dynamics ◽  
Gene Transcripts ◽  
Open Question ◽  
The Relationship ◽  
Unique Relationship

Environmental omics and molecular-biological data have been proposed to yield improved quantitative predictions of biogeochemical processes. The abundances of functional genes and transcripts relate to the number of cells and activity of microorganisms. However, whether molecular-biological data can be quantitatively linked to reaction rates remains an open question. We present an enzyme-based denitrification model that simulates concentrations of transcription factors, functional-gene transcripts, enzymes, and solutes. We calibrated the model using experimental data from a well-controlled batch experiment with the denitrifier Paracoccous denitrificans. The model accurately predicts denitrification rates and measured transcript dynamics. The relationship between simulated transcript concentrations and reaction rates exhibits strong non-linearity and hysteresis related to the faster dynamics of gene transcription and substrate consumption, relative to enzyme production and decay. Hence, assuming a unique relationship between transcript-to-gene ratios and reaction rates, as frequently suggested, may be an erroneous simplification. Comparing model results of our enzyme-based model to those of a classical Monod-type model reveals that both formulations perform equally well with respect to nitrogen species, indicating only a low benefit of integrating molecular-biological data for estimating denitrification rates. Nonetheless, the enzyme-based model is a valuable tool to improve our mechanistic understanding of the relationship between biomolecular quantities and reaction rates. Furthermore, our results highlight that both enzyme kinetics (i.e., substrate limitation and inhibition) and gene expression or enzyme dynamics are important controls on denitrification rates.

scholarly journals Characterizing chemotherapy-induced neutropenia and monocytopenia through mathematical modelling

2020 ◽  
Author(s):  
Tyler Cassidy ◽  
Antony R. Humphries ◽  
Morgan Craig ◽  
Michael C. Mackey
Keyword(s):  
Mechanistic Model ◽  
Lymphoblastic Leukemia ◽  
Optimal Strategies ◽  
Concurrent Chemotherapy ◽  
Response To Chemotherapy ◽  
Hematopoietic Toxicity ◽  
Chemotherapy Induced Neutropenia ◽  
Using Data ◽  
Neutrophil Response ◽  
The Relationship

AbstractIn spite of the recent focus on the development of novel targeted drugs to treat cancer, cytotoxic chemotherapy remains the standard treatment for the vast majority of patients. Unfortunately, chemotherapy is associated with high hematopoietic toxicity that may limit its efficacy. We have previously established potential strategies to mitigate chemotherapy-induced neutropenia (a lack of circulating neutrophils) using a mechanistic model of granulopoiesis to predict the interactions defining the neutrophil response to chemotherapy and to define optimal strategies for concurrent chemotherapy/prophylactic granulocyte colony-stimulating factor (G-CSF). Here, we extend our analyses to include monocyte production by constructing and parameterizing a model of monocytopoiesis. Using data for neutrophil and monocyte concentrations during chemotherapy in a large cohort of childhood acute lymphoblastic leukemia patients, we leveraged our model to determine the relationship between the monocyte and neutrophil nadirs during cyclic chemotherapy. We show that monocytopenia precedes neutropenia by 3 days, and rationalize the use of G-CSF during chemotherapy by establishing that the onset of monocytopenia can be used as a clinical marker for G-CSF dosing post-chemotherapy. This work therefore has important clinical applications as a comprehensive approach to understanding the relationship between monocyte and neutrophils after cyclic chemotherapy with or without G-CSF support.

scholarly journals Identification of blood autosomal cis-expression quantitative trait methylation (cis-eQTMs) in children

2020 ◽  
Author(s):  
Carlos Ruiz-Arenas ◽  
Carles Hernandez-Ferrer ◽  
Marta Vives-Usano ◽  
Sergi Marí ◽  
Inés Quintela ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Quantitative Trait ◽  
Association Studies ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Biological Interpretation ◽  
Cell Type Specific ◽  
Using Data ◽  
The Relationship

AbstractBackgroundThe identification of expression quantitative trait methylation (eQTMs), defined as correlations between gene expression and DNA methylation levels, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis-eQTMs in child blood, using data from 832 children of the Human Early Life Exposome (HELIX) project.MethodsBlood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (transcription start site (TSS) within a window of 1 Mb) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, and cohort.ResultsWe identified 63,831 autosomal cis-eQTMs, representing 35,228 unique CpGs and 11,071 unique transcript clusters (TCs, genes). 74.3% of these cis-eQTMs were located at <250 kb, 60.0% showed an inverse relationship and 23.9% had at least one genetic variant associated with the methylation and expression levels. They were enriched for active blood regulatory regions. Adjusting for cellular composition decreased the number of cis-eQTMs to 37.7%, suggesting that some of them were cell type-specific. The overlap of child blood cis-eQTMs with those described in adults was small, and child and adult shared cis-eQTMs tended to be proximal to the TSS, enriched for genetic variants and with lower cell type specificity. Only half of the cis-eQTMs could be captured through annotation to the closest gene.ConclusionsThis catalogue of blood autosomal cis-eQTMs in children can help the biological interpretation of EWAS findings, and is publicly available at https://helixomics.isglobal.org/.

