Djelatnost Odsjeka za povijest hrvatske glazbe Zavoda za povijest hrvatske književnosti, kazališta i glazbe HAZU u 2016. godini

<i>Geobacter sulfurreducens</i> is a dissimilatory metal-reducing bacterium capable of forming thick electron-conducting biofilms on solid electrodes. Here we employ for the first time comparative proteomics to identify key physiological changes involved in <i>G. sulfurreducens</i> adaptation from fumarate-respiring planktonic cells to electron-conducting biofilms. Increased levels of proteins involved in outer membrane biogenesis, cell motility, and secretion are expressed in biofilms. Of particular importance to the electron-conducting biofilms are proteins associated with secretion systems of Type I, II, V and Type IV pili. Furthermore, enzymes involved in lipopolysaccharide and peptidoglycan biosynthesis show increased levels of expression in electron-conducting biofilms compared with planktonic cells. These observations point to similarities in long-range electron-transfer mechanisms between <i>G. sulfurreducens</i> and <i>Shewanella oneidensis</i> while highlighting the wider significance of secretion systems beyond that of Type IV pili identified to date in the adaptation of <i>G. sulfurreducens</i> to electrode respiration

H2A.Z maps to Hox loci in wild-type and PRC1 mutant ESCs.

<p>Log2 of ChIP:input for: H2A.Z, H3K27me3, EZH2 and Ring1B from WT (+/+) (top) and <i>Ring1B^−/−</i> (bottom) ESCs using a custom tiling microarray. Data is shown for the four paralogous murine hox loci (Hoxa, Hoxb, Hoxc and Hoxd) and their flanking genomic regions. The data represent a mean of 2 biological replicates. RefSeq gene annotations and CGIs are from the July 2007 (mm9) Build 37 assembly of the mouse genome (genome.ucsc.edu).</p

H2A.Z enrichment is not dependent on PRC2.

<p>A) Immunoblots for H3K27me3 and H3 in <i>Eed^−/−</i> and matched WT ESCs B) Immunoblots for H2A.Z and H2A in <i>Eed^−/−</i> and matched WT ESCs. C) ChIP for control IgG or H2A.Z at the promoters of <i>Hoxb1, Hoxb13, Gata4, Pou5f1</i> and <i>Nanog,</i> assayed by qRT-PCR, in WT (grey) or <i>Eed^−/−</i> (black) ESCs. Enrichment is shown as mean % input bound ± s.e.m. over three biological replicates. IgG is shown in white bars. D) Immunoblots for H3K27me3 and H3 in <i>Suz12^−/−</i> and WT (<i>Eed^+/+)</i> ESCs E) Immunoblots for H2A.Z and H2A in <i>Suz12^−/−</i> and WT (<i>Eed^+/+)</i> ESCs. F) ChIP for control IgG or H2A.Z at the promoters of <i>Hoxb1, Hoxb13, Hoxd10, Gata4, Cdx2, Pou5f1</i> and <i>Nanog,</i> assayed by qRT-PCR, in WT (grey) or <i>Suz12^−/−</i> (black) ESCs. Enrichment is shown as mean % input bound ± s.e.m. over three biological replicates. IgG is shown in white bars.</p

H2A.Z occupancy is not affected at Hox loci in PRC2 mutant ESCs.

<p>Log2 of ChIP: input for: H2A.Z from WT (+/+) (top) and <i>Eed^−/−</i> (mid) and <i>Suz12^−/−</i> (bottom) ESCs using a custom tiling microarray. Data is shown for the four paralogous murine hox loci (Hoxa, Hoxb, Hoxc and Hoxd) and their flanking genomic regions. The data represent a mean of 2 biological replicates, (3 technical replicates). RefSeq gene annotations and CGIs are from the July 2007 (mm9) Build 37 assembly of the mouse genome (genome.ucsc.edu).</p

H2A.Z is enriched at developmental genes in wild-type and PRC1 mutant ESCs.

