cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14184882
title: msiFlow: Automated Workflows for Reproducible and Scalable Multimodal Mass Spectrometry Imaging and Immunofluorescence Microscopy Data Processing and Analysis

description: This record contains example and result data of msiFlow.

msiFlow is a collection of automated workflows for reproducible and scalable multimodal mass spectrometry imaging (MSI) and immunofluorescence microscopy (IFM) data processing and analysis. Using an experimental mouse model for urinary tract infection, induced by uropathogenic E.coli (UPEC), we generated data by



matrix-assisted laser desorption ionisation mass spectrometry imaging with laser-induced postionisation (MALDI-2 MSI) using the Bruker timsTOFfleX instrument

transmission-mode MALDI-2 MSI (t-MALDI-2)

immunofluorescence microscopy (IFM) using the MACSima system from Miltenyi 


msiFlow was tested on MALDI-2 MSI, t-MALDI-2 MSI and IFM data of control and UPEC-infected mouse bladder sections. In IFM we used Ly6G and actin for staining neutrophils and the muscle layer. We validated msiFlow on MALDI MSI data of bone marrow (BM)-derived neutrophils. Tentative lipid annotations were validated by MALDI DDA MSI and MALDI MS/MS. All data used and results generated by msiFlow are included in this dataset (besides the intermediate results of the MALDI-2 preprocessing due to data size).

The dataset contains the following zip files:




zip file
description


ly6g_heterogeneity.zip
example and result data (Ly6G clusters) for molecular_heterogeneity_flow


if_segmentation.zip
example and result data (Ly6G segmentation) for if_segmentation_flow


ly6g_heterogeneity_signatures.zip
example and result data (lipids for Ly6G clusters) for molecular_signatures_flow


ly6g_molecular_signatures.zip
example and result data (lipids for Ly6G) for molecular_signatures_flow


msi_if_registration.zip
example and result data for msi_if_registration_flow


msi_segmentation.zip
example and result data (segmented MSI bladder data) for msi_segmentation_flow


region_group_analysis.zip
example and result data (regulated lipids in different bladder tissue regions) for region_group_analysis_flow


macsima.zip
raw IFM data of UPEC-infected bladders containing Ly6G, actin and autofluorescence images


maldi-bm-neutrophils.zip
raw and pre-processed MALDI MSI data of BM-derived neutrophils


t-maldi-2.zip
raw t-MALDI-2 MSI data of a UPEC-infected bladder section


maldi-2-group-sampleno.zip
raw MALDI-2 MSI data of a control/UPEC bladder section


MALDI_DDA_MSI.zip
raw MALDI MSI data acquired in DDA mode


TIMS_MS_MS.zip
raw MALDI TIMS MS/MS data
DOI: 10.5281/zenodo.10698988
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.10659711
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.10719606
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.10784547
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.11498635
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.12821585
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.13786259
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.14184141
title: MicroReset: characterization of the rabbit (Oryctolagus cuniculus) fecal metagenome and resistome by deep shotgun sequencing

description: Data sourceThis dataset was constructed using 30 rabbit fecal samples subjected to deep metagenomic sequencing. Data is published in the Bioproject PRJEB50625
Metagenomic assemblyFirst, sequencing adapters removal and read trimming was performed with fastp. Reads mapped on the host genome (GCF_000001635.27) with bowtie2 were removed with samtools. Finally, Metagenomic assembly was performed with metaSPAdes by processing each sample separately (single-sample assembly). Contigs of less than 1500 bp were removed.
MAGs recoveryReads of each sample were aligned against each assembly (30*30 mappings) with bowtie2 and results were indexed in sorted bam files with samtools. For each assembly, contigs coverage across all samples was computed with jgi_summarize_bam_contig_depths. MAGs were generated with MetaBAT 2 and SemiBin v1.3. MAGs quality was assessed with checkM and those with completeness < 70% or contamination > 5% or N50 < 8Kb were discarded.
DOI: 10.5281/zenodo.13813235
title: CHARMM36M Force Field Parameters for the Thioester Bond between Cysteine and Glycine

description: CHARMM36M force field parameters for the thioester bond connecting the side chain of a cysteine to the carbonyl of a C-terminal glycine.

The dataset includes parameter and auxiliary files in GROMACS format. In addition, a short tutorial shows how to patch the CHARMM36M force field and use the parameters.

These parameters have been developed for the parameterization and simulation of the Ubc6 ubiquitin complex, but can be used with any conparable system.

