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At least 829 records · Page 46

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources, which include pharmaceuticals, bioplastics, chemical feedstocks, and industrial enzymes. Here, a CO2-based ISRU recombinant protein bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Initial work characterized candidate organisms for growth on acetate and formic acid, carbon substrates that can be synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Cyberlindnera jadinii and Escherichia coli. Genetic modifications in E. coli will be facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance calculations from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor concept for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA production in reduced-gravity environments.

Biomanufacturing, Pathway Engineering, Flux Balanc↗

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Gene Expression Programming for Quantum Computing

Here, we introduce QuantumGEP, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (1) maps a given set of input states to a given set of output states or (2) transforms a fixed initial state to minimize a given physical quantity of the output state. QuantumGEP is a driver program that uses evendim, a generic computational engine for GEP, both of which are free and open source. We apply QuantumGEP as a powerful solver for MaxCut in graphs and for condensed matter quantum many-body Hamiltonians.

97 MATHEMATICS AND COMPUTING↗

Self-Assembling Cell-Free Systems for Scalable Bioconversion

This project focused on developing cell-free systems to directly express multi-enzyme catalysts and perform CO2 bioconversions for industrial chemical production. The use of cell-free expression (CFE) systems derived from bacterial lysates is emerging as a promising approach for biomanufacturing. CFEs are genetically programmable, permit the expression of toxic enzymes, and allow for rapid prototyping of metabolic pathways. Research Contributions: 1. Understanding the Area Investigated: This research advances the understanding of cell-free systems by demonstrating their capability to perform complex multi-enzyme reactions. By directly expressing multi-gene systems, CFEs avoid the high costs and inefficiencies associated with producing and purifying enzymes for multi-step pathways. 2. Technical Effectiveness and Economic Feasibility: The project successfully engineered a CFE-based multienzyme biocatalyst for the de novo synthesis of serine and glycine from CO2 equivalents (formate and bicarbonate) and ammonia. This method achieved a 30% conversion rate of formate into these industrially important amino acids. Additionally, an 8-gene CFE biocatalyst was developed to produce malate, conserving 43% of carbon that would otherwise be lost as CO2. This approach has the potential to reach higher carbon efficiency than microbial production. 3. Public Benefit: The cell-free production of chemicals like serine, glycine, and malate using electrochemically generated formate could significantly reduce CO2 emissions. For example, satisfying the global malate market with this method could avoid approximately 400,000 tons of CO2 emissions annually. This work demonstrates the potential of CFE systems to produce platform chemicals, contributing to environmental sustainability and reducing reliance on petrochemicals. Future Prospects: The CFE-based biocatalyst process could be extended to produce a variety of chemicals, including other industrial di-acids, aromatics, terpenes, alcohols, and polymers. This project showcases the capabilities of cell-free expression systems for prototyping carbon-conserving pathways and sustainably bioproducing platform chemicals, marking a significant step towards economically-viable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high-yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence-derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock.

