Biology subjects

Nielsen, J.

Publications and source records attributed to Nielsen, J..

11 recordsLinked to original sources

bioRxiv2018

Investigation of putative regulatory acetylation sites in Fas2p of Saccharomyces cerevisiae

Yeast metabolism is highly regulated, in part via coordinated reprogramming of metabolism on a transcriptional level, for example in response to environmental changes. Furthermore, regulation occurs on the protein level via posttranslational modifications directly affecting enzymatic activity - a mode of regulation that has the benefit of being very fast in response to environmental changes. One group of posttranslational modification that has been suggested to have a high impact on regulation of metabolism are acetylations. Around 4000 distinct protein acetylation sites have been found in Saccharomyces cerevisiae, many of which are located in central metabolic enzymes. However, reports on the verification of regulatory roles of specific acetylation sites on these metabolic enzymes have yet to emerge. This study investigates putative regulatory acetylation sites on Fas2p, which in concert with Fas1p is responsible for cytosolic fatty acid (FA) biosynthesis in S. cerevisiae. Fas2p stands out as one of the most highly acetylated proteins in yeast and is located at a branchpoint of acetyl-CoA metabolism. The amino acids (AAs) glutamine (Q) and arginine (R) were introduced to mimic a constitutively acetylated or non-acetylatable state at three separate lysine sites (K) (K83, K173 and K1551) confirmed to be acetylated in two independent studies, either separately or simultaneously. The results suggest that the residue replacement system in the specific case interferes with the enzymatic function of the fatty acid synthase (FAS), as QQQ and RRR triple mutants both reduce the amount of secreted free fatty acids (FFAs) in a faa1{Delta} faa4{Delta} yeast deletion mutant. The K173Q substitution significantly decreased C16 FA species at the expense of C18 FAs, while no such change could be observed for the corresponding K173R modification.

bioengineering↗

bioRxiv2018

Saccharomyces cerevisiae displays a stable transcription start site landscape in multiple conditions

One of the fundamental processes that determine cellular fate is regulation of gene transcription. Understanding these regulatory processes is therefore essential for understanding cellular responses to changes in environmental conditions. At the core promoter, the regulatory region containing the transcription start site (TSS), all inputs regulating transcription are integrated. Here, we used Cap Analysis of Gene Expression (CAGE) to analyze the pattern of transcription start sites at four different environmental conditions (limited in ethanol, limited in nitrogen, limited in glucose and limited in glucose under anaerobic conditions) using the Saccharomyces cerevisiae strain CEN.PK113-7D. With this experimental setup we were able to show that the TSS landscape in yeast is stable at different metabolic states of the cell. We also show that the shape index, a characteristic feature of each TSS describing the spatial distribution of transcription initiation events, has a surprisingly strong negative correlation with the measured expression levels. Our analysis supplies a set of high quality TSS annotations useful for metabolic engineering and synthetic biology approaches in the industrially relevant laboratory strain CEN.PK113-7D, and provides novel insights into yeast TSS dynamics and gene regulation.

systems biology↗

bioRxiv2018

Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite

Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.\n\nHere, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the models performance parameters, which supports informed model development and facilitates error detection.\n\nMemote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.

systems biology↗

bioRxiv2018

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

systems biology↗

bioRxiv2018

SLIMEr: probing flexibility of lipid metabolism in yeast with an improved constraint-based modeling framework

A recurrent problem in genome-scale metabolic models (GEMs) is to correctly represent lipids as biomass requirements, due to the numerous of possible combinations of individual lipid species and the corresponding lack of fully detailed data. In this study we present SLIMEr, a formalism for correctly representing lipid requirements in GEMs using commonly available experimental data. SLIMEr enhances a GEM with mathematical constructs where we Split Lipids Into Measurable Entities (SLIME reactions), in addition to constraints on both the lipid classes and the acyl chain distribution. By implementing SLIMEr on the consensus GEM of Saccharomyces cerevisiae, we can predict accurate amounts of lipid species, analyze the flexibility of the resulting distribution, and compute the energy costs of moving from one metabolic state to another. The approach shows potential for better understanding lipid metabolism in yeast under different conditions. SLIMEr is freely available at https://github.com/SysBioChalmers/SLIMEr.

