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Phase Contrast Time-Lapse and F-actin Imaging of Mechanically Compressed or Irradiated Pseudostratified Human Bronchial Epithelial Cells

Overview This dataset includes phase contrast time-lapse imaging of in vitro pseudostratified airway epithelial cells to visualize their collective cellular migration after exposure to mechanical compression (mimicking bronchoconstriction) or irradiation. Additionally, the cells were fixed and stained for F-actin to visualize the apical cell boundaries, basal cell boundaries, and basal cell stress fibers. Cell Culture and Treatment Primary human bronchial epithelial cells (from a single donor) were grown on transwells in air-liquid interface (ALI) culture for 14 days to model a well-differentiated, pseudostratified airway epithelium. Cells were then exposed to either mechanical compression (30 cmH2O for 3 hours) mimicking asthmatic bronchoconstriction or irradiation (1Gy of ionizing radiation using a RS 2000 Biological Research Irradiator (RadSource) on ALI days 7, 10, and 14). Phase Contrast Time-Lapse Imaging At 24 or 72 hours after final treatment, cells were imaged to visualize collective cellular migration. For each independent experimental replicate (2 transwells per treatment per timepoint), six fields of view per well were imaged every 6 minutes over 1.5 hours. The imaging chamber was supplied with 37°C, 5% CO2, humidified air on a Zeiss Axio Observer Z1 to collect phase contrast images. The image resolution is 0.586 µm/pixel. Immunofluorescence Imaging Cells were fixed (4% PFA for 30 minutes) at 24 or 72 hours after final treatment (and after phase contrast time-lapse imaging). Fixed transwells were stained for F-actin (Alexa fluor 488-Phalloidin, ThermoFisher Scientific, diluted 1:40, 30 minutes). Transwell membranes were cut from the plastic support and mounted on glass slides. Slides were imaged using a Zeiss Axio Observer Z1 with an apotome module controlled using Zen Blue 2.0 software. Five random fields of view were imaged from each transwell membrane in a z-stack from substrate to apical cell surface. To visualize various planes through the pseudostratified epithelial layer (apical cell boundaries, basal cell boundaries, and basal cell stress fibers), maximum intensity projections were generated from regions of interest through the z-stack. The image resolution is 0.293 µm/pixel. Dataset Phase contrast time-lapse movies are provided as *.avi files. Immunofluorescence images are provided as *.tif files. For an individual transwell, the imaging dataset includes: <ul> <li>6 phase contrast time-lapse movies</li> <li>5 immunofluorescence images of apical cell boundaries</li> <li>5 immunofluorescence images of basal cell boundaries</li> <li>5 immunofluorescence images of basal cell stress fibers</li> </ul> Phase contrast time-lapse filenames contain <ul> <li>Donor: U13</li> <li>Timepoint: 24 or 72 hours</li> <li>Treatment & Well: control (C), mechanical compression (P), or irradiation (R); well 1 or 2</li> <li>Field of View: (1) – (6)</li> </ul> Immunofluorescence image filenames contain: <ul> <li>Donor: U13</li> <li>Timepoint: 24 or 72 hours</li> <li>Treatment & Well: control (C), mechanical compression (P), or irradiation (R); well 1 or 2</li> <li>Field of View: 1-5</li> <li>Region of Interest: apical cell boundaries (ACB), basal cell boundaries (BCB), or basal stress fibers (SF)</li> </ul> Phase contrast time-lapse and immunofluorescence from the same transwell will all start with the same “Donor_Timepoint_Treatment/Well...” (i.e. U13_24_C1…). Note that the images from phase contrast and immunofluorescence are not necessarily from matched locations within the transwell and are at different spatial scales. Immunofluorescence images from the same z-stack field of view will start with the same “Donor_Timepoint_Treatment/Well_FieldofView…” (i.e. U13_24_C1_1…).

