CO2 exposure at pressure impacts metabolism and stress responses in the model sulfate-reducing bacterium Desulfovibrio vulgaris strain Hildenborough.

Geologic carbon dioxide (CO2) sequestration drives physical and geochemical changes in deep subsurface environments that impact indigenous microbial activities. The combined effects of pressurized CO2 on a model sulfate-reducing microorganism, Desulfovibrio vulgaris, have been assessed using a suite of genomic and kinetic measurements. Novel high-pressure NMR time-series measurements using (13)C-lactate were used to track D. vulgaris metabolism. We identified cessation of respiration at CO2 pressures of 10 bar, 25 bar, 50 bar, and 80 bar. Concurrent experiments using N2 as the pressurizing phase had no negative effect on microbial respiration, as inferred from reduction of sulfate to sulfide. Complementary pressurized batch incubations and fluorescence microscopy measurements supported NMR observations, and indicated that non-respiring cells were mostly viable at 50 bar CO2 for at least 4 h, and at 80 bar CO2 for 2 h. The fraction of dead cells increased rapidly after 4 h at 80 bar CO2. Transcriptomic (RNA-Seq) measurements on mRNA transcripts from CO2-incubated biomass indicated that cells up-regulated the production of certain amino acids (leucine, isoleucine) following CO2 exposure at elevated pressures, likely as part of a general stress response. Evidence for other poorly understood stress responses were also identified within RNA-Seq data, suggesting that while pressurized CO2 severely limits the growth and respiration of D. vulgaris cells, biomass retains intact cell membranes at pressures up to 80 bar CO2. Together, these data show that geologic sequestration of CO2 may have significant impacts on rates of sulfate reduction in many deep subsurface environments where this metabolism is a key respiratory process.

Inference of interactions in cyanobacterial-heterotrophic co-cultures via transcriptome sequencing.

We used deep sequencing technology to identify transcriptional adaptation of the euryhaline unicellular cyanobacterium Synechococcus sp. PCC 7002 and the marine facultative aerobe Shewanella putrefaciens W3-18-1 to growth in a co-culture and infer the effect of carbon flux distributions on photoautotroph-heterotroph interactions. The overall transcriptome response of both organisms to co-cultivation was shaped by their respective physiologies and growth constraints. Carbon limitation resulted in the expansion of metabolic capacities, which was manifested through the transcriptional upregulation of transport and catabolic pathways. Although growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. These hypothesized interactions were inferred from the excretion of specific amino acids (for example, alanine and methionine) by the cyanobacterium, which correlated with the downregulation of the corresponding biosynthetic machinery in Shewanella W3-18-1. In addition, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation may indicate increased Fe availability as well as more facile and energy-efficient mechanisms for Fe acquisition by the cyanobacterium. Furthermore, evidence pointed at potentially novel interactions between oxygenic photoautotrophs and heterotrophs related to the oxidative stress response as transcriptional patterns suggested that Synechococcus 7002 rather than Shewanella W3-18-1 provided scavenging functions for reactive oxygen species under co-culture conditions. This study provides an initial insight into the complexity of photoautotrophic-heterotrophic interactions and brings new perspectives of their role in the robustness and stability of the association.

Changes in translational efficiency is a dominant regulatory mechanism in the environmental response of bacteria.

To understand how cell physiological state affects mRNA translation, we used Shewanella oneidensis MR-1 grown under steady state conditions at either 20% or 8.5% O2. Using a combination of quantitative proteomics and RNA-Seq, we generated high-confidence data on >1000 mRNA and protein pairs. By using a steady state model, we found that differences in protein-mRNA ratios were primarily due to differences in the translational efficiency of specific genes. When oxygen levels were lowered, 28% of the proteins showed at least a 2-fold change in expression. Transcription levels were sp. significantly altered for 26% of the protein changes; translational efficiency was significantly altered for 46% and a combination of both was responsible for the remaining 28%. Changes in translational efficiency were significantly correlated with the codon usage pattern of the genes and measurable tRNA pools changed in response to altered O2 levels. Our results suggest that changes in the translational efficiency of proteins, in part due to altered tRNA pools, is a major determinant of regulated alterations in protein expression levels in bacteria.

Improving RNA-Seq Precision with MapAl.

With currently available RNA-Seq pipelines, expression estimates for most genes are very noisy. We here introduce MapAl, a tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. In the post-processing of RNA-Seq reads, it incorporates gene models already at the stage of read alignment, increasing the number of reliably measured known transcripts consistently by 50%. Adding genes identified de novo then allows a reliable assessment of double the total number of transcripts compared to other available pipelines. This substantial improvement is of general relevance: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not.

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

MOTIVATION: Measurement precision determines the power of any analysis to reliably identify significant signals, such as in screens for differential expression, independent of whether the experimental design incorporates replicates or not. With the compilation of large-scale RNA-Seq datasets with technical replicate samples, however, we can now, for the first time, perform a systematic analysis of the precision of expression level estimates from massively parallel sequencing technology. This then allows considerations for its improvement by computational or experimental means. RESULTS: We report on a comprehensive study of target identification and measurement precision, including their dependence on transcript expression levels, read depth and other parameters. In particular, an impressive recall of 84% of the estimated true transcript population could be achieved with 331 million 50 bp reads, with diminishing returns from longer read lengths and even less gains from increased sequencing depths. Most of the measurement power (75%) is spent on only 7% of the known transcriptome, however, making less strongly expressed transcripts harder to measure. Consequently, <30% of all transcripts could be quantified reliably with a relative error<20%. Based on established tools, we then introduce a new approach for mapping and analysing sequencing reads that yields substantially improved performance in gene expression profiling, increasing the number of transcripts that can reliably be quantified to over 40%. Extrapolations to higher sequencing depths highlight the need for efficient complementary steps. In discussion we outline possible experimental and computational strategies for further improvements in quantification precision. CONTACT: rnaseq10@boku.ac.at

Translating the histone code into leukemia.

The "histone code" is comprised of the covalent modifications of histone tails that function to regulate gene transcription. The post-translational modifications that occur in histones within the regulatory regions of genes include acetylation, methylation, phosphorylation, ubiquitination, sumoylation, and ADP-ribosylation. These modifications serve to alter chromatin structure and accessibility, and to act as docking sites for transcription factors or other histone modifying enzymes. Several of the factors that are disrupted by chromosomal translocations associated with hematological malignancies can alter the histone code in a gene-specific manner. Here, we discuss how the histone code may be disrupted by chromosomal translocations, either directly by altering the activity of histone modifying enzymes, or indirectly by recruitment of this type of enzyme by oncogenic transcription factors. These alterations in the histone code may alter gene expression pattern to set the stage for leukemogenesis.