RUBY↗

Catabolism of β-5 linked aromatics by Novosphingobium aromaticivorans

ABSTRACT Aromatic compounds are an important source of commodity chemicals traditionally produced from fossil fuels. Aromatics derived from plant lignin can potentially be converted into commodity chemicals through depolymerization followed by microbial funneling of monomers and low molecular weight oligomers. This study investigates the catabolism of the β-5 linked aromatic dimer dehydrodiconiferyl alcohol (DC-A) by the bacterium Novosphingobium aromaticivorans . We used genome-wide screens to identify candidate genes involved in DC-A catabolism. Subsequent in vivo and in vitro analyses of these candidate genes elucidated a catabolic pathway composed of four required gene products and several partially redundant dehydrogenases that convert DC-A to aromatic monomers that can be funneled into the central aromatic metabolic pathway of N. aromaticivorans . Specifically, a newly identified γ-formaldehyde lyase, PcfL, opens the phenylcoumaran ring to form a stilbene and formaldehyde. A lignostilbene dioxygenase, LsdD, then cleaves the stilbene to generate the aromatic monomers vanillin and 5-formylferulate (5-FF). We also showed that the aldehyde dehydrogenase FerD oxidizes 5-FF before it is decarboxylated by LigW, yielding ferulic acid. We found that some enzymes involved in the β-5 catabolism pathway can act on multiple substrates and that some steps in the pathway can be mediated by multiple enzymes, providing new insights into the robust flexibility of aromatic catabolism in N. aromaticivorans . A comparative genomic analysis predicted that the newly discovered β-5 aromatic catabolic pathway is common within the order Sphingomonadales. IMPORTANCE In the transition to a circular bioeconomy, the plant polymer lignin holds promise as a renewable source of industrially important aromatic chemicals. However, since lignin contains aromatic subunits joined by various chemical linkages, producing single chemical products from this polymer can be challenging. One strategy to overcome this challenge is using microbes to funnel a mixture of lignin-derived aromatics into target chemical products. This approach requires strategies to cleave the major inter-unit linkages of lignin to release monomers for funneling into valuable products. In this study, we report newly discovered aspects of a pathway by which the Novosphingobium aromaticivorans DSM12444 catabolizes aromatics joined by the second most common inter-unit linkage in lignin, the β-5 linkage. This work advances our knowledge of aromatic catabolic pathways, laying the groundwork for future metabolic engineering of this and other microbes for optimized conversion of lignin into products.

59 BASIC BIOLOGICAL SCIENCES↗

Use of a genetic algorithm for the analysis of eye movements from the linear vestibulo-ocular reflex

It is common in vestibular and oculomotor testing to use a single-frequency (sine) or combination of frequencies [sum-of-sines (SOS)] stimulus for head or target motion. The resulting eye movements typically contain a smooth tracking component, which follows the stimulus, in which are interspersed rapid eye movements (saccades or fast phases). The parameters of the smooth tracking--the amplitude and phase of each component frequency--are of interest; many methods have been devised that attempt to identify and remove the fast eye movements from the smooth. We describe a new approach to this problem, tailored to both single-frequency and sum-of-sines stimulation of the human linear vestibulo-ocular reflex. An approximate derivative is used to identify fast movements, which are then omitted from further analysis. The remaining points form a series of smooth tracking segments. A genetic algorithm is used to fit these segments together to form a smooth (but disconnected) wave form, by iteratively removing biases due to the missing fast phases. A genetic algorithm is an iterative optimization procedure; it provides a basis for extending this approach to more complex stimulus-response situations. In the SOS case, the genetic algorithm estimates the amplitude and phase values of the component frequencies as well as removing biases.

Non-NASA Center↗

State-dependent motion of a genetically encoded fluorescent biosensor

Genetically encoded biosensors can measure biochemical properties such as small-molecule concentrations with single-cell resolution, even in vivo. Despite their utility, these sensors are “black boxes”: Very little is known about the structures of their low- and high-fluorescence states or what features are required to transition between them. We used LiLac, a lactate biosensor with a quantitative fluorescence-lifetime readout, as a model system to address these questions. X-ray crystal structures and engineered high-affinity metal bridges demonstrate that LiLac exhibits a large interdomain twist motion that pulls the fluorescent protein away from a “sealed,” high-lifetime state in the absence of lactate to a “cracked,” low-lifetime state in its presence. Understanding the structures and dynamics of LiLac will help to think about and engineer other fluorescent biosensors.

Rosen, Paul C. (ORCID:000000017414454X)↗

Data for Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high- yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence- derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock. **NOTE: in "TableS2_ProtocolComparison.csv", the data from row 665 to 971 should be removed.

