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Ames Laboratory scientist Doug McCorkle explains the importance of virtual engineering and talks about the C6. The C6 is a three-dimensional, fully-immersive synthetic environment residing in the center atrium of Iowa State University's Howe Hall.
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This study describes the composition and metabolic potential of a lignocellulosic biomass degrading community that decays poplar wood chips under anaerobic conditions. We examined the community that developed on poplar biomass in a non-aerated bioreactor over the course of a year, with no microbial inoculation other than the naturally occurring organisms on the woody material. The composition of this community contrasts in important ways with biomass-degrading communities associated with higher organisms, which have evolved over millions of years into a symbiotic relationship. Both mammalian and insect hosts provide partial size reduction, chemical treatments (low or high pH environments), and complex enzymatic 'secretomes' that improve microbial access to cell wall polymers. We hypothesized that in order to efficiently degrade coarse untreated biomass, a spontaneously assembled free-living community must both employ alternative strategies, such as enzymatic lignin depolymerization, for accessing hemicellulose and cellulose and have a much broader metabolic potential than host-associated communities. This would suggest that such a community would make a valuable resource for finding new catalytic functions involved in biomass decomposition and gaining new insight into the poorly understood process of anaerobic lignin depolymerization. Therefore, in addition to determining the major players in this community, our work specifically aimed at identifying functions potentially involved in the depolymerization of cellulose, hemicelluloses, and lignin, and to assign specific roles to the prevalent community members in the collaborative process of biomass decomposition. A bacterium similar to Magnetospirillum was identified among the dominant community members, which could play a key role in the anaerobic breakdown of aromatic compounds. We suggest that these compounds are released from the lignin fraction in poplar hardwood during the decay process, which would point to lignin-modification or depolymerization under anaerobic conditions.
This study developed a computational strategy that utilizes data inputs from multiple spatial scales to investigate how variability within individual fields can impact sustainable residue removal for bioenergy production. Sustainable use of agricultural residues for bioenergy production requires consideration of the important role that residues play in limiting soil erosion and maintaining soil C, health, and productivity. Increased availability of subfield‐scale data sets such as grain yield data, high‐fidelity digital elevation models, and soil characteristic data provides an opportunity to investigate the impacts of subfield‐scale variability on sustainable agricultural residue removal. Using three representative fields in Iowa, this study contrasted the results of current NRCS conservation management planning analysis with subfield‐scale analysis for rake‐and‐bale removal of agricultural residue. The results of the comparison show that the field‐average assumptions used in NRCS conservation management planning may lead to unsustainable residue removal decisions for significant portions of some fields. This highlights the need for additional research on subfield‐scale sustainable agricultural residue removal including the development of real‐time variable removal technologies for agricultural residue.
The transcription factor WRINKLED1 ( WRI1 ) is known as a master regulator of fatty acid synthesis in developing oilseeds of Arabidopsis thaliana and other species. WRI1 is known to directly stimulate the expression of many fatty acid biosynthetic enzymes and a few targets in the lower part of the glycolytic pathway. However, it remains unclear to what extent and how the conversion of sugars into fatty acid biosynthetic precursors is controlled by WRI 1. To shortlist possible gene targets for future in-planta experimental validation, here we present a strategy that combines phylogenetic foot printing of cis-regulatory elements with additional layers of evidence. Upstream regions of protein-encoding genes in A. thaliana were searched for the previously described DNA-binding consensus for WRI1, the ASML1/WRI1 (AW)-box. For about 900 genes, AW-box sites were found to be conserved across orthologous upstream regions in 11 related species of the crucifer family. For 145 select potential target genes identified this way, affinity of upstream AW-box sequences to WRI1 was assayed by Microscale Thermophoresis. This allowed definition of a refined WRI1 DNA-binding consensus. We find that known WRI1 gene targets are predictable with good confidence when upstream AW-sites are phylogenetically conserved, specifically binding WRI1 in the in vitro assay, positioned in proximity to the transcriptional start site, and if the gene is co-expressed with WRI1 during seed development. When targets predicted in this way are mapped to central metabolism, a conserved regulatory blueprint emerges that infers concerted control of contiguous pathway sections in glycolysis and fatty acid biosynthesis by WRI1. Several of the newly predicted targets are in the upper glycolysis pathway and the pentose phosphate pathway. Of these, plastidic isoforms of fructokinase ( FRK 3) and of phosphoglucose isomerase ( PGI 1) are particularly corroborated by previously reported seed phenotypes of respective null mutations.
