Ontology highlight
ABSTRACT:
PROVIDER: PRJNA918836 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23025615_1.fastq.gz | Fastqsanger.gz | |||
| SRR23025615_2.fastq.gz | Fastqsanger.gz | |||
| SRR23025616_1.fastq.gz | Fastqsanger.gz | |||
| SRR23025616_2.fastq.gz | Fastqsanger.gz | |||
| SRR23025617_1.fastq.gz | Fastqsanger.gz |
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Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
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Project description:To effectively monitor microbial populations in acidic environments and bioleaching systems, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the known genes associated with the acidophiles. This array contained 1,072 probes in which there were 571 related to 16S rRNA and 501 related to functional genes. Acid mine drainage (AMD) presents numerous problems to the aquatic life and surrounding ecosystems. However, little is known about the geographic distribution, diversity, composition, structure and function of AMD microbial communities. In this study, we analyzed the geographic distribution of AMD microbial communities from twenty sites using restriction fragment length polymorphism (RFLP) analysis of 16S rRNA genes, and the results showed that AMD microbial communities were geographically distributed and had high variations among different sites. Then an AMD-specific microarray was used to further analyze nine AMD microbial communities, and showed that those nine AMD microbial communities had high variations measured by the number of detected genes, overlapping genes between samples, unique genes, and diversity indices. Statistical analyses indicated that the concentrations of Fe, S, Ca, Mg, Zn, Cu and pH had strong impacts on both phylogenetic and functional diversity, composition, and structure of AMD microbial communities. This study provides insights into our understanding of the geographic distribution, diversity, composition, structure and functional potential of AMD microbial communities and key environmental factors shaping them. This study investigated the geographic distribution of Acid Mine Drainages microbial communities using a 16S rRNA gene-based RFLP method and the diversity, composition and structure of AMD microbial communities phylogenetically and functionally using an AMD-specific microarray which contained 1,072 probes ( 571 related to 16S rRNA and 501 related to functional genes). The functional genes in the microarray were involved in carbon metabolism (158), nitrogen metabolism (72), sulfur metabolism (39), iron metabolism (68), DNA replication and repair (97), metal-resistance (27), membrane-relate gene (16), transposon (13) and IST sequence (11).
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Project description:A combination of shotgun metaproteomics and 16S rRNA gene pyrosequencing wasused to identify potential functional pathways and key microorganisms involved in long-chain fatty acids (LCFA) anaerobic conversion. Microbial communities degrading saturated- and unsaturated-LCFA were compared. Archaeal communities were mainly composed of Methanosaeta, Methanobacterium and Methanospirillum species, both in stearate (saturated C18:0) and oleate (mono-unsaturated C18:1) incubations. Over 80% of the 16S rRNA gene sequences clustered within the Methanosaeta genus, which is in agreement with the high number of proteins assigned to this group (94%). Archaeal proteins related with methane metabolism were highly expressed. Bacterial communities were rather diverse and the composition dissimilar between incubations with saturated- and unsaturated-LCFA. Stearate-degrading communities were enriched in Deltaproteobacteria (34% of the assigned sequences), while microorganisms clustering within the Synergistia class were more predominant in oleate incubation (25% of the assigned sequences). Bacterial communities were diverse and active, given by the high percentage of proteins related with mechanisms of energy production. Several proteins were assigned to syntrophic bacteria, emphasizing the importance of the interactions between acetogens and methanogens in energy exchange and formation in anaerobic LCFA-rich environments.
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Project description:A combination of shotgun metaproteomics and 16S rRNA gene pyrosequencing wasused to identify potential functional pathways and key microorganisms involved in long-chain fatty acids (LCFA) anaerobic conversion. Microbial communities degrading saturated- and unsaturated-LCFA were compared. Archaeal communities were mainly composed of Methanosaeta, Methanobacterium and Methanospirillum species, both in stearate (saturated C18:0) and oleate (mono-unsaturated C18:1) incubations. Over 80% of the 16S rRNA gene sequences clustered within the Methanosaeta genus, which is in agreement with the high number of proteins assigned to this group (94%). Archaeal proteins related with methane metabolism were highly expressed. Bacterial communities were rather diverse and the composition dissimilar between incubations with saturated- and unsaturated-LCFA. Stearate-degrading communities were enriched in Deltaproteobacteria (34% of the assigned sequences), while microorganisms clustering within the Synergistia class were more predominant in oleate incubation (25% of the assigned sequences). Bacterial communities were diverse and active, given by the high percentage of proteins related with mechanisms of energy production. Several proteins were assigned to syntrophic bacteria, emphasizing the importance of the interactions between acetogens and methanogens in energy exchange and formation in anaerobic LCFA-rich environments.
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