Haematopoietic multi-potent progenitor cells dynamics

Data accompanying the paper: "Heterogeneous run-and-tumble motion accounts for transient non-Gaussian super-diffusion in haematopoietic multi-potent progenitor cells" by Benjamin Partridge,Sara Gonzalez Anton, Reema Khorshed, George Adams, Constandina Pospori, Cristina Lo Celso, and Chiu Fan Lee

Gene expression counts from induced Pluripotent Stem Cells

File description: <ol> <li> Gene-level counts using the gtf file from the release 34 of GENCODE <a href="https://www.gencodegenes.org/human/release_34">https://www.gencodegenes.org/human/release_34</a> </li> <li> Split counts spanning from one exon to another using an annotation-free algorithm, therefore capturing new splice sites </li> <li> Non-split counts covering exon-intron boundaries </li> <li> Sample annotation describing each sample from the dataset </li> <li> Description file with global information from the dataset </li> </ol> Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, the workflow DROP can be used to compute expression and splicing outliers (<a href="https://github.com/gagneurlab/drop">https://github.com/gagneurlab/drop</a>). Maintainer: Vicente A. Yépez, <a href="mailto:yepez@in.tum.de">yepez@in.tum.de</a> URL: <a href="https://github.com/gagneurlab/drop/">https://github.com/gagneurlab/drop/</a>   Title: induced Pluripotent Stem Cells Number of samples: 330 Tissue: iPSCs Organism: Homo sapiens Genome assembly: hg19 Gene annotation: gencode34 Disease: None Strand specific: True Paired end: True Dataset contact: Marc Bonder, marcj89 at gmail.com Citation: Cite both the resource using Zenodo's citation and the publication under References

[Demo Input Data] for SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells

This archive (input.tar.gz) contains the demo data for SCAFE v1.0.0 (on <a href="https://doi.org/10.5281/zenodo.7023163">Zenodo</a> or <a href="https://github.com/chung-lab/SCAFE/releases/tag/v1.0.0">Github</a>) SCAFE (Single Cell Analysis of Five-prime Ends) provides an end-to-end solution for processing of single cell 5’end RNA-seq data. It takes a read alignment file (*.bam) from single-cell RNA-5’end-sequencing (e.g. 10xGenomics Chromimum®), precisely maps the cDNA 5'ends (i.e. transcription start sites, TSS), filters for the artefacts and identifies genuine TSS clusters using logistic regression. Based on the TSS clusters, it defines transcribed cis-regulatory elements (tCRE) and annotated them to gene models. It then counts the UMI in tCRE in single cells and returns a tCRE UMI/cellbarcode matrix ready for downstream analyses, e.g. cell-type clustering, linking promoters to enhancers by co-activity etc. For details on installation, usage and test run on demo data, visit <a href="https://github.com/chung-lab/SCAFE">https://github.com/chung-lab/SCAFE</a>

Processed KnockTF2 experiments of human cells

Processed perturbation experiments of human cells from <a href="http://www.licpathway.net/KnockTFv2/index.php">KnockTF2</a> to easily benchmark methods and networks using <a href="http://decoupler-py.readthedocs.io/">decoupleR</a>. The file <a href="http://www.licpathway.net/KnockTFv2_download/knocktf_v2_main_human.txt">Human Differential Expression of Genes</a> was processed to extract a matrix of logFCs were experiments are rows and genes are columns. Their associated meta-data was downloaded from the <a href="http://www.licpathway.net/KnockTFv2/browse_human.php#">Browse</a> tab. Identifiers were unified to match both matrix and meta-data. I do not claim ownership of these data. If used, please cite their original source: Chenchen Feng, Chao Song, Yuejuan Liu, Fengcui Qian, Yu Gao, Ziyu Ning, Qiuyu Wang, Yong Jiang, Yanyu Li, Meng Li, Jiaxin Chen, Jian Zhang, Chunquan Li, KnockTF: a comprehensive human gene expression profile database with knockdown/knockout of transcription factors, Nucleic Acids Research, Volume 48, Issue D1, 08 January 2020, Pages D93–D100, <a href="https://doi.org/10.1093/nar/gkz881">https://doi.org/10.1093/nar/gkz881</a>

opencc-by-4.0Jul 2022View details →

Establishment of a Spermatogonial Stem Cell Line with Potential of Meiosis in a Hermaphroditic Fish, Epinephelus coioides