Elucidating climatic impacts on stream nutrient export and stoichiometry will improve the understanding of forest carbon (C) storage in a warmer world. We constructed C, nitrogen (N), and phosphorus (P) budgets in four watersheds within a rain-snow transition site and another four within a higher-elevation, snow-dominated site, in California’s mixed-conifer zone. We used these two sites in a space-for-time substitution to assess the potential effects of warming on nutrient cycles in currently snow-dominated areas that will become more rain-dominated. During a non-drought period (water year (WY) 2004 – 2011), mean annual stream exports of C and N in particulate forms at the transition site were double that at the snow-dominated site, suggesting that sediment-associated nutrient losses may increase with warming. The transition site had 12% lower N but double the P content in mineral horizons, lower N:P mass ratios in organic horizons, and lower stream export of dissolved inorganic N than the snow-dominated site. Furthermore, these differences suggest that montane forests may receive lower supply of N relative to P with warming. In addition, given strong interests in forest thinning to increase drought resiliency, we examined changes in stream nutrient export after thinning and during a major drought period (WY 2013 – 2015). Stream exports of C, N, and P were similar between unthinned and thinned watersheds during drought, suggesting negligible thinning impacts on stream nutrient export during excessively dry periods. Taken together, our results suggest that as the climate warms, California’s montane forests may lose more nutrients through erosion and receive less N input than P.
Here, soil erosion continuously redistributes soil and associated soil organic matter (SOM) on the Earth's surface, with important implications for biogeochemical cycling of essential elements and terrestrial carbon sequestration. Despite the importance of soil erosion, surprisingly few studies have evaluated the sources of eroded carbon (C). We used natural abundance levels of the stable and radioactive isotopes of C ( 13 C and 14 C) and stable isotope of nitrogen ( 15 N) to elucidate the origins of SOM eroded from low-order catchments along the western slopes of the Sierra Nevada of California, USA. Our work was conducted in two relatively undisturbed catchments (low elevation = 1800 m, and high elevation = 2300 m) of the Kings River Experimental Watersheds (KREW) in the Sierra National Forest. Sediment captured in basins at the outlet of each gauged watershed were compared to possible source materials, which included: upland surficial organic horizons (i.e., forest floor) and mineral soils (0–0.6 m) from three landform positions (i.e., crest, backslope, and toeslope), stream bank soils (0–0.6 m), and stream-bed materials (0–0.05 m). We found that most of the organic matter (OM) in the captured sediments was composed of O-horizon material that had high C concentrations. Radiocarbon analyses also showed that the captured OM is composed of modern (post-1950) C, with fraction modern values at or above 1.0. Our results suggest that surface (sheet) erosion, as opposed to channeling through established streams and episodic mass wasting events, is likely the largest source of sediment exported out of these minimally disturbed, headwater catchments. The erosional export of sediment with a high concentration of C, especially in the form of relatively undecomposed litter from the O horizon, suggests that a large fraction of the exported C is likely to be decomposed during or after erosion; hence, it is unlikely that soil erosion acts as a significant net sink for atmospheric CO 2 in these low-order, temperate forest catchments.
Epigenetic landscapes can shape physiologic and disease phenotypes. We used integrative, high resolution multi-omics methods to delineate the methylome landscape and characterize the oncogenic drivers of esophageal squamous cell carcinoma (ESCC). We found 98% of CpGs are hypomethylated across the ESCC genome. Hypo-methylated regions are enriched in areas with heterochromatin binding markers (H3K9me3, H3K27me3), while hyper-methylated regions are enriched in polycomb repressive complex (EZH2/SUZ12) recognizing regions. Altered methylation in promoters, enhancers, and gene bodies, as well as in polycomb repressive complex occupancy and CTCF binding sites are associated with cancer-specific gene dysregulation. Epigenetic-mediated activation of non-canonical WNT/β-catenin/MMP signaling and a YY1/lncRNA ESCCAL-1/ribosomal protein network are uncovered and validated as potential novel ESCC driver alterations. This study advances our understanding of how epigenetic landscapes shape cancer pathogenesis and provides a resource for biomarker and target discovery.
