Mapping condition-dependent regulation of metabolism in yeast through genome-scale modeling

<p>Background:</p> <p>The genome-scale metabolic model of Saccharomyces cerevisiae, first presented in 2003, was the first genome-scale network reconstruction for a eukaryotic organism. Since then continuous efforts have been made in order to improve and expand the yeast metabolic network.</p> <p>Results:</p> <p>Here we present iTO977, a comprehensive genome-scale metabolic model that contains more reactions, metabolites and genes than previous models. The model was constructed based on two earlier reconstructions, namely iIN800 and the consensus network, and then improved and expanded using gap-filling methods and by introducing new reactions and pathways based on studies of the literature and databases. The model was shown to perform well both for growth simulations in different media and gene essentiality analysis for single and double knock-outs. Further, the model was used as a scaffold for integrating transcriptomics, and flux data from four different conditions in order to identify transcriptionally controlled reactions, i.e. reactions that change both in flux and transcription between the compared conditions.</p> <p>Conclusion:</p> <p>We present a new yeast model that represents a comprehensive up-to-date collection of knowledge on yeast metabolism. The model was used for simulating the yeast metabolism under four different growth conditions and experimental data from these four conditions was integrated to the model. The model together with experimental data is a useful tool to identify condition-dependent changes of metabolism between different environmental conditions.</p

Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics

Background: Metagenomics is the study of microbial communities by sequencing of genetic material directly from environmental or clinical samples. The genes present in the metagenomes are quantified by annotating and counting the generated DNA fragments. Identification of differentially abundant genes between metagenomes can provide important information about differences in community structure, diversity and biological function. Metagenomic data is however high-dimensional, contain high levels of biological and technical noise and have typically few biological replicates. The statistical analysis is therefore challenging and many approaches have been suggested to date. Results: In this article we perform a comprehensive evaluation of 14 methods for identification of differentially abundant genes between metagenomes. The methods are compared based on the power to detect differentially abundant genes and their ability to correctly estimate the type I error rate and the false discovery rate. We show that sample size, effect size, and gene abundance greatly affect the performance of all methods. Several of the methods also show non-optimal model assumptions and biased false discovery rate estimates, which can result in too large numbers of false positives. We also demonstrate that the performance of several of the methods differs substantially between metagenomic data sequenced by different technologies. Conclusions: Two methods, primarily designed for the analysis of RNA sequencing data (edgeR and DESeq2) together with a generalized linear model based on an overdispersed Poisson distribution were found to have best overall performance. The results presented in this study may serve as a guide for selecting suitable statistical methods for identification of differentially abundant genes in metagenomes

Organisatoriska hinder vid miljöinvesteringar i familjeföretag

Det globala miljö- och klimathotet har gjort att företag i allt större utsträckning försöker minska sin klimatpåverkan. Genom miljöinvesteringar – investeringar som är ämnade att minska miljöpåverkan- kan företagen både minska klimatpåverkan och förbättra sin image. Syftet med studien är att undersöka hur ett etablerat företag med vinstintresse arbetar med miljöinvesteringar som inkluderar ickemonetära värden. Den här uppsatsen har använt sig av en kvalitativ forskningsansats där en fallstudie har gjorts av ett tillverkningsföretag. Företaget har valt att vara anonymt, så det påhittade namnet TIAB kommer att användas. TIAB är ett familjeföretag som har funnits sedan 1940-talet. Den insamlade datan tyder på att TIAB inte värderar de ickemonetära värdena en miljöinvestering kan innebära. Analysen identifierar två organisatoriska hinder för miljöinvesteringar inom TIAB. Det ena relaterar till företagets starka sociala institutioner och det andra till företagets absorptionskapacitet. Vidare tar uppsatsen upp olika attityder som företag kan ha till miljöinvesteringar samt möjliga förbättringsåtgärder som TIAB kan använda sig utav för att bättre kunna arbeta med miljöfrågor. De tre miljöansvariga som intervjuas i uppsatsen har högre ambitioner för TIABs arbete med miljöfrågor än vad företaget står för. Att TIAB är ett familjeföretag med en ledning som sedan grundandet har bestått av familjemedlemmar, har resulterat i att en stark institutionalism har skapats. Uppsatsen visar att framförallt starka normer har bidragit till en mer defensiv hållning till miljöfrågor inom företaget. För att bryta dessa normer föreslås en förbättring av företagets absorptionskapacitet i allmänhet.The global environmental and climate threats have increasingly led companies to make efforts to reduce their climate impact. Through environmental investments – capital investments that reduce climate impact- firms can both reduce their climate impact and improve their image. This study has used a qualitative approach where a case study has been made on a production company. The company has chosen to be anonymous, so the made up name of TIAB will be used. TIAB is a family owned business that has existed since the 1940s. The collected data indicates that indicates that TIAB does not value non-monetary values that an environmental investment can include. The essay finds that there are organizational barriers for environmental investments within TIAB. To illustrate these barriers, the essay will use two organization theories – “the new institutionalism and absorption capacity. Furthermore, the essay will enlighten different attitudes that companies can have towards environmental investments and show possible solutions that TIAB can use in order to improve their environmental work. The three environmental employees within TIAB that are interviewed have higher ambition than TIAB as a company, regarding environmental work. The fact that TIAB is a family owned business, with a management that has included family members since the start, may have resulted in strong institutionalism. The essay shows that norms have contributed to a defensive approach towards environmental work within TIAB. To breach these barriers TIAB has to work with absorption capacity in general and internal absorption capacity in particular

