Cell biological and proteogenomic study of the chloroplast of the marine, bloom-forming dinoflagellate P. cordatum

Test data amaizing

LIMAQUA results in an innovative process for converting and recirculating aquaculture side-streams (sludge and wastewater) in algae (Galdieria sulphuraria)-based feed production for aquacultures. In conventional aquaculture, feed production is responsible for 50% of greenhouse gas (GHG) emission. The aim is to substantially reduce GHG emission by considering geographic and site-specific characteristics (temperature, sunshine duration etc.) and to design site-specific phototrophic or heterotrophic ...

Project Overview

Databases of biomedical knowledge are rapidly proliferating and growing, with recent advances (such as the RTX-KG2 knowledge-base that we have recently developed; (Wood et al. 2022)) increasingly focusing on integration of knowledge under a standardized schema and semantic layer (i.e., controlled vocabularies for types of concepts and types of relationships, for example, the Biolink standard (Unni et al. 2022)). The rise of standardized knowledge-bases sets the stage for the ...

MESI-STRAT Review

Endometriosis research done by the Griffith lab (MIT) and the Goods lab (Dartmouth)

Trabajo de Fin de Master

supplementary materials

Developing a placenta on a chip

This work aims to identify the biochemical pathways of THP-1 human monocytes infected by different Leishmania infantum clinical isolates from patients with either resistance or with TF outcome, using whole cell differential Mass Spectrometry proteomics. Network enrichment analysis was adopted to integrate the transcriptomics and the proteomic results of infected cells studies. Transferrin Receptor C and Nucleoside Diphosphate Kinase 3 were discovered as overexpressed proteins in THP-1 cells ...

This investigation serves as supplementary material for a SWAT4HCLS publication that describes minimum metadata and provenance requirements for reproducible enrichment analysis results.

Functional enrichment analysis is an essential downstream process in high throughput omics studies, such as transcriptomics and proteomics. By using the Gene Ontology (GO) and its annotations (GOA), underlying functional patterns of over-representation can be identified, leading to ...

Aims: The immune response is important for mediating the benefit of cardiac cell therapies. The role of varied immune responses in influencing the outcome of cardiomyocyte cell transplantation after myocardial infarction was investigated. Methods and Results: Cardiac flow cytometric analysis of C57BL/6J and T- and B cell deficient Rag2del mice revealed varied CD11b, natural killer and dendritic cell responses following sham injection and a disparate macrophage response after myocardial infarction. ...

Members of the genus Aromatoleum are cosmopolitan in diverse habitats and utilize a broad range of recalcitrant organic molecules coupled to denitrification or O2-respiration. To gain a holistic understanding of the model organism A. aromaticum EbN1T, we here studied its catabolic network dynamics in response to 3-(4-hydroxyphenyl)propanoate, phenylalanine, 3-hydroxybenzoate, benzoate and acetate utilized under nitrate-reducing vs. oxic conditions. Multi-OMICS (transcriptome, proteome and metabolome) ...

1. To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
2. To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M. hyopneumoniae for vaccine optimization
3. To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2) aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a serum-free growth medium and; 4) assess, at genome scale, the metabolic ...

This study describes the results of a survey on enrichment analysis tool usage and provenance reporting for a corpus of SARS-CoV2 data.

This study contains the singele nuclei data analysis part of the Bl6 and Rag2del comparison. Here, we used Seurat, harmony, and monocle for an in-depth analysis.

Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to “low quality” potentially leading to data misinterpretation. Common standard quality control parameters involve the ...

This study contains our snRNA-Seq based comparison of whole hearts from Fzt.DU and Bl6 mice published in Cardiovascular Research.

This study includes the single snRNA-seq in whole adult murine hearts from an inbred (C57BL/6NRj) and an outbred (Fzt:DU) mouse strain in comparison to publicly available scRNA-seq data of the tabula muris project.

This study contains our single nuclei characterisation of whole hearts from Fzt.DU mice published in Cells.

Predictions made using the core model for combinatorial perturbations to the model simulating combined effects from OE, KO mutants, perturbations and time series concentrations.

Internal metabolites concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations External metabolite concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations Mutant (OE, KO, perturbation) metabolite measurements

Training of the core model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data. The core model contains reactions in glycolysis, pyruvate metabolism and ATPase

Validation of the core model of glycolysis, pyruvate metabolism and ATPase reaction using OE, KO mutant samples and perturbation samples

This section contains all the raw data and files required for each figures.

Construction of a Genome scale constrained-based metabolic modeling of M. hyopneumonia

Proteomics Average and SD data for time series data, 6h, 12h, 24h, 48h,72, 96h per protein

Contains copy number per locus tag at different times of Growth between 0.25h and 96 hours. M. pneumoniae was grown in Batch, cells attached to the bottom of the flask (single cell layer), non stirred, non aerated.

RobOKoD algorithm was, designed then implemented as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain. It was shown to perform better than similar methods (OptKnock, and RobustKnock).

OptKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

RobustKnock algorithm was used as part of a study in RobOKoD: microbial strain design for (over)production of target compounds. (http://fairdomhub.org/publications/236). It was used to generate a strain of e.coli for producing butanol, that was then compared to an experimental strain.

Training of the model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data.

Validation by simulating independent OE, KO mutant and perturbation samples, using sampling of the gausian distribution based on the mean and SD of measurements per sample. A 1000 samples of the gausian distribution of the mean and SD was performed per sample to show error in the measurements and how it propegates in predicted metabolite concentration in SS

Comparison of Kcat values from the model and values from literature.

Protein copy number at 6h, 12h, 24h, 48h, 72h, 96h, average values and SD for the measurements

Metabolomics time series measurements for internal metabolites for 6h, 24h and 48h for multiple experiments. Largely based on MAss spectrometry, bioluminescence kits to measure NAD, NADH at 24h, other time points are infered from relative measurements times the absolute measurements at 24h.

Simulation of OE mutants targetting enzymes in the model, combined with metabolite concentrations and enzyme fold change of from the 40 samples. For each second mutant the enzyme concentrations in case of OE and KO mutants in updated and the metabolite concentrations of the second sample are loaded in the model. Using this approach the model approximately predicts combinatorial effects of OE mutations with other mutations, perturbations and time series concentrations.

Measurements of external metabolites based on growth curve data. Flux estimates for uptake of external metabolites such as glucose and production rates for external metabolites lactate and acetate

Construction and manual curated Genome Scale Metabolitic model of M. hyopneumoniae. Dynamic flux balance analysis was performed for glucose uptake

Contains the analysis of the internal metabolite concentrations of the 40 independend samples Pearson correlation was used to generate heatmaps Pearson correlation with p-value cutof of 0.001 was used and as input for a correlation network (grouping using H-clust) Principal component analysis was performed on samples, F-ion and H-ion data combined and seperately Zip files contains the data (FC.txt), PCA and heatmap plots and the script to re-generate these plots

Metabolic control analysis: Local control coefficients for 40 independent samples based on 100x sampling from the measurement distribution Global control analysis based on 100.000 Latin Hypercube sampling from the parameter search range (0.01-100 for Km values and 0.001-1000 for Vmax values)

The associated zip files contains all input files and a Jupyter notebook to rerun sampled simmulations, combined simmulations, parameter scan for the model with addition of an oxygin inhibiton of LDH, local- and global-sensitivity analysis and plot simmulation output in various formats. In addition the zip file contains the py36.yaml file that can be used to recreate the model simmulation environment using Anaconda making all simmulations completely reproducable. All information on how to use ...

Content:

• Compiled 15 columns annotation of P. cordatum (Dougan et al. 2022)
• Summary of predicted unknown proteins of P. cordatum
• Calculations of predicted unknown proteins of P. cordatum

Tab color: annotation, purple; unknowns, green

• Calculations of predictions of all identified proteins of P. cordatum
• Calculations of fold-changes of all identified proteins (cell vs. nuclei fraction) of P. cordatum
• Calculations of predictions of proteins of unknown function of_ P. cordatum_
• Calculations of fold-changes of unknowns (cell vs. nuclei fraction) of P. cordatum

Tab color: all identified proteins, purple; unkowns, green

Content:

• Nuclear protein fractions: NSP, NMP and NTP R1-R3 (Peptide counts)
• Summary nuclear proteins geLC
• Cellular protein fractions: CSP, CMP R1-R3 (Peptide counts)
• Summary cellular proteins geLC
• Summary nuclear protein fractions NSP R1-R3 (iBAQs)
• Summary cellular protein fractions CSP R1-R3 (iBAQs)
• 15 columns annotation
• Final summary of protein data
• Prediction results
• Annotation (biological processes and categories)

Tab color: raw data, green; summarized data, orange; final ...

• Summary of functional categorization of all identified proteins of P. cordatum
• Calculations of general functions (Fig. 5, left panel)
• Calculations of nuclear functions (Fig. 5, right panel)
• Categories in separate sheets

Tab color: Summarized data, purple; calculations, organge; functional categories, green

• Summary of nuclear proteins
• Separate sheets of nuclear processes (MBNP_Histones, DNA replication, DNA repair, RNA processing (rRNA and mRNA processing), transcription, import and export, ubiquitylation, proteasome, biogenesis ribosomes)
• Ribosomes (category translation)

Tab color: Summary, purple; nuclear processes, green; ribosomes, orange

Prepared (sub-)cellular fractions were separated by gradient SDS-PAGE and entire sample lanes cut into pieces prior to in-gel digest and nanoLC separation coulpled to iontrap MS/MS detection.

Supplementary movie of the distribution of nuclear pores in the nuclear envelope of P. cordatum

Movie of the chromosomal packing in the nucleus of P. cordatum MPEG format (mp4)

• Amira raw data of nuclear structures of P. cordatum
• Volume calculations of nuclear structures of_ P. cordatum _

• raw data tif-file, stacked image for 3D reconstruction of the nucleus of P. cordatum

This file provides a full list of the PubMed IDs used as input to our survey of SARS-CoV2 enrichment analysis results

A list of the search terms used for identifying SARS-CoV2 studies involving enrichment analysis. A random sample of 100 papers were used as input to the experiment.

