Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Gene expression”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Catabolism and interactions of uncultured organisms shaped by eco-thermodynamics in methanogenic bioprocesses

We currently understand the carbon cycle in methanogenic environments as trophic interactions revolving around interspecies H 2 transfer between organotrophs and methanogens. However, many H 2 -generating processes are thermodynamically sensitive to H 2 accumulation and can be inhibited by high H 2 concentrations produced by other metabolisms. To uncover how anaerobes combat this H 2 conflict in situ, we employ metagenomics and metatranscriptomics to revisit a model ecosystem that has inspired many foundational discoveries in anaerobic ecology – methanogenic bioreactors. Through analysis of 15 anaerobic digesters, we recover 1343 high-quality metagenome-assembled genomes (MAGs) and corresponding gene expression profiles for diverse uncultured lineages spanning 66 phyla and reconstruct their individual metabolic capacities. We discover that diverse uncultured organotrophic populations can drive H 2 -sensitive degradation through (i) metabolic coupling with concurrent H 2 -tolerant catabolism, (ii) unprecedented shifts from H 2 generation to CO 2 -reducing formate transfer and cytochrome/pili-mediated direct interspecies electron transfer for avoiding thermodynamic conflict, and (iii) integration of low-concentration O 2 as an ancillary thermodynamics-enhancing electron sink. Archaeal populations in situ support the above processes through novel metabolisms distinct from conventional methanogenesis – high-affinity H 2 oxidation driven by methyl-reducing methanogenesis and concomitant uptake of formate, electrons, and acetate from HS metabolism by Methanothrix. In total, synthesis of omics analyses and eco-thermodynamics reveals overlooked metabolic behavior and interactions of uncultured organisms that address a central issue in methanogenic carbon cycling, thermodynamic conflict among diverse concurrent metabolic processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Low-abundance populations distinguish microbiome performance in plant cell wall deconstruction

Abstract Background Plant cell walls are interwoven structures recalcitrant to degradation. Native and adapted microbiomes can be particularly effective at plant cell wall deconstruction. Although most understanding of biological cell wall deconstruction has been obtained from isolates, cultivated microbiomes that break down cell walls have emerged as new sources for biotechnologically relevant microbes and enzymes. These microbiomes provide a unique resource to identify key interacting functional microbial groups and to guide the design of specialized synthetic microbial communities. Results To establish a system assessing comparative microbiome performance, parallel microbiomes were cultivated on sorghum ( Sorghum bicolor L. Moench) from compost inocula. Biomass loss and biochemical assays indicated that these microbiomes diverged in their ability to deconstruct biomass. Network reconstructions from gene expression dynamics identified key groups and potential interactions within the adapted sorghum-degrading communities, including Actinotalea , Filomicrobium , and Gemmatimonadetes populations. Functional analysis demonstrated that the microbiomes proceeded through successive stages that are linked to enzymes that deconstruct plant cell wall polymers. The combination of network and functional analysis highlighted the importance of cellulose-degrading Actinobacteria in differentiating the performance of these microbiomes. Conclusions The two-tier cultivation of compost-derived microbiomes on sorghum led to the establishment of microbiomes for which community structure and performance could be assessed. The work reinforces the observation that subtle differences in community composition and the genomic content of strains may lead to significant differences in community performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Single-nuclei transcriptome analysis of the shoot apex vascular system differentiation in Populus

ABSTRACT Differentiation of stem cells in the plant apex gives rise to aerial tissues and organs. Presently, we lack a lineage map of the shoot apex cells in woody perennials – a crucial gap considering their role in determining primary and secondary growth. Here, we used single-nuclei RNA-sequencing to determine cell type-specific transcriptomes of the Populus vegetative shoot apex. We identified highly heterogeneous cell populations clustered into seven broad groups represented by 18 transcriptionally distinct cell clusters. Next, we established the developmental trajectories of the epidermis, leaf mesophyll and vascular tissue. Motivated by the high similarities between Populus and Arabidopsis cell population in the vegetative apex, we applied a pipeline for interspecific single-cell gene expression data integration. We contrasted the developmental trajectories of primary phloem and xylem formation in both species, establishing the first comparison of vascular development between a model annual herbaceous and a woody perennial plant species. Our results offer a valuable resource for investigating the principles underlying cell division and differentiation conserved between herbaceous and perennial species while also allowing us to examine species-specific differences at single-cell resolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Organogenetic transcriptomes of the Drosophila embryo at single cell resolution