scholarly journals Simulation of the metabolism of absorbed energy-yielding nutrients in young sheep

1984 ◽  
Vol 52 (3) ◽  
pp. 621-649 ◽  
Author(s):  
Margaret Gill ◽  
J. H. M. Thornley ◽  
J. L. Black ◽  
J. D. Oldham ◽  
D. E. Beever
Keyword(s):  
Basic Assumption ◽  
Reaction Rates ◽  
Metabolizable Energy ◽  
State Variables ◽  
Nutrient Inputs ◽  
Absorbed Energy ◽  
Protein Deposition ◽  
Maximum Reaction ◽  
Synthetic Reactions ◽  
The Relationship

1. A mathematical model is described, which simulates the metabolism of absorbed nutrients (amino acids, acetic acid, butyric acid, glucose, lipid and propionic acid) in growing sheep.2. The basic assumption of the model is that each nutrient is partitioned between synthetic, oxidative or intermediate reactions with rates of reaction which are described using enzyme kinetics. These rates depend on the relationship between maximum reaction rates, constants of affinity and inhibition and the concentrations of metabolites as determined by the model.3. Synthetic reactions calculate fat and protein deposition while intermediate reactions involve the production of ATP and NADPH. There is a total of twelve state variables and the model, programmed in CSMP and ACSL, is solved by integration of twelve differential equations.4. The model calculates the efficiency of utilization of metabolizable energy for different nutrient inputs and the results may be interpreted in terns of fluxes through the metabolite pools. Simulations using inputs representing forage- and concentrate-based diets indicated decreased efficiency for the forage at high levels of intake and possible reasons for this were further studied in simulations where the inputs of protein and glucose were varied.

scholarly journals Distinguishing between models of mammalian gene expression: telegraph-like models versus mechanistic models

2021 ◽  
Author(s):  
Svitlana Braichenko ◽  
James Holehouse ◽  
Ramon Grima
Keyword(s):  
Gene Expression ◽  
Experimental Data ◽  
Mammalian Cells ◽  
Mechanistic Model ◽  
Waiting Times ◽  
Mechanistic Models ◽  
Region I ◽  
History Of ◽  
State Models ◽  
The Relationship

Two-state models (telegraph-like models) have a successful history of predicting distributions of cellular and nascent mRNA numbers that can well fit experimental data. These models exclude key rate limiting steps, and hence it is unclear why they are able to accurately predict the number distributions. To answer this question, here we compare these models to a novel stochastic mechanistic model of transcription in mammalian cells that presents a unified description of transcriptional factor, polymerase and mature mRNA dynamics. We show that there is a large region of parameter space where the first, second and third moments of the distributions of the waiting times between two consecutively produced transcripts (nascent or mature) of two-state and mechanistic models exactly match. In this region, (i) one can uniquely express the parameters of the two-state models in terms of those of the mechanistic model, (ii) the models are practically indistinguishable by comparison of their transcript numbers distributions, and (iii) they are distinguishable from the shape of their waiting time distributions. Our results clarify the relationship between different gene expression models and identify a means to select between them from experimental data.

scholarly journals A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Lai ◽  
Animesh Bhattacharya ◽  
Ulf Schmitz ◽  
Manfred Kunz ◽  
Julio Vera ◽  
...  
Keyword(s):  
Systems Biology ◽  
Gene Regulatory Networks ◽  
Mirna Expression ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Mechanistic Model ◽  
Biological Data ◽  
Combining Data ◽  
Gene Regulatory ◽  
Using Data

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

Accent Policy and Accent Modification Enterprises as Potential Indicators of Intercultural Power Relations: A Call for an Updated Research Agenda

2013 ◽  
Vol 3 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Brynne D. Ovalle ◽  
Rahul Chakraborty
Keyword(s):  
International Relations ◽  
Identity Construction ◽  
Social Theory ◽  
Power Relations ◽  
Linguistic Diversity ◽  
Cultural Organization ◽  
Using Data ◽  
The Individual ◽  
The Impact ◽  
The Relationship

This article has two purposes: (a) to examine the relationship between intercultural power relations and the widespread practice of accent discrimination and (b) to underscore the ramifications of accent discrimination both for the individual and for global society as a whole. First, authors review social theory regarding language and group identity construction, and then go on to integrate more current studies linking accent bias to sociocultural variables. Authors discuss three examples of intercultural accent discrimination in order to illustrate how this link manifests itself in the broader context of international relations (i.e., how accent discrimination is generated in situations of unequal power) and, using a review of current research, assess the consequences of accent discrimination for the individual. Finally, the article highlights the impact that linguistic discrimination is having on linguistic diversity globally, partially using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and partially by offering a potential context for interpreting the emergence of practices that seek to reduce or modify speaker accents.