The ballistic performance of edge-clamped monolithic polyimide aerogel blocks (12 mm thickness) has been studied through a series of impact tests using a helium-filled gas gun connected to a vacuum chamber and a spherical steel projectile (approximately 3 mm diameter) with an impact velocity range of 150–1300 m s -1 . The aerogels had an average bulk density of 0.17 g cm -3 with high porosity of approximately 88%. The ballistic limit velocity of the aerogels was estimated to be in the range of 175–179 m s -1 . Moreover, the aerogels showed a robust ballistic energy absorption performance (e.g., at the impact velocity of 1283 m s -1 at least 18% of the impact energy was absorbed). At low impact velocities, the aerogels failed by ductile hole enlargement followed by a tensile failure. By contrast, at high impact velocities, the aerogels failed through an adiabatic shearing process. Given the substantially robust ballistic performance, the polyimide aerogels have a potential to combat multiple constraints such as cost, weight, and volume restrictions in aeronautical and aerospace applications with high blast resistance and ballistic performance requirements such as in stuffed Whipple shields for orbital debris containment application.
Significance Historically, it has been understood that for gene expression in eukaryotes, each messenger RNA encodes a single protein. With the recent development of technologies to sequence full-length transcripts en masse, we have discovered hundreds of examples in two species of green algae where two, three, or more proteins are translated from a single transcript. These “polycistronic” transcripts are found in diverse species throughout the green algal lineage, which highlights their biological importance. We have leveraged these findings to coexpress pairs of genes on polycistronic transcripts in vitro, which should facilitate efforts to engineer algae for research and industrial applications.
Abstract For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.
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Several recent reports and workshops have identified integrated computational engineering as an emerging technology with the potential to transform engineering design. The goal is to integrate geometric models, analyses, simulations, optimization and decision-making tools, and all other aspects of the engineering process into a shared, interactive computer-generated environment that facilitates multidisciplinary and collaborative engineering. While integrated computational engineering environments can be constructed from scratch with high-level programming languages, the complexity of these proposed environments makes this type of approach prohibitively slow and expensive. Rather, a high-level software framework is needed to provide the user with the capability to construct an application in an intuitive manner using existing models and engineering tools with minimal programming. In this paper, we present an exploratory open source software framework that can be used to integrate the geometric models, computational fluid dynamics (CFD), and optimization tools needed for shape optimization of complex systems. This framework is demonstrated using the multiphase flow analysis of a complete coal transport system for an 800 MW pulverized coal power station. The framework uses engineering objects and three-dimensional visualization to enable the user to interactively design and optimize the performance of the coal transport system.
Abstract Background Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13 C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13 C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.
The p53 ability to elicit stress specific and cell type specific responses is well recognized, but how that specificity is established remains to be defined. Whether upon activation p53 binds to its genomic targets in a cell type and stress type dependent manner is still an open question. Here we show that the p53 binding to the human genome is selective and cell context-dependent. We mapped the genomic binding sites for the endogenous wild type p53 protein in the human cancer cell line HCT116 and compared them to those we previously determined in the normal cell line IMR90. We report distinct p53 genome-wide binding landscapes in two different cell lines, analyzed under the same treatment and experimental conditions, using the same ChIP-seq approach. This is evidence for cell context dependent p53 genomic binding. The observed differences affect the p53 binding sites distribution with respect to major genomic and epigenomic elements (promoter regions, CpG islands and repeats). We correlated the high-confidence p53 ChIP-seq peaks positions with the annotated human repeats (UCSC Human Genome Browser) and observed both common and cell line specific trends. In HCT116, the p53 binding was specifically enriched at LINE repeats, compared to IMR90 cells. The p53 genome-wide binding patterns in HCT116 and IMR90 likely reflect the different epigenetic landscapes in these two cell lines, resulting from cancer-associated changes (accumulated in HCT116) superimposed on tissue specific differences (HCT116 has epithelial, while IMR90 has mesenchymal origin). In conclusion, our data support the model for p53 binding to the human genome in a highly selective manner, mobilizing distinct sets of genes, contributing to distinct pathways.