Summary of identified ribosomal proteins of P. cordatum.

Summary table of identified pigment binding proteins with relative shares in % and calculations of total amount of pigment binding proteins in the different data sets.

Underlying R script for the investigation of immune cells. Script contains basic data processing, as well as a DE and monocle analysis.

Stoichiometric model in SBML format using the acetate-aerobic standard scenario.

Please note that SBML was exported using the sbmlwriter class of Metano. This file was not used for the actual analyses.

This stoichiometric model of Aromatoleum aromaticum EbN1 is a genome-scale model and comprises 655 enzyme-catalyzed reactions and 731 distinct metabolites.

The model is in the plain-text reaction format of Metano that is human-readable and can be opened with every text editor. To run this version of the model, please use the Metano Modeling Toolbox (mmtb.brenda-enzymes.org) and the associated scenario files.

A population of turtles have between 1 and 3 genes contributing to the strength of selective destruction, which can either cause ageing or allow for negligible senescence.

Model of selective destruction in a single population of cells with differing sensitivities for growth. Fast growing cells can be epigenetically converted to slower cells rather than simple cell death as in previous models.

Model of unselective destruction in a single population of cells with differing sensitivities for growth

Model of selective destruction in a single population of cells with differing sensitivities for growth

Here, we describe the index file generation of the mm10 genome, the genome alignment with kallisto, and quantification with bustools to obtain the used spliced / unspliced transcript input.

Here is the detailed R script to generate the input needed by scSynO for synthetic cell generation and classification model training.

The code that can be embedded into any other Seurat data processing workflow is:

cell_expression_target_cluster <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = "target_cluster_number")]) cell_expression_all_other_clusters <- as.matrix(GetAssayData(seuratobject, slot = "data")[, WhichCells(seuratobject, ident = ...

Single nuclei transcriptomics data as .csv files from the Allen Brain atlas data set of mus musculus (https://celltypes.brain-map.org/) have been utilized as an input for scSynO. The underlying analysis is part of the manuscript entitled "Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling". Data anaylsis and visalizations were mainly generated with the Seurat R package (https://satijalab.org/seurat/archive/v3.2/spatial_vignette.html)

Dynamic model of glycolysis, pyruvate metabolism and NoxE. The model is parameterized by selecting the best out of 100 parameter set using Copasi's Genetic algorithm with 1000 itterations and 500 simmulatanious models.

The new GEM of S. coelicolor developed by Tjasa Kumelj, Snorre Sulheim, Alexander Wentzel and Eivind Almaas in 2017/2018

Core model with the addition of a NoxE reaction to regenerate NAD using O2. COPASI’s build in Evolutionary programming algorithm was used to estimate parameters using a maximum of 2000 generations with a population size of 100 models with value scaling as weights to train the 5 parameters of the NoxE reaction.

Butanol producing iNS142, redesigned using RobOKoD.

E.coli Core model, with additional reactions added to generate the beta-oxadation cycle. This is the basic model used in RobOKoD: microbial strain design for (over)production of target compounds (http://fairdomhub.org/publications/236).

This file contains the script for the downstream scRNA-Seq analysis including quality control using the barcode ranking method together with the tool DropletUtils to exclude empty droplets and undetected genes as well as standard data processing (normalisation, variable feature identification, scaling, and dimensionality reduction) using tools of Seurat (v.3.2.2). After cluster annotation the %mtDNA was plotted for both datasets.

This file contains the detailed experimental protocol for the cultivation of "induced sinoatrial bodies (iSABs), the scRNA-Seq procedure as well as the general computational workflow for data processing. The R-script is provided separately.

This file contains the R-script to analyse single nuclei and single cell data of Bl6 and Fzt:DU mice previously processed with cellranger. The analyses utilizes the Seurat and harmony package to integrate three datasets before subsequent downstream analysis characterizing proliferative cardiomyocytes.

This file contains the detailed experimental protocol to isolate nuclei from murine hearts.

This R-script contains the single nuclei analysis for our Fzt:DU and BL6 data, namely bustools file integration, preprocessing, scaling, clustering, marker indentification and annotation of markers and RNAvelocity computation.

Detection of small RNAs by blot hybridization.

Describes the steps required in order to detect and quantify alcohols and other volatile compounds in microbial culture supernatants by gas chromatography with a flame-ionization detector (GC-FID).

This protocol describes the analysis of RNA-Seq data to identify differential expressed genes between two samples. The protocol is simply the analysis of the data and do not include the sequencing protocol.

Metabolomics perturbation sample preparation and description of how the exact details of the perturbations. Perturbations: -Glucose starvation -Amino acid starvation -Fe2+ depletion -Oxidative stress via H2O2 -Glycerol addition to the medium

Standard Operating Procedure describing the process and software used in generating a Genome Scale Metabolic model of M. hyopneumoniae. Used software: Pathway tools PathLogic Cobrapy the Cobra Toolbox libSBML