Noise propagation in "Escherichia coli's" regulatory network

The ability to regulate gene expression allows bacteria to grow under diverse conditions, often involving large regulatory networks. As gene expression is an inherently stochastic process, accurate regulation will only be achieved if the molecules involved in the process adapt perfectly to the different conditions and show low noise themselves. In Escherichia coli it has been reported that high noise promoters are characterized by containing a large number of regulatory binding sites in their sequences and that noise propagation from the regulators to their targets is explaining the elevated noise levels. This suggests that regulation and noise are intimately coupled. However, little is known about this association or even how noise levels vary in response to changes in the environment. The work presented in this thesis aims at elucidating to what extent noise and gene regulation are coupled. We have quantified the variation in genome-wide transcriptional noise across 8 diverse growth conditions in Escherichia coli using flow cytometry and high-throughput microscopy. In summary, we find a growth-rate dependent lowerbound on noise mainly exhibited by constitutive promoters. Individual regulated promoters show complex behaviours in terms of changes in mean and noise across conditions, and condition-dependent expression noise shaped by noise propagation from transcription factors. Using a simple linear model we identify a set of TFs that contribute to condition-specific and condition-independent noise propagation. The overall correlation structure of genome-wide expression properties uncovers that genes are organized along two principal axes, with the first one sorting genes by their mean expression and evolutionary rate, and the second one by their expression noise, number of regulatory inputs and expression plasticity. Overall, the results of the thesis show clear evidence that noise and regulation are intimately linked due to noise propagation from regulators to their targets, and that this association has evolved independently of a promoter's expression level or evolutionary rate in its coding region

Respiratory syncytial virus-associated hospitalisation in adults with 2 comorbidities in two European countries:a modelling study

Background: Individuals with comorbidities are at increased risk of severe respiratory syncytial virus (RSV) infection. We estimated RSV-associated respiratory hospitalization among adults aged ≥45 years with comorbidities in Denmark and Scotland. Methods: By analyzing national hospital and virologic data, we estimated annual RSV-associated hospitalizations by 7 selected comorbidities and ages between 2010 and 2018. We estimated rate ratios of RSV-associated hospitalization for adults with comorbidity than the overall population. Results: In Denmark, annual RSV–associated hospitalization rates per 1000 adults ranged from 3.1 for asthma to 19.4 for chronic kidney disease (CKD). In Scotland, rates ranged from 2.4 for chronic liver disease to 9.0 for chronic obstructive pulmonary disease (COPD). In both countries, we found a 2- to 4-fold increased risk of RSV hospitalization for adults with COPD, ischemic heart disease, stroke, and diabetes; a 1.5- to 3-fold increased risk for asthma; and a 3- to 7-fold increased risk for CKD. RSV hospitalization rates among adults aged 45 to 64 years with COPD, asthma, ischemic heart disease, or CKD were higher than the overall population. Conclusions: This study provides important evidence for identifying risk groups and assisting health authorities in RSV vaccination policy making

A comparison of four self-controlled study designs in an analysis of COVID-19 vaccines and myocarditis using five European databases.

INTRODUCTION: The aim of this study was to assess the possible extent of bias due to violation of a core assumption (event-dependent exposures) when using self-controlled designs to analyse the association between COVID-19 vaccines and myocarditis. METHODS: We used data from five European databases (Spain: BIFAP, FISABIO VID, and SIDIAP; Italy: ARS-Tuscany; England: CPRD Aurum) converted to the ConcePTION Common Data Model. Individuals who experienced both myocarditis and were vaccinated against COVID-19 between 1 September 2020 and the end of data availability in each country were included. We compared a self-controlled risk interval study (SCRI) using a pre-vaccination control window, an SCRI using a post-vaccination control window, a standard SCCS and an extension of the SCCS designed to handle violations of the assumption of event-dependent exposures. RESULTS: We included 1,757 cases of myocarditis. For analyses of the first dose of the Pfizer vaccine, to which all databases contributed information, we found results consistent with a null effect in both of the SCRI and extended SCCS, but some indication of a harmful effect in a standard SCCS. For the second dose, we found evidence of a harmful association for all study designs, with relatively similar effect sizes (SCRI pre = 1.99, 1.40 - 2.82; SCRI post 2.13, 95 %CI - 1.43, 3.18; standard SCCS 1.79, 95 %CI 1.31 - 2.44, extended SCCS 1.52, 95 %CI = 1.08 - 2.15). Adjustment for calendar time did not change these conclusions. Findings using all designs were also consistent with a harmful effect following a second dose of the Moderna vaccine. CONCLUSIONS: In the context of the known association between COVID-19 vaccines and myocarditis, we have demonstrated that two forms of SCRI and two forms of SCCS led to largely comparable results, possibly because of limited violation of the assumption of event-dependent exposures

A comparison of four self-controlled study designs in an analysis of COVID-19 vaccines and myocarditis using five European databases

