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ABSTRACT: Sequence reads of bacteria community associated with Hydrogen and VFAs production

PROVIDER: PRJNA533127 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8914805_1.fastq.gz	Fastqsanger.gz
	SRR8914805_2.fastq.gz	Fastqsanger.gz
	SRR8914806_1.fastq.gz	Fastqsanger.gz
	SRR8914806_2.fastq.gz	Fastqsanger.gz
	SRR8914807_1.fastq.gz	Fastqsanger.gz

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Project description:Purpose: Compare the transcriptomes of T. paralvinellae using RNA-Seq gene expression analyses to understand the physiology of this organism when it is grown on different carbon sources, under optimal and hydrogen stress conditions. Methods: T. paralvinellae was grown in triplicate at with either 0.5% maltose or 0.5% tryptone to investigate its catabolic pathways when grown on a sugar and peptides, respectively. It was also grown on 1% formate to determine the effect of formate on cell growth, metabolite production, and gene expression. It was also grown separately on maltose or tryptone media as before, except with hydrogen in the media to examine the effects of hydrogen inhibition. The cells remaining in the 2-liter bioreactor were concentrated by centrifugation. The resulting cell pellets were resuspended in TRIzol (Invitrogen) and total RNA was extracted using a Direct-zol RNA extraction kit (Zymo). RNA quantity was determined with Qubit fluorometry. RNA integrity was checked by a bioanalyzer and a Nanodrop spectrometer. Genewiz sequencing facilities performed rRNA removal, library construction, multiplexing and sequence the RNA with HiSeq2500, 2×100 Paired-End. We aligned the RNAseq reads to T. paralvinellae genome (STAR) and assigned aligned sequence reads to genomic features (featureCounts). We then quantified transcriptome and reported pairwise significant genes that are differentially expressed by DESeq available under Bioconductor (www.bioconductor.org) on Galaxy platform and in R. Results: Sequencing depths ranged from 29,974,378 to 45,240,342 sequences, with a mean of 38,990,002 and a median of 38,951,352 reads per sample. Of 2,138 genes annotated in the T. paralvinellae genome, 2084 transcripts were detected by RNA-Seq.Of the 2084 genes detected by transcriptomics, hydrogen stress caused only 48 genes to be differentially regulated (log2FC > 1, P < 0.05) with maltose and tryptone carbon sources. These included mostly genes associated with formate-dependent metabolism and transporters. The upregulated genes upon growth under H2 stress conditions indicate intrinsic formate production via formate hydrogen lyase and format secretion.

Project description:Photosynthetic microbes can produce the clean-burning fuel hydrogen using one of natureâ??s most plentiful resources, sunlight 1,2. Anoxygenic photosynthetic bacteria generate hydrogen and ammonia during a process known as biological nitrogen fixation. This reaction is catalyzed by the enzyme nitrogenase and consumes nitrogen gas, ATP and electrons 3. One bacterium, Rhodopseudomonas palustris, has a remarkable ability to obtain electrons from green plant-derived material 4,5 and to efficiently absorb both high and low intensity light energy to form ATP 6. Manipulating R. palustris or a similar organism to produce hydrogen commercially will require us to identify all its genes that contribute to hydrogen production and to understand how this process is regulated in cells. Here we describe mutant strains in which metabolism is redirected such that hydrogen production is uncoupled from nitrogen fixation. Our data indicate that three different single amino acid changes in the transcriptional regulator NifA each yielded strains that produced hydrogen even in the presence of the repressing nitrogen source ammonium and in the absence of specific inducing metabolic signals. We used the mutants to show that, in addition to nitrogenase genes, 18 genes outside of the nitrogenase gene cluster may contribute to hydrogen production. Some of these genes are likely involved in efficient ATP acquisition and in channeling electrons to nitrogenase for reduction of protons to molecular hydrogen. Our results demonstrate that photosynthetic bacteria can be genetically manipulated for sustained production of pure hydrogen in a variety of cultivation conditions in the absence of oxygen, nitrogen or other gases as long as light and an electron donor are supplied. Transcriptome profile of wild type (CGA009) growing photosynthetically in the presence of amonium an acetate was compare with that of 4 different mutants (CGA570, CGA571, CGA572 and CGA574). We did 2 biological replicates per strain.

Project description:Background: Microalgae can make a significant contribution towards meeting global renewable energy needs in both lipid-based liquid biofuel and hydrogen biofuel. The development of energy-related products and chemicals from algae could be accelerated with improvements in systems biology tools, and recent advances in sequencing technology provide a platform for enhanced transcriptomic analyses. However, these techniques are still heavily reliant upon available genomic sequence data. We have developed a de novo sequencing, annotation, and quantitation pipeline that can be applied to unsequenced organisms for effective quantitative gene expression profiling. Chlamydomonas moewusii is a unicellular green alga capable of evolving molecular hydrogen (H2) under both dark and light anaerobic conditions, and has high hydrogenase activity that can be rapidly induced. However, to date, there is no systematic investigation of transcriptomic profiling during induction of hydrogen photoproduction in this organism. Results: In this work, we measured rates of hydrogen production and extracted RNA from samples of C. moewusii following various lengths of dark anaerobic incubation. RNA-Seq was applied to investigate transcriptomic profiles during the dark anaerobic induction of hydrogen photoproduction. One hundred fifty six million reads generated from seven samples were then used for de novo assembly after data trimming. The BlastX results against NCBI database and Blast2GO results were used to interpret the functions of the assembled 39,136 contigs, which were then used as the reference transcripts for RNA-Seq analysis. Nearly 98% transcripts had Blast hits, although more than one-third were annotated as hypothetical proteins. The expression value of RNA-Seq results was imported into statistical software for data quality control, normalization, and subsequent statistical analyses such as One-way ANOVA and K-means Clustering. Our results indicated that more transcripts were differentially expressed during the period of early and higher hydrogen photoproduction, and fewer transcripts were differentially expressed when rates of hydrogen photoproduction decreased. Conclusions: Herein, we have described a workflow to analyze RNA-Seq data without reference genome sequence information, which can be applied to the rapid development of other unsequenced microorganisms (both prokaryotic and eukaryotic) with the potential for development as fuel production strains. This study provided the first transcriptomic RNA-Seq dataset, as well as biological insights into the metabolic changes that occur concomitant with induction of hydrogen photoevolution in C. moewusii, which can help further development of this organism as a hydrogen photoproduction strain. Examine time course gene differential expression post anaerobic induction for hydrogen production

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