Engineering topics

Linggi, Bryan E.

Publications and source records attributed to Linggi, Bryan E..

7 records

DOE OSTI2014

DNA Methylation as a Biomarker for Preeclampsia

Background: Preeclampsia contributes significantly to pregnancy-associated morbidity and mortality as well as future risk of cardiovascular disease in mother and offspring, and preeclampsia in offspring. The lack of reliable methods for early detection limits the opportunities for prevention, diagnosis, and timely treatment. Purpose: The purpose of this study was to explore distinct DNA methylation patterns associated with preeclampsia in both maternal cells and fetal-derived tissue that represent potential biomarkers to predict future preeclampsia and inheritance in children. Method: A convenience sample of nulliparous women (N = 55) in the first trimester of pregnancy was recruited for this prospective study. Genome-wide DNA methylation was quantified in first-trimester maternal peripheral white blood cells and placental chorionic tissue from normotensive women and those with preeclampsia (n = 6/group). Results: Late-onset preeclampsia developed in 12.7% of women. Significant differences in DNA methylation were identified in 207 individual linked cytosine and guanine (CpG) sites in maternal white blood cells collected in the first trimester (132 sites with gain and 75 sites with loss of methylation), which were common to approximately 75% of the differentially methylated CpG sites identified in chorionic tissue of fetal origin. Conclusion: This study is the first to identify maternal epigenetic targets and common targets in fetal-derived tissue that represent putative biomarkers for early detection and heritable risk of preeclampsia. Findings may pave the way for diagnosis of preeclampsia prior to its clinical presentation and acute damaging effects, and the potential for prevention of the detrimental long-term sequelae.

biomarker↗

DOE OSTI2014

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 13C-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 four hours, and at 80 bar CO2 for two hours. The fraction of dead cells increased rapidly after four hours 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.

Desulfovibrio↗

DOE OSTI2014

Inference of Interactions in Cyanobacterial-Heterotrophic Co-Cultures via Transcriptome Sequencing

We employed 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. While growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. On one hand, the production and excretion of specific amino acids (methionine and alanine) by the cyanobacterium correlated with the putative downregulation of the corresponding biosynthetic machinery of Shewanella W3-18-1. On the other hand, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation suggested 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.

cyanobacterium↗

DOE OSTI2013

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 aerobic or suboxic conditions. 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 caused by 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. Altered transcription levels appeared responsible for 26% of the protein changes, altered translational efficiency appeared responsible for 46% and a combination of both were 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 caused by altered tRNA pools, is a major determinant of regulated protein expression in bacteria.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2013

Coregulation of terpenoid pathway genes and prediction of isoprene production in Bacillus subtilis using transcriptomics

The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding the system level regulation and control of the pathway. To address this limitation, we examined Bacillus subtilis grown under multiple conditions and then determined the relationship between altered isoprene production and the pattern of gene expression. We found that terpenoid genes appeared to fall into two distinct subsets with opposing correlations with respect to the amount of isoprene produced. The group whose expression levels positively correlated with isoprene production included dxs, the gene responsible for the commitment step in the pathway, as well as ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. This analysis showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model which accurately predicts production of this secondary metabolite across many simulated environmental conditions.

Bacillus subtilis↗

DOE OSTI2013

EMSL Research Campaigns: Status Report on the Development of Research Campaigns

Research campaigns were conceived as a means to focus EMSL research on specific scientific questions. Campaign will help fulfill the Environmental Molecular Sciences Laboratory (EMSL) strategic vision to develop and integrate, for use by the scientific community, world leading capabilities that transform understanding in the environmental molecular sciences and accelerate discoveries relevant to the Department of Energy’s (DOE’s) missions. Campaigns are multi-institutional multi-disciplinary projects with scope beyond those of normal EMSL user projects. The goal of research campaigns is to have EMSL scientists and users team on the projects in the effort to accelerate progress and increase impact in specific scientific areas by focusing user research, EMSL resources, and expertise in those areas. This report will give a history and update on the progress of those campaigns.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2012

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.

59 BASIC BIOLOGICAL SCIENCES↗