systems biology↗

bioRxiv2018

RAVEN 2.0: a versatile platform for metabolic network reconstruction and a case study on Streptomyces coelicolor

RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community.\n\nAuthor summaryCellular metabolism is a large and complex network. Hence, investigations of metabolic networks are aided by in silico modelling and simulations. Metabolic networks can be derived from whole-genome sequences, through identifying what enzymes are present and connecting these to formalized chemical reactions. To facilitate the reconstruction of genome-scale models of metabolism (GEMs), we have developed RAVEN 2.0. This versatile toolbox can reconstruct GEMs fast, through either metabolic pathway databases KEGG and MetaCyc, or from homology with an existing GEM. We demonstrate RAVENs functionality through generation of a metabolic model of Streptomyces coelicolor, an antibiotic-producing bacterium. Comparison of this de novo generated GEM with a previously manually curated model demonstrates that RAVEN captures most of the previous model, and we subsequently reconstructed an updated model of S. coelicolor: Sco4. Following, we used Sco4 to predict promising targets for genetic engineering, which can be used to increase antibiotic production.

systems biology↗

bioRxiv2018

Engineering Lipid Droplet Assembly Mechanisms for Improved Triacylglycerols Accumulation in S. cerevisiae

Production of triacylglycerols (TAGs) through microbial fermentation is an emerging alternative to plant and animal-derived sources. The yeast Saccharomyces cerevisiae is a preferred organism for industrial use but has natively a very poor capacity of TAG production and storage. Here, we engineered S. cerevisiae for accumulation of high TAG levels through the use of structural and physiological factors that influence assembly and biogenesis of lipid droplets. First, human and fungal perilipin genes were expressed, increasing TAG content by up to 36% when expressing the human perilipin gene PLIN3. Secondly, expression of the FIT2 homologue YFT2 resulted in a 26% increase in TAG content. Lastly, the genes ERD1 and PMR1 were deleted in order to induce an ER stress response and stimulate lipid droplet formation, increasing TAG content by 72% for {Delta}erd1, with an additive effect for both YFT2 and PLIN3 expression. These new approaches were implemented in previously engineered strains that carry high flux of fatty acid biosynthesis and conversion of acyl-CoA into TAG, resulting in improvements of up to 138% over those high-producing strains without any substantial growth effects or abnormal cell morphology. We find that these approaches are not only a major advancement in engineering S. cerevisiae for TAG production, but also highlight the importance of lipid droplet dynamics for high lipid accumulation in yeast.

bioengineering↗

bioRxiv2017

Quantitative in vivo evaluation of the reverse β-oxidation pathway for fatty acid production in Saccharomyces cerevisiae

Production of fatty acids using engineered Saccharomyces cerevisiae cells is a challenging task in part due to low efficiency of the native fatty acid biosynthesis pathway. One option for improving production efficiency relies on exploring alternative fatty acid production pathways with either improved kinetics, thermodynamics or yield properties.\n\nIn this work, we explored the reverse {beta}-oxidation pathway as an alternative pathway for free fatty acid production. Different gene combinations and analysis methods were tested for assessing pathway efficiency when expressed in the yeast Saccharomyces cerevisiae. Even though different alternatives were tested, quantitative analysis showed no improvement or major change in fatty acid production of the tested strains in our conditions. This lack of improvement suggests that the tested pathway designs and constructs are either nonfunctional in the tested conditions or the resulting strains lack a metabolic driving force that is needed for a functional pathway.\n\nWe conclude that expression of the reverse {beta}-oxidation pathway in S. cerevisiae poses many challenges when compared to expression in bacterial systems. These factors gravely hinder development efforts and success rate for producing fatty acids through this pathway.

bioengineering↗

bioRxiv2017

Mitochondrial DNA SNPs associated with Schizophrenia exhibit Highly Variable Inter-allelic Haplogroup Affiliation and Nuclear Genogeographic Affinity: Bi-Genomic Linkage Disequilibrium raises Major Concerns for Link to Disease