Introduction: The aim of this study was to assess the possible extent of bias due to violation of a core assumption (event-dependent exposures) when using self-controlled designs to analyse the association between COVID-19 vaccines and myocarditis. Methods: We used data from five European databases (Spain: BIFAP, FISABIO VID, and SIDIAP; Italy: ARS-Tuscany; England: CPRD Aurum) converted to the ConcePTION Common Data Model. Individuals who experienced both myocarditis and were vaccinated against COVID-19 between 1 September 2020 and the end of data availability in each country were included. We compared a self-controlled risk interval study (SCRI) using a pre-vaccination control window, an SCRI using a post-vaccination control window, a standard SCCS and an extension of the SCCS designed to handle violations of the assumption of event-dependent exposures. Results: We included 1,757 cases of myocarditis. For analyses of the first dose of the Pfizer vaccine, to which all databases contributed information, we found results consistent with a null effect in both of the SCRI and extended SCCS, but some indication of a harmful effect in a standard SCCS. For the second dose, we found evidence of a harmful association for all study designs, with relatively similar effect sizes (SCRI pre = 1.99, 1.40 – 2.82; SCRI post 2.13, 95 %CI – 1.43, 3.18; standard SCCS 1.79, 95 %CI 1.31 – 2.44, extended SCCS 1.52, 95 %CI = 1.08 – 2.15). Adjustment for calendar time did not change these conclusions. Findings using all designs were also consistent with a harmful effect following a second dose of the Moderna vaccine. Conclusions: In the context of the known association between COVID-19 vaccines and myocarditis, we have demonstrated that two forms of SCRI and two forms of SCCS led to largely comparable results, possibly because of limited violation of the assumption of event-dependent exposures

A comparison of four self-controlled study designs in an analysis of COVID-19 vaccines and myocarditis using five European databases

Introduction: The aim of this study was to assess the possible extent of bias due to violation of a core assumption (event-dependent exposures) when using self-controlled designs to analyse the association between COVID-19 vaccines and myocarditis. Methods: We used data from five European databases (Spain: BIFAP, FISABIO VID, and SIDIAP; Italy: ARS-Tuscany; England: CPRD Aurum) converted to the ConcePTION Common Data Model. Individuals who experienced both myocarditis and were vaccinated against COVID-19 between 1 September 2020 and the end of data availability in each country were included. We compared a self-controlled risk interval study (SCRI) using a pre-vaccination control window, an SCRI using a post-vaccination control window, a standard SCCS and an extension of the SCCS designed to handle violations of the assumption of event-dependent exposures. Results: We included 1,757 cases of myocarditis. For analyses of the first dose of the Pfizer vaccine, to which all databases contributed information, we found results consistent with a null effect in both of the SCRI and extended SCCS, but some indication of a harmful effect in a standard SCCS. For the second dose, we found evidence of a harmful association for all study designs, with relatively similar effect sizes (SCRI pre = 1.99, 1.40 – 2.82; SCRI post 2.13, 95 %CI – 1.43, 3.18; standard SCCS 1.79, 95 %CI 1.31 – 2.44, extended SCCS 1.52, 95 %CI = 1.08 – 2.15). Adjustment for calendar time did not change these conclusions. Findings using all designs were also consistent with a harmful effect following a second dose of the Moderna vaccine. Conclusions: In the context of the known association between COVID-19 vaccines and myocarditis, we have demonstrated that two forms of SCRI and two forms of SCCS led to largely comparable results, possibly because of limited violation of the assumption of event-dependent exposures

Generation and evaluation of a genome-scale metabolic network model of synechococcus elongatus PCC7942

The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942

Respiratory syncytial virus-associated hospitalization in adults with comorbidities in 2 European countries: a modeling study

Background: Individuals with comorbidities are at increased risk of severe respiratory syncytial virus (RSV) infection. We estimated RSV-associated respiratory hospitalization among adults aged ≥45 years with comorbidities in Denmark and Scotland. Methods: By analyzing national hospital and virologic data, we estimated annual RSV-associated hospitalizations by 7 selected comorbidities and ages between 2010 and 2018. We estimated rate ratios of RSV-associated hospitalization for adults with comorbidity than the overall population. Results: In Denmark, annual RSV–associated hospitalization rates per 1000 adults ranged from 3.1 for asthma to 19.4 for chronic kidney disease (CKD). In Scotland, rates ranged from 2.4 for chronic liver disease to 9.0 for chronic obstructive pulmonary disease (COPD). In both countries, we found a 2- to 4-fold increased risk of RSV hospitalization for adults with COPD, ischemic heart disease, stroke, and diabetes; a 1.5- to 3-fold increased risk for asthma; and a 3- to 7-fold increased risk for CKD. RSV hospitalization rates among adults aged 45 to 64 years with COPD, asthma, ischemic heart disease, or CKD were higher than the overall population. Conclusions: This study provides important evidence for identifying risk groups and assisting health authorities in RSV vaccination policy making

Respiratory Syncytial Virus–Associated Hospitalization in Adults With Comorbidities in 2 European Countries: A Modeling Study

Background. Individuals with comorbidities are at increased risk of severe respiratory syncytial virus (RSV) infection. We estimated RSV-associated respiratory hospitalization among adults aged ≥45 years with comorbidities in Denmark and Scotland. Methods. By analyzing national hospital and virologic data, we estimated annual RSV-associated hospitalizations by 7 selected comorbidities and ages between 2010 and 2018. We estimated rate ratios of RSV-associated hospitalization for adults with comorbidity than the overall population. Results. In Denmark, annual RSV–associated hospitalization rates per 1000 adults ranged from 3.1 for asthma to 19.4 for chronic kidney disease (CKD). In Scotland, rates ranged from 2.4 for chronic liver disease to 9.0 for chronic obstructive pulmonary disease (COPD). In both countries, we found a 2- to 4-fold increased risk of RSV hospitalization for adults with COPD, ischemic heart disease, stroke, and diabetes; a 1.5- to 3-fold increased risk for asthma; and a 3- to 7-fold increased risk for CKD. RSV hospitalization rates among adults aged 45 to 64 years with COPD, asthma, ischemic heart disease, or CKD were higher than the overall population. Conclusions. This study provides important evidence for identifying risk groups and assisting health authorities in RSV vaccination policy making