To gain insight into the transcription programs activated during the formation of Drosophila larval structures, we carried out single cell RNA sequencing during two periods of Drosophila embryogenesis: stages 10-12, when most organs are first specified and initiate morphological and physiological specialization; and stages 13-16, when organs achieve their final mature architectures and begin to function. Our data confirm previous findings with regards to functional specialization of some organs – the salivary gland and trachea – and clarify the embryonic functions of another – the plasmatocytes. We also identify two early developmental trajectories in germ cells and uncover a potential role for proteolysis during germline stem cell specialization. We identify the likely cell type of origin for key components of the Drosophila matrisome and several commonly used Drosophila embryonic cell culture lines. Finally, we compare our findings with other recent related studies and with other modalities for identifying tissue-specific gene expression patterns. These data provide a useful community resource for identifying many new players in tissue-specific morphogenesis and functional specialization of developing organs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data for Integrating Transcriptomic and Metabolomic Analysis of the Oleaginous Yeast Rhodosporidium toruloides IFO0880 During Growth under Different Carbon Sources

Rhodosporidium toruloides is an oleaginous yeast capable of producing a variety of biofuels and bioproducts from diverse carbon sources. Despite numerous studies showing its promise as a platform microorganism, little is known about its metabolism and physiology. In this work, we investigated the central carbon metabolism in R. toruloides IFO0880 using transcriptomics and metabolomics during growth on glucose, xylose, acetate, or soybean oil. These substrates were chosen because they can be derived from plants. Significant changes in gene expression and metabolite concentrations were observed during growth on these four substrates. We mapped these changes onto the governing metabolic pathways to better understand how R. toruloides reprograms its metabolism to enable growth on these substrates. One notable finding concerns xylose metabolism, where poor expression of xylulokinase induces a bypass leading to arabitol production. Collectively, these results further our understanding of central carbon metabolism in R. toruloides during growth on different substrates. They may also help guide the metabolic engineering and development of better models of metabolism for R. toruloides .

Conversion↗
DOE OSTI2021

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E . coli . Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E . coli lifestyles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Biophysical and X-ray structural studies of the (GGGTT)3GGG G-quadruplex in complex with N-methyl mesoporphyrin IX

The G-quadruplex (GQ) is a well-studied non-canonical DNA structure formed by G-rich sequences found at telomeres and gene promoters. Biological studies suggest that GQs may play roles in regulating gene expression, DNA replication, and DNA repair. Small molecule ligands were shown to alter GQ structure and stability and thereby serve as novel therapies, particularly against cancer. In this work, we investigate the interaction of a G-rich sequence, 5’-GGGTTGGGTTGGGTTGGG-3’ (T1), with a water-soluble porphyrin, N- methyl mesoporphyrin IX (NMM) via biophysical and X-ray crystallographic studies. UV-vis and fluorescence titrations, as well as a Job plot, revealed a 1:1 binding stoichiometry with an impressively tight binding constant of 30–50 μM -1 and ΔG 298 of -10.3 kcal/mol. Eight extended variants of T1 (named T2 –T9) were fully characterized and T7 was identified as a suitable candidate for crystallographic studies. We solved the crystal structures of the T1- and T7-NMM complexes at 2.39 and 2.34 Å resolution, respectively. Both complexes form a 5’-5’ dimer of parallel GQs capped by NMM at the 3’ G-quartet, supporting the 1:1 binding stoichiometry. Our work provides invaluable details about GQ-ligand binding interactions and informs the design of novel anticancer drugs that selectively recognize specific GQs and modulate their stability for therapeutic purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus

Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover key regulatory elements that determine cell fate during developmental programs. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell wall structure, Populus shoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor’s sensitivity (EC 50 ) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC 50 . Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

CovS inactivation reduces CovR promoter binding at diverse virulence factor encoding genes in group A Streptococcus