Details about the parameterization are provided in:

Swarnkar, Anuruti, Florian Leidner, Ashok K. Rout, Sofia Ainatzi, Claudia C. Schmidt, Stefan Becker, Henning Urlaub, Christian Griesinger, Helmut Grubmüller, and Alexander Stein. "Determinants of chemoselectivity in ubiquitination by the J2 family of ubiquitin-conjugating enzymes." The EMBO Journal (2024): 1-35.
DOI: 10.5281/zenodo.13813236
title: CHARMM36M Force Field Parameters for the Thioester Bond between Cysteine and Glycine

description: CHARMM36M force field parameters for the thioester bond connecting the side chain of a cysteine to the carbonyl of a C-terminal glycine.

The dataset includes parameter and auxiliary files in GROMACS format. In addition, a short tutorial shows how to patch the CHARMM36M force field and use the parameters.

These parameters have been developed for the parameterization and simulation of the Ubc6 ubiquitin complex, but can be used with any conparable system.

Details about the parameterization are provided in:

Swarnkar, Anuruti, Florian Leidner, Ashok K. Rout, Sofia Ainatzi, Claudia C. Schmidt, Stefan Becker, Henning Urlaub, Christian Griesinger, Helmut Grubmüller, and Alexander Stein. "Determinants of chemoselectivity in ubiquitination by the J2 family of ubiquitin-conjugating enzymes." The EMBO Journal (2024): 1-35.
DOI: 10.5281/zenodo.10685510
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.10698977
title: A catalog of genes and species of the human oral microbiota
DOI: 10.5281/zenodo.10719586
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.10784558
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.11493681
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.12821296
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.13786233
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.14181351
title: A catalog of genes and species of the human oral microbiota

description: Data sources
DOI: 10.5281/zenodo.10681122
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota

description: Data sources
DOI: 10.5281/zenodo.10701160
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota
DOI: 10.5281/zenodo.10719553
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota
DOI: 10.5281/zenodo.10784524
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota
DOI: 10.5281/zenodo.11491849
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota
DOI: 10.5281/zenodo.12820832
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota

description: Gene catalog constructionThe methodology for creating the IGC2 catalog is described in the original papers: Li et al., 2014 and Wen et al., 2017
MSP creationReads from publicly available human gut metagenomes were aligned against the IGC2 catalog with the Meteor to produce a raw gene abundance table (10.4M genes quantified in >2000 samples). Then, co-abundant genes were binned in 1,989 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of co-abundant genes that likely belong to the same microbial species) using MSPminer.
MSPs taxonomic annotationMSPs taxonomic annotation was performed by aligning MSP core and accessory genes against representative genomes of the Genome Taxonomy Database (GTDB r207) using blastn (task = megablast, word_size = 16). The 20 best hits for each gene were kept (--max-target-seq 20). Using an in-house pipeline, a species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.
Construction of the phylogenetic tree39 universal phylogenetic markers genes were extracted from the MSPs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni). (2021-04-01)
DOI: 10.5281/zenodo.13772391
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota

description: Gene catalog constructionThe methodology for creating the IGC2 catalog is described in the original papers: Li et al., 2014 and Wen et al., 2017
MSP creationReads from publicly available human gut metagenomes were aligned against the IGC2 catalog with the Meteor to produce a raw gene abundance table (10.4M genes quantified in >2000 samples). Then, co-abundant genes were binned in 1,989 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of co-abundant genes that likely belong to the same microbial species) using MSPminer.
MSPs taxonomic annotationMSPs taxonomic annotation was performed by aligning MSP core and accessory genes against representative genomes of the Genome Taxonomy Database (GTDB r207) using blastn (task = megablast, word_size = 16). The 20 best hits for each gene were kept (--max-target-seq 20). Using an in-house pipeline, a species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.
Construction of the phylogenetic tree39 universal phylogenetic markers genes were extracted from the MSPs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni). (2021-04-01)
DOI: 10.5281/zenodo.14181329
title: Updated Metagenomic Species Pan-genomes (MSPs) of the human gastrointestinal microbiota