Figure S1. Cell localization of ly75, thy1, and dmc1 in adult testis of orange-spotted grouper. (A-C) Antisense probe signals of ly75, thy1, and dmc1. (D-F) Sense probe signals of ly75, thy1, and dmc1. Sg, Spermatogonium; Sc, Spermatocyte; St, spermatid. Scale Bars: 20 μm. Figure S2. Fluorescent immunostaining of antibodies in adult testis of orange-spotted grouper. (A-D and M-O) Fluorescence signals of Piwi, Dazl, Ssea1, Nanog, PCNA, Sycp3, and Dmc1. (E-H and P-R) Nuclei are counterstained with PI. (I-L and S-U) Merge images. Sg, Spermatogonium; Sc, Spermatocyte; St, spermatid; Sz, spermatozoa. Scale Bars: 20 μm. Figure S3. Derivation of a single colony from a single cell of GPT line. (A) A small colony after five days of culture. (B) A distinct colony after 10 days of culture. (C) A large colony containing hundreds of cells after 20 days of culture. Scale Bars: 20 μm in A; 50 μm in B; 200 μm in C. Figure S4. Prolonged cultivation of GPT cells under the lack of bFGF. (A-D) All GPT cells would differentiate into large epithelial-like cells and gradually die out during 25 days of culture under the lack of bFGF, LIF, and SCF (-/-). (E-H, J-M, and O-R) GPT cells consisted of some polygonal-like cells and many epithelial-like cells during 25 days of culture in the ESM media containing SCF and/or LIF. (I, N and S) All GPT cells transformed into very large epithelial-like cells and gradually died after 35 days of culture in the ESM media containing SCF and/or LIF. Scale Bars: 50 μm. Figure S5. Morphology of GPT cells under a condition of high cell confluence. (A) GPT cells were cultured for 14 days without subculture and (B) generated a few spherical cells (Arrows). Scale Bars: 50 μm in A; 20 μm in B. Figure S6. Establishment of a GPT cell line stably expressing green fluorescence protein. (A-C) Bright-field image, fluorescent image, and merged image of GPT cells after 48 hours of culture following electrotransfection with pEGFP-N3 plasmid. (D-F) Bright-field image, fluorescent image, and merged image of GPT cells after G418 resistance screening. Scale Bars: 200 μm in A-C; 100 μm in D-F.

Datasets for 'Label-free imaging of 3D pluripotent stem cell differentiation dynamics on chip'

Here we publish the datasets associated with our publication ‘Label-free imaging of 3D pluripotent stem cell differentiation dynamics on chip’. 3D cultures of human induced pluripotent stem cells (hiPSCs) were imaged while undergoing definitive endoderm (DE) differentiation. Data were acquired either on the live 3D cultures at various time points during the 3 days DE differentiation, or after fixation and immunostaining, with the 3D cultures being fixed at regular 24 h intervals during differentiation, as to form a timeline. Images were recorded with a standard confocal microscope using a xy-resolution of 0.25 μm/px and a z-resolution of 1 μm/plane.

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Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores

Supporting data for paper "Long-Term, Single-Molecule Imaging of Proteins in Live Cells with Photoregulated Fluxional Fluorophores"

BCL6 deletion in CD4 T cells reveals Th2 eff mediated immunity in the skin

RNA-Seq datasets related to the study of Mouse Tfh cells. Recent studies propose that Group 2 T follicular helper (Tfh) cells have a higher degree of functional plasticity in addition to their well-defined roles in mediating IL-4-dependent switching of germinal centre B cells to the production of IgG1 and IgE antibodies. In particular Tfh cells have been proposed to be an essential stage in Th2 effector cell development that are able to contribute to innate Type 2 responses. We used CD4-cre targeted deletion of BCL6 to identify the contribution Tfh cells make to tissue Th2 effector responses in models of skin atopic disease   and lung immunity to parasites. Ablation of Tfh cells did not impair the development or recruitment of Th2 effector subsets to the skin and did not alter the transcriptional expression profile or functional activities of the resulting tissue resident Th2 effector cells. However, the accumulation of Th2 effector cells in lung Th2 responses was partially affected by BCL6 deficiency. These data indicate that the development of Th2 effector cells does not require a BCL6 dependent step implying Tfh and Th2 effector populations follow separate developmental trajectories and Tfh cells do not contribute to Type 2 responses in the skin . This study reveals important findings that add to the growing literature around the plasticity and functional interconversion of T helper subsets.

