SantiagoSanchezF/mgnify_study_descriptions huggingface dataset:
SHAMAN: a user-friendly website for meta-taxonomic analysis from raw reads to statistical analysis

Profiling differences in microbiome composition regarding a healthy or a disease phenotype is central in microbiome research. It typically involves the sequencing, the data processing, the statistical analysis and the graphical representation of the detected signatures. This process is currently addressed through several separated applications that requires expertise for installation, data pre-processing and in some case, programming skills. We present SHAMAN, which is an interactive web application that facilitates the use of a workflow for OTU calculation, the robust statistical modelling proposed by the DESeq2 package and provides more than ten interactive visualisations. It also implements new normalization methods which account for the sparsity of metagenomic data. %which is relevant for the DESeq2 approach.SHAMAN is primary designed for biologist with no experience in metagenomics, but can also meet the needs of specialist who can easily access to the configuration of processed tools and packages. It is freely accessible at http://shaman.pasteur.fr/, but also work as a standalone application with docker (aghozlane/shaman) or in R with packrat. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using a mock community sequencing and a published 16S metagenomic dataset, we show here that SHAMAN allows to perform a complete meta-taxonomic analysis.

Biome: root:Engineered:Modeled:Simulated communities (sequence read mixture)
The_role_of_the_receptors_of_IL_10_superfamily_members_on_epithelial_cells_during_whipworm_infection_and_immunity

The role of the receptors of IL-10 superfamily members on epithelial cells during whipworm infection and immunity

Biome: root:Host-associated:Mammals
The impact of anthelmintic treatment on human gut microbiota in western Kenya: Cross-sectional and pre-post deworming comparisons

Murine studies suggest that the presence of some species of intestinal helminths is associated with changes in host microbiota composition and diversity. Some changes are even found in anatomic locations remote from where these helminths reside and may persist after helminth clearance. However, studies in humans have produced varied conclusions and the impact appears to vary widely depending on the helminth species present. To demonstrate how molecular approaches to the human gut microbiome can provide insights into the complex interplay among disparate organisms, DNA was extracted from cryopreserved stools collected from residents of 5 rural Kenyan villages prior to, 3 weeks and 3 months following albendazole (ALB) therapy. Samples were analyzed by qPCR for the presence of 8 species of intestinal parasites, and by MiSeq 16S rRNA gene sequencing. Based on pre-treatment results, the presence of neither Ascaris lumbricoides (Al) nor Necator americanus (Na) infection significantly altered the overall diversity of the microbiota in comparison with age-matched controls. Following ALB therapy and clearance of soil-transmitted helminths (STH), there were significant increases in the proportion of the microbiota made up by Clostridiales (p=0.0002, average fold change 0.57), and reductions in the proportion made up by Enterobacteriales (p=0.0004, average fold change -0.58). There were additional changes in the microbiota that appear to be related to ALB administration, suggesting that these antimicrobial effects must be considered in any post-treatment setting. Nevertheless, the helminth-associated changes in Clostridiales and Enterobacteriales suggest that clearance of STH, and Na in particular, alters the gut microbiota.  This submission was done on behalf of Thomas B. Nutman (Principal Investigator) and Alice V. Easton.

Biome: root:Host-associated:Human:Digestive system:Large intestine:Fecal
Mucosal Barrier and Th2 Immune Responses are Enhanced by Dietary Inulin in Pigs Infected with Trichuris suis

Diet composition may play a crucial role in shaping host immune responses and commensal gut microbiota populations. Bioactive dietary components, such as inulin, have been extensively studied for their bioactive properties, particularly in modulating gut immune function and reducing inflammation. It is has been shown that colonization with gastrointestinal parasitic worms (helminths) may alleviate chronic inflammation through promotion of T-helper cell type (Th) 2 and T-regulatory immune responses and alterations in the gut microbiome. In this study, we investigated if dietary inulin could modulate mucosal immune function in pigs during colonization with the porcine whipworm, Trichuris suis. T. suis infection induced a typical Th2-biased immune response characterised by transcriptional changes in Th2- and barrier function-related genes, accompanied by intestinal remodelling through increased epithelial goblet and tuft cell proliferation. We observed that inulin also up-regulated Th2-related immune genes (IL13, IL5), and suppressed Th1-related pro-inflammatory genes (IFNG, IL1A, IL8) in the colon. Notably, inulin augmented the T. suis-induced responses with increased transcription of key Th2 and mucosal barrier genes (e.g. IL13, TFF3), and synergistically suppressed pro-inflammatory genes such as IFNG and CXCL9. 16S rRNA sequencing of proximal colon digesta samples revealed that inulin supplementation reduced the abundance of bacterial phyla linked to inflammation, such as Proteobacteria and Firmicutes, and simultaneously increased Actinobacteria and Bacteroidetes. Interestingly, pigs treated with both inulin and T. suis displayed the highest Bacteroidetes: Firmicutes ratio and the lowest gut pH, suggesting an interaction of diet and helminth infection that stimulates the growth of beneficial bacterial species. Overall, our data demonstrate that T. suis infection and inulin co-operatively enhance anti-inflammatory immune responses, which is potentially mediated by changes in microbiota composition. Our results highlight the intricate interactions between diet, immune function and microbiota composition in a porcine helminth infection model. This porcine model should facilitate further investigations into the use of bioactive diets as immunomodulatory mediators against inflammatory conditions, and how diet and parasites may influence gut health.

Biome: root:Host-associated:Mammals:Digestive system
Shrimp aquaculture

Shrimp aquaculture metagenome

Biome: root:Environmental:Aquatic:Aquaculture
Comparison of soil bacterial communities in crop rotations with different levels of intensification (i.e. number of crops per year), in Oliveros, Santa Fe, Argentina

Comparison of soil bacterial communities in crop rotations with different levels of intensification (i.e. number of crops per year), in Oliveros, Santa Fe, Argentina

Biome: root:Environmental:Terrestrial:Soil:Agricultural
EMG produced TPA metagenomics fasta_path of the Longitudinal_Nasopharyngeal_Microbiome_Dynamics_in_Infants_from_the_Maela_ARI_Birth_Cohort (PRJEB25223) data set.

The PRJEB25223 Third Party Annotation (TPA) fasta_path was derived from the primary whole genome shotgun (WGS) data set: PRJEB25223.  This project includes samples from the following biomes: root:Host-associated:Human:Skin:Naris.

Biome: root:Host-associated:Human:Skin:Naris
EMG produced TPA metagenomics fasta_path of the Novel gut-microbiota based metagenomic signature for advanced fibrosis in nonalcoholic fatty liver disease (PRJNA373901) data set.

The PRJNA373901 Third Party Annotation (TPA) fasta_path was derived from the primary whole genome shotgun (WGS) data set: PRJNA373901.  This project includes samples from the following biomes: root:Host-associated:Mammals:Digestive system:Fecal.

Biome: root:Host-associated:Mammals:Digestive system:Fecal
EMG produced TPA metagenomics fasta_path of the Cow-to-mouse fecal transplantation established intestinal microbiota as cause of cow mastitis (PRJNA357148) data set.

The PRJNA357148 Third Party Annotation (TPA) fasta_path was derived from the primary whole genome shotgun (WGS) data set: PRJNA357148.  This project includes samples from the following biomes: root:Host-associated:Mammals:Digestive system.

Biome: root:Host-associated:Mammals:Digestive system:Large intestine:Fecal
EMG produced TPA metagenomics fasta_path of the Gut metagenomes of rural populations in Cameroon (PRJEB27005) data set.

The PRJEB27005 Third Party Annotation (TPA) fasta_path was derived from the primary whole genome shotgun (WGS) data set: PRJEB27005.  This project includes samples from the following biomes: root:Host-associated:Human:Digestive system:Large intestine:Fecal.

Biome: root:Host-associated:Human:Digestive system:Large intestine:Fecal
Natural Bacterial Communities Associated with Emiliania huxleyi

Coccolithophores are photosynthetic marine microorganisms that cover their eukaryotic cells with calcium carbonate disks. They are of great importance in earth's biogeochemical cycles of oxygen, carbon and sulfur and are essential in marine primary production. The species Emiliania huxleyi is the most abundant coccolithophore micro-alga in modern-day oceans. It creates vast annual blooms that stretch for thousands of square kilometers and can be viewed by satellites from space. These dense blooms end after several weeks with the collapse of the algal population. The collapse of the bloom is usually attributed to viral infections or environmental changes. Recent studies demonstrated that bacteria play an important role in the life and death of E. huxleyi populations. In controlled laboratory experiments, it was shown that the bacterium Phaeobacter inhibens has a dynamic mutualistic-pathogenic interaction with the alga. In a co-culture model system, the microbes first exchange beneficial metabolites, however once the alga ages, the bacterium kills its algal partner. This interaction might contribute to the known E. huxleyi bloom dynamics. Nevertheless, in order to interpret data acquired in the lab, a combination between laboratory findings and field studies will be most beneficial in bridging the complex natural environment of E. huxleyi with the laboratory model system. In this current research I intend to link between lab observations and the marine environment. In order to do so, the identity and relative abundance of bacteria that naturally associate with a stable E. huxleyi population in the gulf of Aqaba will be assessed seasonally in order to account for possible seasonal changes in bacterial composition. In understating who are the bacterial key players in the natural environment of E. huxleyi I hope to attain a wide and unbiased comprehensive view of natural algal-bacterial interactions.

Biome: root:Host-associated:Algae
METAGENOMIC STUDY OF PANCHGAVYA

Panchgavya is a term used to describe five major substances, obtained from cow, which include cow's urine, milk, ghee, curd and dung.

Biome: root:Host-associated:Mammals
Trial B 2019

Trial B 2019

Biome: root:Host-associated:Birds:Digestive system
Turf_Chronosequence_16S_ITS

soil 16S and ITS amplicon from different ecosystems

Biome: root:Environmental:Terrestrial:Soil
CEFS_16S_ITS

soil 16S and ITS amplicon from different ecosystems

Biome: root:Environmental:Terrestrial:Soil
obesity_all

obesity_all

Biome: root:Host-associated:Human:Digestive system:Large intestine:Fecal
IBK Shotgun Metagenomics Analysis Sample B7

IBK Shotgun Metagenomics Analysis Sample B7

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B6

IBK Shotgun Metagenomics Analysis Sample B6

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B5

IBK Shotgun Metagenomics Analysis Sample B5

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B4

IBK Shotgun Metagenomics Analysis Sample B4

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B3

IBK Shotgun Metagenomics Analysis Sample B3

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B2

IBK Shotgun Metagenomics Analysis Sample B2

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample B1

IBK Shotgun Metagenomics Analysis Sample B1

Biome: root:Host-associated:Mammals
IBK Shotgun Metagenomics Analysis Sample A8

IBK Shotgun Metagenomics Analysis Sample A8

Biome: root:Host-associated:Mammals
Passalid Beetle2

Metagenomic characterization of the 4 gut regions (FG, MG, AHG, PHG) of the passalid beetle Odontotaenius disjunctus. The four gut regions of 4 beetles were paired-end sequenced using the Illumina platform.

Biome: root:Host-associated:Insecta:Digestive system
Tucurui_Metagenoma_MGRAST

Functional and taxonomic analysis of samples from the hydroelectric lake of Tucurui.

Biome: root:Environmental:Aquatic:Freshwater:Lake
Metagenomic characterization of dietary changes effects on the gut microbiome in smallholder dairy cattle

Assessment of changes in microbial diversity in rumen liquor and fecal samples from three breeds of dairy cattle fed on an increasing concentrate diet

Biome: root:Host-associated:Mammals:Digestive system
Resistflow-INF-EFF-RNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Bioreactor
Resistflow-NFC-DNF-RNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Bioreactor
RM_CSULB

Grass Rhizosphere

Biome: root:Host-associated:Plants:Rhizosphere
Artificial mix of real bacterial sequences

Mixes of 15 bacterial DNA samples in different known proportion. Used to evaluate the prediction accuracy for 16S and WGS data

Biome: root:Engineered:Modeled:Simulated communities (sequence read mixture)
Resistflow-EFF-DNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Wastewater
Resistflow-DNF-DNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Bioreactor
Resistflow-INF-DNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Wastewater
Resistflow-NFC-DNA data

Ju F, Beck K, Yin X, McArdell Christa, Singer H, Johnson D, Zhang T, Buergmann H *. 2018. Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange and up-regulated expression in the effluent. The ISME Journal (in press)

Biome: root:Engineered:Wastewater:Water and sludge
Indian_sediments

Shotgun metagenomics - sediments contaminated by pharmaceutical discharges. This project contains 11 samples (paired-end 101 bp metagenomic libraries) and sequenced on Illumina HiSeq2000  platform. The raw sequence data of read 1 and read 2 (paired-end) from each metagenome has been uploaded individually.

Biome: root:Environmental:Aquatic:Freshwater:Sediment
Comparative metagenome analysis of normal and arsenic contaminated soils from ballia district, Uttar Pradesh, India

Metagenome of normal soil and arsenic contaminated soil of different agricultural field from Ballia district, Uttar Pradesh, India

Biome: root:Environmental:Terrestrial:Soil
Enriched_Iron_Ore_metagenome

study of Enriched iron ore metagenome

Biome: root:Environmental:Terrestrial:Soil
Joined_Deer

Joined_Deer

Biome: root:Host-associated:Mammals:Digestive system:Fecal
Deer_Metagenomics

Deer_Metagenomics

Biome: root:Host-associated:Mammals
Passalid Beetle

Metagenomic characterization of the 4 gut regions (FG, MG, AHG, PHG) of the passalid beetle Odontotaenius disjunctus. The four gut regions of 4 beetles were paired-end sequenced using the Illumina platform.

Biome: root:Host-associated:Arthropoda:Digestive system:Gut
Palazzo_Ducale_SS

Latrine inside an old palace (18th century) (Sassari - Italy)

Biome: root:Engineered:Wastewater
EMG produced TPA metagenomics assembly of the Thermophilic enriched microbial communities from mini bioreactor at UC Davis - Sample SG0.5JP960 metagenome (compost metagenome) data set.

The compost metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA337831.  This project includes samples from the following biomes: Engineered, Solid waste, Composting.

Biome: root:Engineered:Solid waste:Composting
Metagenomic analysis of marine coastal waters

Marine coastal environment hosts a complex diversity of bacteria and archaea. Here we studied the spatial and temporal dynamic of their genomes populations and functions using metagenomic analysis.

Biome: root:Environmental:Aquatic:Marine:Coastal
Characterisation of gut microbiome of sheep experimentally infected with the parasitic nematode Teladorsagia circumcincta

Characterisation of gut microbiome of (i) sheep experimentally infected with the parasitic nematode Teladorsagia circumcincta, i.e. the primary cause of parasitic gastroenteritis in small ruminants in the UK; (ii) sheep immunised against T. circumcincta with an effective sub-unit vaccine developed by collaborators at the MRI; and (iii) immunologically naïve, uninfected control sheep.

Biome: root:Host-associated:Mammals:Digestive system
EMG produced TPA metagenomics assembly of the Urban Enviromental Genomics Project () data set.

The  Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA415974.  This project includes samples from the following biomes: Engineered, Wastewater.

Biome: root:Engineered:Bioremediation:Terephthalate:Wastewater
EMG produced TPA metagenomics assembly of the samples from sewage Raw sequence reads (wastewater metagenome) data set.

The wastewater metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA388734.  This project includes samples from the following biomes: Engineered, Wastewater.

Biome: root:Engineered:Wastewater
EMG produced TPA metagenomics assembly of the Comparison between mouse caecal contents and faeces (Mouse_caecal_contents_vs_faeces) data set.

The Mouse_caecal_contents_vs_faeces Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJEB15341.  This project includes samples from the following biomes: Host-associated, Mammals, Digestive system, Large intestine, Fecal.

Biome: root:Host-associated:Mammals:Digestive system
EMG produced TPA metagenomics assembly of the Marine sediment trap metagenomes (marine sediment metagenome) data set.

The marine sediment metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA270248.  This project includes samples from the following biomes: Environmental, Aquatic, Marine, Sediment.

Biome: root:Environmental:Aquatic:Marine:Sediment
EMG produced TPA metagenomics assembly of the Gut microbiome profiling of pediatric patients undergoing stem cell transplantation (gut metagenome) data set.

The gut metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA283642.  This project includes samples from the following biomes: Host-associated, Human, Digestive system.

Biome: root:Host-associated:Human:Digestive system
EMG produced TPA metagenomics assembly of the Metagenomic analysis of thiocyanate and cyanide biodegrading microbial consortia Metagenome (bioreactor metagenome) data set.

The bioreactor metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA279279.  This project includes samples from the following biomes: Engineered, Bioreactor.

Biome: root:Engineered:Bioreactor
EMG produced TPA metagenomics assembly of the Microbial metagenome (DNA-seq) of fermented sausages during ripening (food fermentation metagenome) data set.

The food fermentation metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA352236.  This project includes samples from the following biomes: Engineered, Food production.

Biome: root:Engineered:Food production
EMG produced TPA metagenomics assembly of the mouse gut metagenome Metagenome (mouse gut metagenome) data set.

The mouse gut metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA341282.  This project includes samples from the following biomes: Host-associated, Mammals, Digestive system.

Biome: root:Host-associated:Mammals:Digestive system
EMG produced TPA metagenomics assembly of the Antimicrobial resistance of urban water samples (freshwater metagenome) data set.

The freshwater metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA400857.  This project includes samples from the following biomes: Environmental, Aquatic, Freshwater.

Biome: root:Environmental:Aquatic:Freshwater
EMG produced TPA metagenomics assembly of the Metagenomics of chicken manure composts (compost sample) data set.

The compost sample Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA433771.  This project includes samples from the following biomes: Engineered, Solid waste, Composting.

Biome: root:Engineered:Solid waste:Composting
EMG produced TPA metagenomics assembly of the BPA degrading microbial community Raw sequence reads (BPA degrading microbial community) data set.

The BPA degrading microbial community Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA450306.  This project includes samples from the following biomes: Engineered, Wastewater, Activated Sludge.

Biome: root:Engineered:Wastewater:Activated Sludge
EMG produced TPA metagenomics assembly of the metagenomic sequencing on sediments of Xiaomei River (sediment metagenome) data set.

The sediment metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA382755.  This project includes samples from the following biomes: Environmental, Aquatic, Freshwater, Lotic, Sediment.

Biome: root:Environmental:Aquatic:Freshwater:Lotic:Sediment
EMG produced TPA metagenomics assembly of the Rapid Sand Filter Metagenome Genome sequencing and assembly (biofilter metagenome) data set.

The biofilter metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA384587.  This project includes samples from the following biomes: Environmental, Aquatic, Freshwater, Groundwater.

Biome: root:Environmental:Aquatic:Freshwater:Groundwater
EMG produced TPA metagenomics assembly of the epibiont metagenome Raw sequence reads (epibiont metagenome) data set.

The epibiont metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA330990.  This project includes samples from the following biomes: Host-associated, Microbial, Bacteria.

Biome: root:Host-associated:Microbial:Bacteria
EMG produced TPA metagenomics assembly of the Candidatus Accumulibacter enrichment culture Metagenome (bioreactor metagenome) data set.

The bioreactor metagenome Third Party Annotation (TPA) assembly was derived from the primary whole genome shotgun (WGS) data set: PRJNA386410.  This project includes samples from the following biomes: Engineered, Bioreactor.

Biome: root:Engineered:Bioreactor