The control of virulence gene regulator (CovR), also called caspsule synthesis regulator (CsrR), is critical to how the major human pathogen group A Streptococcus fine-tunes virulence factor production. CovR phosphorylation (CovR~P) levels are determined by its cognate sensor kinase CovS, and functional abrogating mutations in CovS can occur in invasive GAS isolates leading to hypervirulence. Presently, the mechanism of CovR-DNA binding specificity is unclear, and the impact of CovS inactivation on global CovR binding has not been assessed. Thus, we performed CovR chromatin immunoprecipitation sequencing (ChIP-seq) analysis in the emm1 strain MGAS2221 and its CovS kinase deficient derivative strain 2221-CovS-E281A. We identified that CovR bound in the promoter regions of nearly all virulence factor encoding genes in the CovR regulon. Additionally, direct CovR binding was observed for numerous genes encoding proteins involved in amino acid metabolism, but we found limited direct CovR binding to genes encoding other transcriptional regulators. The consensus sequence AATRANAAAARVABTAAA was present in the promoters of genes directly regulated by CovR, and mutations of highly conserved positions within this motif relieved CovR repression of the hasA and MGAS2221_0187 promoters. Analysis of strain 2221-CovS-E281A revealed that binding of CovR at repressed, but not activated, promoters is highly dependent on CovR~P state. CovR repressed virulence factor encoding genes could be grouped dependent on how CovR~P dependent variation in DNA binding correlated with gene transcript levels. Taken together, the data show that CovR repression of virulence factor encoding genes is primarily direct in nature, involves binding to a newly-identified DNA binding motif, and is relieved by CovS inactivation. These data provide new mechanistic insights into one of the most important bacterial virulence regulators and allow for subsequent focused investigations into how CovR-DNA interaction at directly controlled promoters impacts GAS pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluation of an in vitro three-dimensional HepaRG spheroid model for genotoxicity testing using the high-throughput CometChip platform

Three-dimensional (3D) culture systems are increasingly being used for genotoxicity studies due to improved cell-to-cell interactions and tissue-like structures that are limited or lacking in 2D cultures. The present study optimized a 3D culture system using metabolically competent HepaRG cells for in vitro genotoxicity testing. 3D HepaRG spheroids, formed in 96- or 384-well ultra-low attachment plates, were exposed to various concentrations of 34 test articles, including 8 direct-acting and 11 indirect-acting genotoxicants/carcinogens as well as 15 compounds that show different genotoxic responses in vitro and in vivo. DNA damage was evaluated using the high-throughput CometChip assay with concurrent cytotoxicity assessment by the ATP assay in both 2D and 3D cultures. 3D HepaRG spheroids maintained a stable phenotype for up to 30 days with higher levels of albumin secretion, cytochrome P450 gene expression, and enzyme activities compared to 2D cultures. 3D spheroids also demonstrated a higher sensitivity than 2D cultures for detecting both direct- and indirect-acting genotoxicants/carcinogens, indicating a better prediction of in vivo genotoxicity responses. When DNA damage dose-response data were quantified using PROAST software, 3D spheroids generally had lower or similar benchmark dose values compared to 2D HepaRG cells and were more comparable with primary human hepatocytes. These results demonstrate that 3D models can be adapted to the CometChip technology for high-throughput genotoxicity testing and that 3D HepaRG spheroids may be used as a reliable and pragmatic in vitro approach to better support the hazard identification and risk assessment of potential human genotoxic carcinogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Exogenous erythropoietin increases hematological status, fat oxidation, and aerobic performance in males following prolonged strenuous training

Abstract This study investigated the effects of EPO on hemoglobin (Hgb) and hematocrit (Hct), time trial (TT) performance, substrate oxidation, and skeletal muscle phenotype throughout 28 days of strenuous exercise. Eight males completed this longitudinal controlled exercise and feeding study using EPO (50 IU/kg body mass) 3×/week for 28 days. Hgb, Hct, and TT performance were assessed PRE and on Days 7, 14, 21, and 27 of EPO. Rested/fasted muscle obtained PRE and POST EPO were analyzed for gene expression, protein signaling, fiber type, and capillarization. Substrate oxidation and glucose turnover were assessed during 90‐min of treadmill load carriage (LC; 30% body mass; 55 ± 5% V̇O 2 peak) exercise using indirect calorimetry, and 6‐6‐[ 2 H 2 ]‐glucose PRE and POST. Hgb and Hct increased, and TT performance improved on Days 21 and 27 compared to PRE ( p < 0.05). Energy expenditure, fat oxidation, and metabolic clearance rate during LC increased ( p < 0.05) from PRE to POST. Myofiber type, protein markers of mitochondrial biogenesis, and capillarization were unchanged PRE to POST. Transcriptional regulation of mitochondrial activity and fat metabolism increased from PRE to POST ( p < 0.05). These data indicate EPO administration during 28 days of strenuous exercise can enhance aerobic performance through improved oxygen carrying capacity, whole‐body and skeletal muscle fat metabolism.