Growth in sucrose medium was previously found to trigger the expression of functions involved in the plant associated life style of the endophytic bacterium Enterobacter sp. 638. Therefore, comparative transcriptome analysis between cultures grown in sucrose or lactate medium was used to gain insights in the expression levels of bacterial functions involved in the endophytic life style of strain 638. Growth on sucrose as a carbon source resulted in major changes in cell physiology, including a shift from a planktonic life style to the formation of bacterial aggregates. This shift was accompanied by a decrease in transcription of genes involved in motility (e.g. flagella biosynthesis) and an increase in the transcription of genes involved in colonization, adhesion and biofilm formation. The transcription levels of functions previously suggested as being involved in endophytic behavior and functions responsible for plant growth promoting properties, including the synthesis of indole-acetic acid, acetoin and 2,3-butanediol, also increased significantly for cultures grown in sucrose medium. Interestingly, despite an abundance of essential nutrients transcription levels of functions related to uptake and processing of nitrogen and iron became increased for cultures grown on sucrose as sole carbon source. Transcriptome data were also used to analyze putative regulatory relationships. In addition to the small RNA csrABCD regulon, which seems to play a role in the physiological adaptation and possibly the shift between free-living and plant-associated endophytic life style of Enterobacter sp. 638, our results also pointed to the involvement of rcsAB in controlling responses by Enterobacter sp. 638 to a plant-associated life style. Lastly, targeted mutagenesis was used to confirm this role and showed that compared to wild-type Enterobacter sp. 638 a ΔrcsB mutant was affected in its plant growth promoting ability.
Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed to be safe, may have harmful effects. This perception has spurred a growing interest in investigating the potential risks associated with low-dose radiation exposure across various scenarios. To comprehensively explore the health consequences of low-dose radiation, our study employs a robust statistical framework that examines whether specific groups of genes, belonging to known pathways, exhibit coordinated expression patterns that align with the radiation levels. Notably, our findings reveal the existence of intricate yet consistent signatures that reflect the molecular response to radiation exposure, distinguishing between low-dose and high-dose radiation. Moreover, we leverage a pathway-constrained variational autoencoder to capture the nonlinear interactions within gene expression data. By comparing these two analytical approaches, our study aims to gain valuable insights into the impact of low-dose radiation on gene expression patterns, identify pathways that are differentially affected, and harness the potential of machine learning to uncover hidden activity within biological networks. This comparative analysis contributes to a deeper understanding of the molecular consequences of low-dose radiation exposure.
We report here genome-wide analysis of the tumor suppressor p53 binding sites in normal human cells. 743 high-confidence ChIP-seq peaks representing putative genomic binding sites were identified in normal IMR90 fibroblasts using a reference chromatin sample. More than 40% were located within 2 kb of a transcription start site (TSS), a distribution similar to that documented for individually studied, functional p53 binding sites and, to date, not observed by previous p53 genome-wide studies. Nearly half of the high-confidence binding sites in the IMR90 cells reside in CpG islands, in marked contrast to sites reported in cancer-derived cells. The distinct genomic features of the IMR90 binding sites do not reflect a distinct preference for specific sequences, since the de novo developed p53 motif based on our study is similar to those reported by genome-wide studies of cancer cells. More likely, the different chromatin landscape in normal, compared with cancer-derived cells, influences p53 binding via modulating availability of the sites. We compared the IMR90 ChIPseq peaks to the recently published IMR90 methylome1 and demonstrated that they are enriched at hypomethylated DNA. Our study represents the first genome-wide, de novo mapping of p53 binding sites in normal human cells and reveals that p53 binding sites reside in distinct genomic landscapes in normal and cancer-derived human cells.