description: Gene catalog constructionThe methodology for creating the IGC2 catalog is described in the original papers: Li et al., 2014 and Wen et al., 2017
MSP creationReads from publicly available human gut metagenomes were aligned against the IGC2 catalog with the Meteor to produce a raw gene abundance table (10.4M genes quantified in >2000 samples). Then, co-abundant genes were binned in 1,989 Metagenomic Species Pan-genomes (MSPs, i.e. clusters of co-abundant genes that likely belong to the same microbial species) using MSPminer.
MSPs taxonomic annotationMSPs taxonomic annotation was performed by aligning MSP core and accessory genes against representative genomes of the Genome Taxonomy Database (GTDB r207) using blastn (task = megablast, word_size = 16). The 20 best hits for each gene were kept (--max-target-seq 20). Using an in-house pipeline, a species-level assignment was given if > 50% of the genes matched the representative genome of a given species, with a mean identity ≥ 95% and mean gene length coverage ≥ 90%. The remaining MSPs were assigned to a higher taxonomic level (genus to superkingdom), if more than 50% of their genes had the same annotation.
Construction of the phylogenetic tree39 universal phylogenetic markers genes were extracted from the MSPs with fetchMGs. Then, the markers were separately aligned with MUSCLE. The alignments were merged and trimmed with trimAl (parameters: -automated1). Finally, the phylogenetic tree was computed with FastTreeMP (parameters: -gamma -pseudo -spr -mlacc 3 -slownni). (2021-04-01)
DOI: 10.5281/zenodo.14065518
title: Raw data: Nanogels with tailored hydrophobicity and their behavior at air water interfaces

description: Raw data for Journal article: "Nanogels with tailored hydrophobicity and their behavior at air/water interfaces"

Abstract:

The interfacial behavior of micro-/nanogels is governed to a large extent by the hydrophobicity of their polymeric network. Prevailing studies to examine this influence mostly rely on external stimuli like temperature or pH to modulate the colloidal hydrophobicity. Here, a sudden transition between hydrophilic and hydrophobic state prevents systematic and gradual modulation of hydrophobicity. This limits important correlations between interfacial behavior and quantitative physicochemical measures for network hydrophobicity. To address this challenge, we introduce a nanogel platform that allows accurate tuning of hydrophobicity on a molecular level. For this, via post-functionalization of active ester-based particles, we prepare poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) nanogels as a hydrophilic benchmark and introduce gradually varied amounts of hydrophobic propyl or dodecyl moieties to increase the nanogel hydrophobicity. We study the deformation and arrangement of these particles at an air/water interface and correlate the results with quantitative measures for nanogel hydrophobicity. We observe that increasing hydrophobicity of nanogels, either by increasing the hydrophobic moiety ratio or the alkyl chain length, leads to decreased particle deformability and aggregation of an interfacially-adsorbed monolayer. Contrary to what may be intuitively assumed, these changes are not gradual, but rather occur suddenly above a threshold in hydrophobicity. Our study further shows that the effect of hydrophobicity affects the nanogel properties differently in bulk and when adsorbed at liquid interfaces. Thus, this study establishes the transition of interfacial behavior between soft gel-like particles to a solid spherical morphology triggered by the increase in hydrophobicity.
DOI: 10.5281/zenodo.14065519
title: Raw data: Nanogels with tailored hydrophobicity and their behavior at air water interfaces

description: Raw data for Journal article: "Nanogels with tailored hydrophobicity and their behavior at air/water interfaces"

Abstract:

The interfacial behavior of micro-/nanogels is governed to a large extent by the hydrophobicity of their polymeric network. Prevailing studies to examine this influence mostly rely on external stimuli like temperature or pH to modulate the colloidal hydrophobicity. Here, a sudden transition between hydrophilic and hydrophobic state prevents systematic and gradual modulation of hydrophobicity. This limits important correlations between interfacial behavior and quantitative physicochemical measures for network hydrophobicity. To address this challenge, we introduce a nanogel platform that allows accurate tuning of hydrophobicity on a molecular level. For this, via post-functionalization of active ester-based particles, we prepare poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) nanogels as a hydrophilic benchmark and introduce gradually varied amounts of hydrophobic propyl or dodecyl moieties to increase the nanogel hydrophobicity. We study the deformation and arrangement of these particles at an air/water interface and correlate the results with quantitative measures for nanogel hydrophobicity. We observe that increasing hydrophobicity of nanogels, either by increasing the hydrophobic moiety ratio or the alkyl chain length, leads to decreased particle deformability and aggregation of an interfacially-adsorbed monolayer. Contrary to what may be intuitively assumed, these changes are not gradual, but rather occur suddenly above a threshold in hydrophobicity. Our study further shows that the effect of hydrophobicity affects the nanogel properties differently in bulk and when adsorbed at liquid interfaces. Thus, this study establishes the transition of interfacial behavior between soft gel-like particles to a solid spherical morphology triggered by the increase in hydrophobicity.