Drummer, Devin J.↗
DOE OSTI2025

Kölliker's Organ Functions as a Developmental Hub in Mouse Cochlea Regulating Spiral Limbus and Tectorial Membrane Development

Kölliker's organ is a transient developmental structure in the mouse cochlea that undergoes significant remodeling postnatally. Utilizing an epithelial-specific conditional deletion mouse model of Prdm16 (marker and regulator of Kölliker's organ), we show that Prdm16 is required for interdental cell development, and thereby the development of the limbal domain of the tectorial membrane and its medial anchorage to the spiral limbus. Additionally, we show that Kölliker's organ is involved in normal tectorial membrane collagen fibril development and maturation. Interestingly, mesenchymal cells of the spiral limbus underneath Prdm16 -deficient Kölliker's organ failed to produce interstitial matrix proteins, resulting in a hypoplastic and truncated spiral limbus, indicating a non-cell autonomous role of Prdm16 in regulating spiral mesenchymal matrix development. Single-cell RNA sequencing identified differentially expressed genes in Prdm16 -deficient Kölliker's organ suggesting a role for connective tissue growth factor (CTGF) downstream Prdm16 in epithelial-mesenchymal signaling involved in spiral limbus matrix deposition. Prdm16 -deficient mice showed a hearing deficit, as indicated by elevated auditory brainstem response thresholds at most frequencies, consistent with the cochlear structural defects. Both sexes were studied. This work establishes Prdm16 as a deafness gene in mice through its role in regulating Kölliker's organ development. Such understanding recognizes Kölliker's organ as a developmental hub regulating multiple surrounding cochlear structures.

Zhang, Hongji↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

CERES: CRISPR Engineering for the Rapid Enhancement of Strains

Previous strain development efforts for cyanobacteria have failed to achieve the necessary productivities needed to support economic biofuel production. We proposed to develop CRISPR Engineering for Rapid Enhancement of Strains (CERES). We developed genetic and computational tools to enable future high-throughput screening of CRISPR interference (CRISPRi) libraries in the cyanobacterium Synechococcus sp. PCC 7002, including: (1) Operon- SEQer: an ensemble of algorithms for predicting operon pairs using RNA-seq data, (2) experimental characterization and machine learning prediction of gRNA design rules for CRISPRi, and (3) a shuttle vector for gene expression. These tools lay the foundation for CRISPR library screening to develop cyanobacterial strains that are optimized for growth or metabolite production under a wide range of environmental conditions. The optimization of cyanobacterial strains will directly advance U.S. energy and climate security by enabling domestic biofuel production while simultaneously mitigating atmospheric greenhouse gases through photoautotrophic fixation of carbon dioxide.

09 BIOMASS FUELS↗
DOE OSTI2021

Deuterium Concentration Effects on Cell Cycle Progression

Deuterium (D) seems to play an important role in biology and is thought to be a missing piece in understanding cancer and radiation resistance. D is found in natural water at a concentration of ~150 parts per million (ppm), while D concentrations above 150 ppm are known to produce toxic effects in many organisms. There is evidence to suggest D levels significantly less than 150 ppm can cause delays in cell progression through the normal mitotic cell cycle. Some have theorized that the deuterium: hydrogen ratio (D:H) in cells may impact radiation resistance. Therefore, evaluating the role of D in human cells should lead to a better understanding of cell cycle progression and radiation resistance. To date, little has been revealed on the time-dependent effects of deuterium-depleted water (DDW – less than 150 ppm) on normal and cancer human cells or how the reduction of cell proliferation is associated with cell cycle regulation and consequence on gene expression profiles. Our studies will help further the mission of the Department of Energy to enhance the understanding of deuterium in fundamental biology by studying the cell cycle as a function of D concentration.

36 MATERIALS SCIENCE↗