<p>Log2 of ChIP:input for: H2A.Z, H3K27me3, EZH2 and Ring1B from WT (+/+) (top) and <i>Ring1B^−/−</i> (bottom) ESCs using a custom tiling microarray. Data is shown for selected polycomb target genes (<i>Pax6, Nkx2-9</i> and <i>Cdx2</i>), active genes (<i>Actb, Nanog</i> and <i>Tex19.1</i>) and silent genes (β-globin locus and <i>Magea3</i>). The data represent a mean of 2 biological replicates. RefSeq gene annotations and CGIs are from the July 2007 (mm9) Build 37 assembly of the mouse genome (genome.ucsc.edu).</p

H2A.Z localises to CpG islands and overlap with EZH2 and Ring1B.

<p>A) Venn diagram showing overlap of genes displaying H2A.Z with EZH2 and Ring1B enrichment at TSS ± 500 bp within arrayed regions (total 240 unique TSS) in WT ESCs. B) Box plots showing Log2 H2A.Z ChIP/Input of over TSSs (±250 bp), CpG islands (CGI), exons, introns and transcription end sites (TES ± 250 bp) across all probes or Hox loci in WT ESCs. C) As in (E) but for EZH2, H3K27me3 and Ring1B.</p

Identification of Ring1B associated peptides in mouse ESCs.

<p>A) IPs of Ring1B from nuclear extracts of WT and <i>Ring1B^−/−</i> cells rescued with Ring1BI53A, resolved by 4–20% SDS-PAGE and stained with colloidal blue. Proteins that had a significant number of detected peptides by mass spectrometry analysis are listed. Peptides also detected in the control IgG lane were subtracted. Asterisks indicate the heavy and light Ig chains. B) IP of Ring1B from nuclear extracts of WT and <i>Ring1B^−/−</i> cells rescued with full length Ring1B or Ring1BI53A resolved by 12% SDS-PAGE and immunoblotted with α-Dmap1. C) Immunoblot of p400 IP from WT and <i>Ring1B^−/−</i> ESCs using p400 and Ring1B antibodies. D) IP of endogenous p400 from nuclear extracts of WT ESCs resolved by 4–20% SDS PAGE. Polypeptides stained by colloidal blue were identified by mass spectrometry. Listed are proteins with significant number of peptide hits. E) Size exclusion chromatography of nuclear extract from WT ESCs. Every other fraction (50%) were resolved by 4–15% SDS-PAGE and immunoblotted with anti-p400, anti-Dmap1, anti-Mll2, anti-Menin, anti-Ring1B, anti-Rybp, anti-Ezh2 and anti-Suz12. The upper panel represent fraction number, Input (In), black triangles indicate the retention of molecular weight standards in mega Dalton (MDa) or kilo Dalton (kDa).</p

H2A.Z distribution at polycomb targets in the absence of Ring1B.

<p>A) Immunoblot for H2A.Z and H2A in <i>Ring1B^−/−</i> and matched WT (Ring1B^+/+) ESCs. B) ChIP for H2A.Z at the promoters of <i>Hoxb1, Hoxb13, Hoxd10, Cdx2, Pou5f1</i> and <i>Nanog,</i> assayed by qRT-PCR, in WT (<i>+/+</i>) (grey) or <i>Ring1B^−/−</i> cells (black). Enrichment is shown as mean % input bound ± SD over two biological replicates (6 technical replicates). IgG is shown in white bars with grey or black borders ± SD. C) Average expression signals of active, silent and polycomb target genes in WT (+/+) (grey) and Ring1B<i>^−/−</i> (black) from four biological replicates hybridized to MouseWG-6 v2.0 Expression BeadChips ± s.e.m.</p