Limosilactobacillus reuteri IDCC 3701 - Cell Free Supernatant

This is the raw-data regarding the CFS of the probiotic Limosilactobacillus reuteri IDCC 3701.

ETV6 represses Tumor Necrosis Factor During Stress Hematopoiesis to Regulate Mouse Stem Cell Function

At the root of the blood system lies a heterogenous population of hematopoietic stem and progenitor cells (HSPCs), which reside in the bone marrow (BM) and give rise to diverse blood lineages. Maintaining this pool of self-renewing HSPCs is critical to uphold hematopoiesis during period of stress such as bleeding or infection1. ETS Variant Transcription Factor 6 (ETV6) is a transcriptional repressor that is highly expressed in HSPCs2 where it is essential for development and maintenance of the adult hematopoiesis 3. In 2015, our group4 and others5-7  identified germline pathogenic ETV6 variants in families with predisposition to B-acute lymphoblastic leukemia (B-ALL) and thrombocytopenia, defining a new genetic syndrome known as Thrombocytopenia 5 (T5). Subsequently, we performed targeted germline ETV6 sequencing of remission blood samples from over 4,000 children with B-ALL and identified germline ETV6 variants in ~1% of cases7. In vitro studies revealed that ETV6 variant proteins exhibit impaired repressor activity, reduced DNA binding, and aberrant subcellular localization4,5,7,8. Overall, these studies indicated that T5-associated germline ETV6 variants negatively impact the repressor activity of ETV6. In support of this notion, transcriptional profiling of peripheral blood cells from T5 patients has revealed upregulation of interferon response genes9. Nevertheless, little remains known about the mechanisms by which ETV6 regulates the HSPC compartment and how T5-associated ETV6 variants contribute to disease.   To address these questions, we used CRISPR-Cas9 gene editing to generate a novel mouse model harboring a pathogenic heterozygous germline Etv6 variant, R355X, the murine equivalent to the human T5-associated variant R359X10. Through the comprehensive study of this model, we describe a novel role for ETV6 during aging and regenerative hematopoiesis and show that the heterozygous Etv6R355X variant impairs HSC function in vitro and in vivo. Using genomic approaches to interrogate mouse and human HSCs, we identify new ETV6 targets, including the gene encoding Tumor Necrosis Factor (TNF) and genes involved in TNF signaling. Further, we show increased TNF production and cell cycling in Etv6R355X/+ mouse HSPCs post-BM transplantation. Finally, we demonstrate that genetic ablation of Tnf restores the long-term potential of Etv6R355X/+ cells in serial replating assays in vitro. Together, these findings provide novel insights into the pathways regulated by ETV6 and demonstrate how a pathogenic variant impacts ETV6 function in the context of hematopoietic stress. All bulk RNAseq, Cut&Run, ATACseq, and Hi-C data has been submitted to in the Gene Expression Omnibus (accession number GSE213597) and Sequence Read Archive (BioProject number PRJNA880871). Due to the journal’s limitation on submitted supplementary data  as an Excel file, all post-analysis supplemental data files are deposited in Dryad data repository to be made available with this manuscript.

FOLFOXIRI resistance induction and characterization in human colorectal cancer cells

Supplementary dataset to "FOLFOXIRI resistance induction and characterization in human colorectal cancer cells"

Artificial intelligence for identification of blood cells - Prof Huiyu Zhou (University of Leicester)

This video is the eleventh talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 14/09/2022. Artificial intelligence for identification of blood cells - Prof Huiyu Zhou (University of Leicester) Bio: Prof. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China, and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom. Dr. Zhou currently is a full Professor at School of Computing and Mathematical Sciences, University of Leicester, United Kingdom. He has published over 400 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “MIUA 2020 Best Paper Award”, “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". His research work has been or is being supported by UK EPSRC, ESRC, AHRC, MRC, EU, Royal Society, Leverhulme Trust, Puffin Trust, Alzheimer’s Research UK, Invest NI and industry. Homepage: https://le.ac.uk/people/huiyu-zhou. Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/ This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1 YouTube Link: https://youtu.be/N5AjIUAwYp4

Three-color whole cell LLSM imaging data of ER, H2B, and Lyso over 980 time points during mitosis (ER channel)

This dataset includes the three-color whole cell lattice light-sheet microscopy (LLSM) data of ER, H2B, and Lysosomes over 980 time points at 6 sec intervals in a HeLa cell stably expressing calnexin-mEmerald, H2B-mCherry and Lamp1-Halo during mitosis (only ER channel here due to the file size restriction, other channels can be found in the same depository with different DOI), which was used to demonstrate SiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.

Ultrafst whole cell imaging data of SiT-Golgi vesicles over 10,000 time points

This dataset is the raw lattice light-sheet microscopy data of SiT-Golgi vesicles over 10,000 consecutive time points, which was used to demonstrate TiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.

Discrete Flow Cytometry of Underway Samples from TN398 Using a BD Influx Cell Sorter

The dataset consists of BD Influx-based analysis of picophytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography undergraduate senior thesis cruise (TN398) during December 2021 from Honolulu to San Diego, crossing through the Great Pacific Garbage Patch. The data includes cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus, Synechococcus, and and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton

Three-color whole cell LLSM imaging data of ER, H2B, and Lyso over 980 time points during mitosis (H2B channel)

This dataset includes the three-color whole cell lattice light-sheet microscopy (LLSM) data of ER, H2B, and Lysosomes over 980 time points at 6 sec intervals in a HeLa cell stably expressing calnexin-mEmerald, H2B-mCherry and Lamp1-Halo during mitosis (only H2B channel here due to the file size restriction, other channels can be found in the same depository with different DOI), which was used to demonstrate SiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.

Three-color whole cell LLSM imaging data of ER, H2B, and Mito over 1000 time points during mitosis (Mito channel)

This dataset includes the three-color whole cell lattice light-sheet microscopy (LLSM) data of ER, H2B, and Mitochondia over 1000 time points at 6 sec intervals in a HeLa cell stably expressing calnexin-mEmerald, H2B-mCherry and Mito-Halo during mitosis (only Mito channel here due to the file size restriction, other channels can be found in the same depository with different DOI), which was used to demonstrate SiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.

Three-color whole cell LLSM imaging data of ER, H2B, and Mito over 1000 time points during mitosis (ER channel)

This dataset includes the three-color whole cell lattice light-sheet microscopy (LLSM) data of ER, H2B, and Mitochondria over 1000 time points at 6 sec intervals in a HeLa cell stably expressing calnexin-mEmerald, H2B-mCherry and Mito-Halo during mitosis (only ER channel here due to the file size restriction, other channels can be found in the same depository with different DOI), which was used to demonstrate SiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.

Three-color whole cell LLSM imaging data of ER, H2B, and Lyso over 980 time points during mitosis (Lyso channel)

This dataset includes the three-color whole cell lattice light-sheet microscopy (LLSM) data of ER, H2B, and Lysosomes over 980 time points at 6 sec intervals in a HeLa cell stably expressing calnexin-mEmerald, H2B-mCherry and Lamp1-Halo during mitosis (only Lyso channel here due to the file size restriction, other channels can be found in the same depository with different DOI), which was used to demonstrate SiS-rDL denoising algorithm in our Nature Biotechnology paper (DOI: 10.1038/s41587-022-01471-3). This dataset can be used for non-commercial purposes with proper citations of our NBT paper.