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ShareScore release 0.9.0
Dataset results
520 results for “Host interactions”
Malaria Host Pathogen Interaction Center Experiment S01: Host and parasite gene transcript abundances, from cultured cells, of Macaca mulatta infected with Plasmodium knowlesi Pk1(A+), Pk1(B+)1+, Pk1(
GEO Series GSE110970. Macaca mulatta; Plasmodium knowlesi. 9 samples. Type: Expression profiling by high throughput sequencing.
A temporal proteogenomic atlas of HCV-host interactions unravels cell circuits driving viral and metabolic liver disease.
GEO Series GSE126831. Homo sapiens. 63 samples. Type: Expression profiling by high throughput sequencing.
The endogenous HBZ interactome in ATL leukemic cells reveals an unprecedented complexity of host interacting partners involved in RNA splicing
GEO Series GSE206085. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
Identification and Targeting of Regulators of SARS-CoV-2-Host interactions in the Airway Epithelium
GEO Series GSE262588. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing; Other.
Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection [RNA-Seq]
GEO Series GSE126901. human metagenome. 35 samples. Type: Expression profiling by high throughput sequencing.
SARS-CoV-2 Nucleocapsid protein attenuates stress granule formation and interacts directly with mRNAs to impair host stress response (iCLIP-Seq)
GEO Series GSE171008. Homo sapiens. 18 samples. Type: Other.
Host-pathogen interaction profiling of nontypeable Haemophilus influenzae and Moraxella catarrhalis coinfection of bronchial epithelial cells.
GEO Series GSE283527. Homo sapiens; Moraxella catarrhalis; Haemophilus influenzae. 48 samples. Type: Expression profiling by high throughput sequencing.
Data from "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"
<p>This file contains raw data for the manuscript:<br> "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"<br> <em>ACS Nano</em> 2020, 14, 5, 5382–5391, DOI: <a href="https://doi.org/10.1021/acsnano.9b08752">10.1021/acsnano.9b08752</a></p> <p>The data is transmission electron microscopy (TEM) images of of gold nanoparticles.</p> <p> </p> <p> </p> <p> </p>
Data from: Host interaction analysis of PA-N155 and PA-N182 in chicken cells reveals an essential role of UBA52 for replication of H5N1 avian influenza virus
PA-N155 and PA-N182 proteins were translated from the 11th and 13th start codon AUG of the RNA polymerase acidic protein (PA) mRNA of H5N1 influenza A virus (IAV), which plays an important role in viral replication. Little is known about the interactions between PA-N155 and PA-N182 and the host proteins. This study investigated the interaction landscape of PA-N155 and PA-N182 of H5N1 IAV in chicken cells while their interacting complexes were captured by immunoprecipitation and analyzed by mass spectrometry. A total of 491 (PA-N155) and 302 (PA-N182) interacting proteins were identified. Gene ontology and pathway enrichment analyses showed that proteins of the two interactomes were enriched in RNA processing, viral processing and protein transport, and proteins related to signaling pathways of proteasome, ribosome, and aminoacy1-tRNA biosynthesis were significantly enriched, suggesting their potential roles in H5N1 IAV infection. Comparative analysis of the interactome of PA, PA-N155, and PA-N182 identified UBA52 as a conserved host factor that interacted with all three viral proteins. UBA52 is a fusion protein consisting of ubiquitin at the N terminus and ribosomal protein L40 at the C terminus. Knockdown of UBA52 significantly decreased the titer of H5N1 IAV in chicken cells and was accompanied with attenuated production of proinflammatory cytokines. Our analyses of the influenza–host protein interactomes identified UBA52 as a PA interaction protein for virus replication.
Data from: The impact of bottlenecks on microbial survival, adaptation and phenotypic switching in host-pathogen interactions
Microbial pathogens and viruses can often maintain sufficient population diversity to evade a wide range of host immune responses. However, when populations experience bottlenecks, as occurs frequently during initiation of new infections, pathogens require specialized mechanisms to regenerate diversity. We address the evolution of such mechanisms, known as stochastic phenotype switches, which are prevalent in pathogenic bacteria. We analyze a model of pathogen diversification in a changing host environment that accounts for selective bottlenecks, wherein different phenotypes have distinct transmission probabilities between hosts. We show that under stringent bottlenecks, such that only one phenotype can initiate new infections, there exists a threshold stochastic switching rate below which all pathogen lineages go extinct, and above which survival is a near certainty. We determine how quickly stochastic switching rates can evolve by computing a fitness landscape for the evolutionary dynamics of switching rates, and analyzing its dependence on both the stringency of bottlenecks and the duration of within-host growth periods. We show that increasing the stringency of bottlenecks or decreasing the period of growth results in faster adaptation of switching rates. Our model provides strong theoretical evidence that bottlenecks play a critical role in accelerating the evolutionary dynamics of pathogens.
Data from: Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change
Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host–pathogen interactions when predicting disease impacts. We emphasize the need to consider host–tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host–pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host–pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases. This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'.
Experimental habitat fragmentation disrupts host-parasite interaction over decades via life-cycle bottlenecks
Habitat loss and fragmentation are likely to seriously impact parasites, a less studied but critical component of ecosystems, yet we lack long-term experimental evidence. Parasites structure communities, increase connectivity in food webs, and account for a large proportion of an ecosystem's total biomass. Food web models predict that parasites with multiple obligate hosts are at greater risk of extinction because the local extinction, or reduction in abundance, of any host will result in a life-cycle bottleneck for the parasite. We examine the response of a parasite and its multiple hosts to forest fragmentation over 26 years in the Wog Wog Habitat Fragmentation Experiment in southeastern Australia. The parasite is the nematode Hedruris wogwogensis, its intermediate host is the amphipod, Arcitalitrus sylvaticus, and its definitive host is the skink, Lampropholis guichenoti. In the first decade after fragmentation, nematodes completely disappeared from the matrix (plantation forestry) and all but disappeared from their definitive host (skinks) in fragments, and by the third decade after fragmentation had not appreciably recovered anywhere in the fragmented landscape compared to continuous forest. The low prevalence of the nematode in the fragmented landscape was associated with the low abundance of one or the other host in different decades: low abundance of the intermediate host (amphipod) in the first decade and low abundance of the definitive host (skink) in the third decade. In turn, the low abundance of each host was associated with changes to the abiotic environment over time due largely to the dynamically changing matrix as the plantation trees grew. Our study provides rare long-term experimental evidence of how disturbance can cause local extinction in parasites with life cycles dependent on more than one host species through population bottlenecks at any life stage. Mismatches in the abundance of multiple hosts over time are likely to be common following disturbance, thus causing parasites with complex life cycles to be particularly susceptible to habitat fragmentation and other disturbances. The integrity of food webs, communities, and ecosystems in fragmented landscapes may be more compromised than presently appreciated due to the sensitivity of parasites to habitat fragmentation.
Data from: Defining host–pathogen interactions employing an artificial intelligence workflow
For image-based infection biology, accurate unbiased quantification of host–pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentation. Host protein recruitment to pathogens is often refractory to accurate automated assessment due to its heterogeneous nature. An intuitive intelligent image analysis program to assess host protein recruitment within general cellular pathogen defense is lacking. We present HRMAn (Host Response to Microbe Analysis), an open-source image analysis platform based on machine learning algorithms and deep learning. We show that HRMAn has the capacity to learn phenotypes from the data, without relying on researcher-based assumptions. Using Toxoplasma gondii and Salmonella enterica Typhimurium we demonstrate HRMAn's capacity to recognize, classify and quantify pathogen killing, replication and cellular defense responses. HRMAn thus presents the only intelligent solution operating at human capacity suitable for both single image and high content image analysis.
Dataset for "Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine"
<p>Dataset:</p> <p>Data1. Host gene expression profile</p> <p>Data2. Microbiome gene expression profile</p>
Resolving the haplotypes of arbuscular mycorrhizal fungi highlights the role of two nuclear populations in host interactions
<p>This repository contains the annotations, analyses and scripts used to create the figures for the dikaryotic strains of <em>R. irregularis</em> chromosome assemblies.</p>
Host-Diet-Gut Interaction Post Vegan Diet in Pediatric Autoimmune Hepatitis.
ClinicalTrials.gov study NCT07118657. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Immunological Interaction Between the Host and Candida Albicans Biofilm
ClinicalTrials.gov study NCT01919931. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Multi-omics Studies of Host-microbiome Interaction in Chronic Obstructive Pulmonary Disease and Bronchiectasis
ClinicalTrials.gov study NCT05738044. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Interaction Between Host, Microenvironment and Immunity on Gastrointestinal Neoplasms
ClinicalTrials.gov study NCT04363983. IPD Sharing: NO. Countries: 1. Publications: 0.
Spatial Analysis of Host-parasite Interactions in Cutaneous Leishmaniasis in Ethiopia
ClinicalTrials.gov study NCT05332093. IPD Sharing: YES. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.