KRAS-G12C Mutation in One Real-Life and Three Population-Based Nordic Cohorts of Metastatic Colorectal Cancer

BackgroundKRAS mutations, present in over 40% of metastatic colorectal cancer (mCRC), are negative predictive factors for anti-EGFR therapy. Mutations in KRAS-G12C have a cysteine residue for which drugs have been developed. Published data on this specific mutation are conflicting; thus, we studied the frequency and clinical characteristics in a real-world and population-based setting. MethodsPatients from three Nordic population-based cohorts and the real-life RAXO-study were combined. RAS and BRAF tests were performed in routine healthcare, except for one cohort. The dataset consisted of 2,559 patients, of which 1,871 could be accurately classified as KRAS, NRAS, and BRAF-V600E. Demographics, treatments, and outcomes were compared using logistic regression. Overall survival (OS) was estimated with Kaplan-Meier, and differences were compared using Cox regression, adjusted for baseline factors. ResultsThe KRAS-G12C frequency was 2%-4% of all tested in the seven cohorts (mean 3%) and 4%-8% of KRAS mutated tumors in the cohorts (mean 7%). Metastasectomies and ablations were performed more often (38% vs. 28%, p = 0.040), and bevacizumab was added more often (any line 74% vs. 59%, p = 0.007) for patients with KRAS-G12C- vs. other KRAS-mutated tumors, whereas chemotherapy was given to similar proportions. OS did not differ according to KRAS mutation, neither overall (adjusted hazard ratio (HR) 1.03; 95% CI 0.74-1.42, reference KRAS-G12C) nor within treatment groups defined as "systemic chemotherapy, alone or with biologics", "metastasectomy and/or ablations", or "best supportive care", RAS and BRAF wild-type tumors (n = 548) differed similarly to KRAS-G12C, as to other KRAS- or NRAS-mutated (n = 66) tumors. ConclusionsIn these real-life and population-based cohorts, there were no significant differences in patient characteristics and outcomes between patients with KRAS-G12C tumors and those with other KRAS mutations. This contrasts with the results of most previous studies claiming differences in many aspects, often with worse outcomes for those with a KRAS-G12C mutation, although not consistent. When specific drugs are developed, as for this mutation, differences in outcome will hopefully emerge.Peer reviewe

Management of the endoplasmic reticulum stress by activation of the heat shock response in yeast

In yeast Saccharomyces cerevisiae, accumulation of misfolded proteins in the endoplasmic reticulum (ER) causes ER stress and activates the unfolded protein response (UPR), which is mediated by Hac1p. The heat shock response (HSR) mediated by Hsf1p, mainly regulates cytosolic processes and protects the cell from stresses. Here, we find that a constitutive activation of the HSR could increase ER stress resistance in both wild-type and UPR-deficient cells. Activation of HSR decreased UPR activation in the WT (as shown by the decreased HAC1 mRNA splicing). We analyzed the genome-wide transcriptional response in order to propose regulatory mechanisms that govern the interplay between UPR and HSR and followed up for the hypotheses by experiments in vivo and in vitro. Interestingly, we found that the regulation of ER stress response via HSR is (1) only partially dependent on over-expression of Kar2p (ER resident chaperone induced by ER stress); (2) does not involve the increase in protein turnover via the proteasome activity; (3) is related to the oxidative stress response. From the transcription data, we also propose that HSR enhances ER stress resistance mainly through facilitation of protein folding and secretion. We also find that HSR coordinates multiple stress-response pathways, including the repression of the overall transcription and translation

Genome-scale modeling of the protein secretory machinery in yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery