MOESM1 of Comparative analysis of deep sequenced methanogenic communities: identification of microorganisms responsible for methane production
Creators: name: Pyzik, Adam
name: Ciezkowska, Martyna
name: Krawczyk, Pawel
name: Sobczak, Adam
name: Lukasz Drewniak
name: Dziembowski, Andrzej
name: Lipinski, Leszek
Publisher: name: figshare
Year: 2018
Subjects: subject: Biochemistry
subject: Microbiology
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: Genetics
subject: Pharmacology
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: FOS: Earth and related environmental sciences
subject: Ecology
subject: 69999 Biological Sciences not elsewhere classified
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: FOS: Chemical sciences
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: FOS: Health sciences
subject: Plant Biology

description: Additional file 1: Table S1. Physico-chemical characteristics of the studied samples. TS—total solids; VS—volatile solids; COD—chemical oxygen demand; VFA—volatile fatty acids; CH4—methane; #—data not available on site but obtained in laboratory by measuring the effectiveness of methane production from a given substrate. Experiments were performed in 1 L bottles with 10% of the substrate and 90% of mineral water in 37 °C for 21 days; Table S2. MG-RAST statistics of the analyzed metagenomes. Post QC—post quality control; *—percentage of the identified protein features in the predicted protein features; #—percentage of the identified functional categories in the identified protein features; Table S3. Microbial community structure build on protein annotations against the RefSeq database [%]. Only genera with abundance greater than 1% in at least one metagenome were shown. For better readability, Class and Order names were excluded from the table. E—Euryarcheota, A—Acidobacteria, B—Bacteroidetes, C—Chloroflexi, F—Firmicutes, P—Proteobacteria, S—Spirochaetes, T—Tenericutes, TH—Thermotogae, UB—unclassified Bacteria; Table S4. Shannon–Wiener diversity index and Pielou eveness measurement at genus level based on RefSeq annotations data from MG-RAST; Fig. S1. Multidimensional scaling plot of Bray–Curtis dissimilarity at genus level of RefSeq annotations data from MG-RAST. Samples in pairs of ABF and ABF_TS as well as CM and CS overlaps; Table S5. Shannon–Wiener diversity index and Pielou eveness measurement at function level based on Subsystem annotations data from MG-RAST; Fig. S2. Multidimensional scaling plot of Bray–Curtis dissimilarity at function level of Subsystem annotations analyzed by MG-RAST; Fig. S3. Overviews of methanogenesis pathways highlighting the key microorganisms (identified based on MetAnnotate assignments of the genes marked in red) for: (A) agricultural biogas fermenter (ABF); (B) laboratory reactor inoculated with the agricultural biogas fermenter sample (ABF_TS); (C) agricultural biogas hydrolyzer (ABH); (D) cattle manure (CM); (E) cattle slurry (CS); (F) gold mine (GM); (G) lowland bog (LB); (H) wastewater treatment plant (WTP); (I) laboratory reactor inoculated with the wastewater treatment plant sample (WTP_TS). Only genera with hits above 15% were shown with a name. In brackets, the number of microorganisms with hits in the range of 5–15% was indicated. The x sign indicates that sequences for a given enzyme were not detected in metagenomic data by MetAnnotate. The initial substrates for methane production and the final product were marked by bold capital letters. Additionally, initial substrates were underlined and the final product was marked with a frame; Fig. S4. PCR reaction control on isolated metagenomic DNA with primers specific to bacterial and archaeal 16S rDNA variable region V3–V4.