Workplace Ostracism and Its Negative Outcomes

2016 ◽  
Vol 15 (4) ◽  
pp. 143-151 ◽  
Author(s):  
Xiaoming Zheng ◽  
Jun Yang ◽  
Hang-Yue Ngo ◽  
Xiao-Yu Liu ◽  
Wengjuan Jiao
Keyword(s):  
Affective Commitment ◽  
Psychological Capital ◽  
Intention To Leave ◽  
Future Research ◽  
Conservation Of Resources ◽  
Negative Consequences ◽  
Negative Outcomes ◽  
Workplace Ostracism ◽  
Using Data ◽  
The Relationship

Abstract. Workplace ostracism, conceived as to being ignored or excluded by others, has attracted the attention of researchers in recent years. One essential topic in this area is how to reduce or even eliminate the negative consequences of workplace ostracism. Based on conservation of resources (COR) theory, the current study assesses the relationship between workplace ostracism and its negative outcomes, as well as the moderating role played by psychological capital, using data collected from 256 employees in three companies in the northern part of China. The study yields two important findings: (1) workplace ostracism is positively related to intention to leave and (2) psychological capital moderates the effect of workplace ostracism on affective commitment and intention to leave. This paper concludes by discussing the implications of these findings for organizations and employees, along with recommendations for future research.

Plasminogen Depletion during Streptokinase Treatment or Two-Chain Urokinase Incubation Correlates with Decreased Clot Lysability Ex Vivo and In Vitro

1993 ◽  
Vol 70 (06) ◽  
pp. 0998-1004 ◽  
Author(s):  
Páll T Önundarson ◽  
H Magnús Haraldsson ◽  
Lena Bergmann ◽  
Charles W Francis ◽  
Victor J Marder
Keyword(s):  
Myocardial Infarction ◽  
Ex Vivo ◽  
Time Dependent ◽  
State Variables ◽  
Thrombolytic Treatment ◽  
Direct Proportion ◽  
Plasmin Activity ◽  
Plasma Exposure ◽  
The Relationship

SummaryThe relationship between lytic state variables and ex vivo clot lysability was investigated in blood drawn from patients during streptokinase administration for acute myocardial infarction. A lytic state was already evident after 5 min of treatment and after 20 min the plasminogen concentration had decreased to 24%, antiplasmin to 7% and fibrinogen 0.2 g/1. Lysis of radiolabeled retracted clots in the patient plasmas decreased from 37 ± 8% after 5 min to 21 ± 8% at 10 min and was significantly lower (8 ± 9%, p <0.005) in samples drawn at 20, 40 and 80 min. Clot lysability correlated positively with the plasminogen concentration (r = 0.78, p = 0.003), but not with plasmin activity. Suspension of radiolabeled clots in normal plasma pre-exposed to 250 U/ml two-chain urokinase for varying time to induce an in vitro lytic state was also associated with decreasing clot lysability in direct proportion with the duration of prior plasma exposure to urokinase. The decreased lysability correlated with the time-dependent reduction in plasminogen concentration (r = 0.88, p <0.0005). Thus, clot lysability decreases in conjunction with the development of the lytic state and the associated plasminogen depletion. The lytic state may therefore limit reperfusion during thrombolytic treatment.

Editor’s Pick: Regulatory and Ethical Issues in the New Era of Radiomics and Radiogenomics

EMJ Radiology ◽  
2020 ◽  
Author(s):  
Filippo Pesapane
Keyword(s):  
Ethical Issues ◽  
Medical Images ◽  
Practical Significance ◽  
Innovative Technology ◽  
New Era ◽  
Naked Eye ◽  
Disease Characteristics ◽  
The Future ◽  
Using Data ◽  
The Relationship

Radiomics is a science that investigates a large number of features from medical images using data-characterisation algorithms, with the aim to analyse disease characteristics that are indistinguishable to the naked eye. Radiogenomics attempts to establish and examine the relationship between tumour genomic characteristics and their radiologic appearance. Although there is certainly a lot to learn from these relationships, one could ask the question: what is the practical significance of radiogenomic discoveries? This increasing interest in such applications inevitably raises numerous legal and ethical questions. In an environment such as the technology field, which changes quickly and unpredictably, regulations need to be timely in order to be relevant.  In this paper, issues that must be solved to make the future applications of this innovative technology safe and useful are analysed.

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