Table_1.DOCX

<p>Harvesting valuable bioproducts from various renewable feedstocks is necessary for the critical development of a sustainable bioeconomy. Anaerobic digestion is a well-established technology for the conversion of wastewater and solid feedstocks to energy with the additional potential for production of process intermediates of high market values (e.g., carboxylates). In recent years, first-generation biofuels typically derived from food crops have been widely utilized as a renewable source of energy. The environmental and socioeconomic limitations of such strategy, however, have led to the development of second-generation biofuels utilizing, amongst other feedstocks, lignocellulosic biomass. In this context, the anaerobic digestion of perennial grass holds great promise for the conversion of sustainable renewable feedstock to energy and other process intermediates. The advancement of this technology however, and its implementation for industrial applications, relies on a greater understanding of the microbiome underpinning the process. To this end, microbial communities recovered from replicated anaerobic bioreactors digesting grass were analyzed. The bioreactors leachates were not buffered and acidic pH (between 5.5 and 6.3) prevailed at the time of sampling as a result of microbial activities. Community composition and transcriptionally active taxa were examined using 16S rRNA sequencing and microbial functions were investigated using metaproteomics. Bioreactor fraction, i.e., grass or leachate, was found to be the main discriminator of community analysis across the three molecular level of investigation (DNA, RNA, and proteins). Six taxa, namely Bacteroidia, Betaproteobacteria, Clostridia, Gammaproteobacteria, Methanomicrobia, and Negativicutes accounted for the large majority of the three datasets. The initial stages of grass hydrolysis were carried out by Bacteroidia, Gammaproteobacteria, and Negativicutes in the grass biofilms, in addition to Clostridia in the bioreactor leachates. Numerous glycolytic enzymes and carbohydrate transporters were detected throughout the bioreactors in addition to proteins involved in butanol and lactate production. Finally, evidence of the prevalence of stressful conditions within the bioreactors and particularly impacting Clostridia was observed in the metaproteomes. Taken together, this study highlights the functional importance of Clostridia during the anaerobic digestion of grass and thus research avenues allowing members of this taxon to thrive should be explored.</p

Table_2.DOC

<p>Harvesting valuable bioproducts from various renewable feedstocks is necessary for the critical development of a sustainable bioeconomy. Anaerobic digestion is a well-established technology for the conversion of wastewater and solid feedstocks to energy with the additional potential for production of process intermediates of high market values (e.g., carboxylates). In recent years, first-generation biofuels typically derived from food crops have been widely utilized as a renewable source of energy. The environmental and socioeconomic limitations of such strategy, however, have led to the development of second-generation biofuels utilizing, amongst other feedstocks, lignocellulosic biomass. In this context, the anaerobic digestion of perennial grass holds great promise for the conversion of sustainable renewable feedstock to energy and other process intermediates. The advancement of this technology however, and its implementation for industrial applications, relies on a greater understanding of the microbiome underpinning the process. To this end, microbial communities recovered from replicated anaerobic bioreactors digesting grass were analyzed. The bioreactors leachates were not buffered and acidic pH (between 5.5 and 6.3) prevailed at the time of sampling as a result of microbial activities. Community composition and transcriptionally active taxa were examined using 16S rRNA sequencing and microbial functions were investigated using metaproteomics. Bioreactor fraction, i.e., grass or leachate, was found to be the main discriminator of community analysis across the three molecular level of investigation (DNA, RNA, and proteins). Six taxa, namely Bacteroidia, Betaproteobacteria, Clostridia, Gammaproteobacteria, Methanomicrobia, and Negativicutes accounted for the large majority of the three datasets. The initial stages of grass hydrolysis were carried out by Bacteroidia, Gammaproteobacteria, and Negativicutes in the grass biofilms, in addition to Clostridia in the bioreactor leachates. Numerous glycolytic enzymes and carbohydrate transporters were detected throughout the bioreactors in addition to proteins involved in butanol and lactate production. Finally, evidence of the prevalence of stressful conditions within the bioreactors and particularly impacting Clostridia was observed in the metaproteomes. Taken together, this study highlights the functional importance of Clostridia during the anaerobic digestion of grass and thus research avenues allowing members of this taxon to thrive should be explored.</p