Mitochondria play a significant role in human diseases. However, disease associations with mitochondrial DNA (mtDNA) SNPs have proven difficult to replicate. A reanalysis of eight schizophrenia-associated mtDNA SNPs, in 23,743 normal Danes and 2,538 schizophrenia patients, revealed marked inter-allelic differences in haplogroup affiliation and nuclear ancestry, genogeophraphic affinity (GGA). This bi-genomic linkage disequilibrium (2GLD) could entail population stratification. Only two mitochondrial SNPs, m. 15043A and m. 15218G, were significantly associated with schizophrenia. However, these associations disappeared when corrected for haplogroup affiliation. The extensive 2GLD documented is a major concern when interpreting historic as well as designing future mtDNA association studies.

genomics↗

bioRxiv2017

Complex spatio-temporal distribution and genogeographic affinity of mitochondrial DNA haplogroups in 24,216 Danes

Mitochondrial DNA (mtDNA) haplogroups (hgs) are evolutionarily conserved sets of mtDNA SNP-haplotypes with characteristic geographical distribution. Associations of hgs with disease and physiological characteristics have been reported, but have frequently not been reproducible. Using 418 mtDNA SNPs on the PsychChip (Illumina), we assessed the spatio-temporal distribution of mtDNA hgs in Denmark in DNA isolated from 24,642 geographically un-biased dried blood spots (DBS), collected from 1981 to 2005 through the Danish National Neonatal Screening program. Geno-geographic affinity (ancestry background) was established with ADMIXTURE using a reference of 100K+ autosomal SNPs in 2,248 individuals from nine populations. The hg distribution was typically Northern European, and hgs were highly variable based on median-joining analysis, suggesting multiple founder events. Considerable heterogeneity and variation in autosomal geno-geographic affinity was observed. Thus, individuals with hg H exhibited 95 %, and U hgs 38.2 % - 92.5 %, Danish ancestry. Significant clines between geographical regions and rural and metropolitan populations were found. Over 25 years, macro-hg L increased from 0.2 % to 1.2 % (p = 1.1*E-10), and M from 1 % to 2.4 % (p = 3.7*E-8). Hg U increased among the R macro-hg from 14.1 % to 16.5 % (p = 1.9*E-3). Geno-geographic affinity, geographical skewedness, and sub-hg distribution suggested that the L, M and U increases are due to immigration. The complex spatio-temporal dynamics and geno-geographic heterogeneity of mtDNA in the Danish population reflect repeated migratory events and, in later years, net immigration. Such complexity may explain the often contradictory and population-specific reports of mito-genomic association with disease.

genomics↗

bioRxiv2017

Fundamental Constraints In Synchronous Muscle Limit Superfast Motor Control In Vertebrates

Superfast muscles (SFM) are extremely fast synchronous muscles capable of contraction rates up to 250 Hz, enabling precise motor execution at the millisecond time scale. To allow such speed, the archetypal SFM, found in the toadfish swimbladder, has hallmark structural and kinetic adaptations at each step of the conserved excitation-contraction coupling (ECC) pathway. More recently SFM phenotypes have been discovered in most major vertebrate lineages, but it remains unknown whether all SFM share ECC adaptations for speed, and if SFM arose once, or from independent evolutionary events. Here we use genomic analysis to identify the myosin heavy chain genes expressed in bat and songbird SFM to achieve rapid actomyosin crossbridge kinetics and demonstrate that these are evolutionarily and ontologically distinct. Furthermore, by quantifying cellular morphometry and calcium signal transduction combined with force measurements we show that all known SFM share multiple functional adaptations that minimize ECC transduction times. Our results suggest that SFM evolved independently in sound producing organs in ray-finned fish, birds, and mammals, and that SFM phenotypes operate at a maximum operational speed set by fundamental constraints in synchronous muscle. Consequentially, these constraints set a fundamental limit to the maximum speed of fine motor control.

physiology↗