Gene Editing↗

Phylogenomics and genetic analysis of solvent-producing Clostridium species

Abstract The genus Clostridium is a large and diverse group within the Bacillota (formerly Firmicutes), whose members can encode useful complex traits such as solvent production, gas-fermentation, and lignocellulose breakdown. We describe 270 genome sequences of solventogenic clostridia from a comprehensive industrial strain collection assembled by Professor David Jones that includes 194 C. beijerinckii , 57 C. saccharobutylicum , 4 C. saccharoperbutylacetonicum , 5 C. butyricum , 7 C. acetobutylicum , and 3 C. tetanomorphum genomes. We report methods, analyses and characterization for phylogeny, key attributes, core biosynthetic genes, secondary metabolites, plasmids, prophage/CRISPR diversity, cellulosomes and quorum sensing for the 6 species. The expanded genomic data described here will facilitate engineering of solvent-producing clostridia as well as non-model microorganisms with innately desirable traits. Sequences could be applied in conventional platform biocatalysts such as yeast or Escherichia coli for enhanced chemical production. Recently, gene sequences from this collection were used to engineer Clostridium autoethanogenum , a gas-fermenting autotrophic acetogen, for continuous acetone or isopropanol production, as well as butanol, butanoic acid, hexanol and hexanoic acid production.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic Basis of Non–Photochemical Quenching and Photosystem II Efficiency Responses to Chilling in the Biomass Crop Miscanthus

Miscanthus holds a promise as a biocrop due to its high yield, perenniality and ability to grow on infertile soils. However, the current commercial biomass production of Miscanthus is mostly limited to a single sterile triploid clone of M. × giganteus. Nevertheless, parental species of M. × giganteus, Miscanthus sacchariflorus and Miscanthus sinensis contain vast genetic diversity for crop improvement. With M. sacchariflorus having a natural geographic distribution in cold-temperate northeast China and eastern Russia, we hypothesised that it has substantial variation in physiological response to chilling. Using a semi-high-throughput method, we phenotyped 209 M. sacchariflorus genotypes belonging to six genetic groups for non-photochemical quenching (NPQ) and photosystem II efficiency (ΦPSII) kinetics under warm and chilling treatments in three growing seasons. In response to the chilling treatment, all genetic groups exhibited an increase in NPQ induction rate indicating faster activation of NPQ in light. Notably, under chilling, the Korea/NE China/Russia 2x and N China 2x groups stood out for the highest NPQ rate in light and the highest steady-state NPQ in light. This NPQ phenotype may contribute adaptation to chilling during bright, cold mornings of spring and early autumn in temperate climates, when faster NPQ would better protect from oxidative stress. Such enhanced adaptation could expand the growing season and thus productivity at a given location or expand the range of economically viable growing locations to higher latitudes and altitudes. A genome-wide association study identified 126 unique SNPs associated with NPQ and ΦPSII traits. Among the identified candidate genes were enzymes involved in the ascorbate recycle and shikimate pathway, gamma-aminobutyric acid and cation efflux transporters. Identifying natural variation and genes involved in NPQ and ΦPSII kinetics considerably enlarges the toolbox for breeding and/or engineering Miscanthus with optimised photosynthesis under warm and chilling conditions for sustainable feedstock production for bioenergy.

09 BIOMASS FUELS↗

Reducing stomatal density by expression of a synthetic epidermal patterning factor increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop

Abstract Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Engineering lower stomatal density to reduce stomatal conductance (gs) has improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the relationship of photosynthesis (AN) with intracellular CO2 concentration (ci), such that photosynthesis is CO2 saturated and reductions in gs are unlikely to limit AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum led to reduced stomatal densities, reduced gs, reduced plant water use, and avoidance of stress during a period of water deprivation. In addition, moderate reduction in stomatal density did not increase stomatal limitation to AN. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues could provide a pathway to improved agronomic outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Spaceflight Autonomous Multigenerational Microbial Sequencer in Support of Plant-Growth Systems

The CubeSat platform has proven successful in obtaining meaningful life science information when biological payloads are incorporated. Examples include: 1) the first-ever CubeSat with a biological payload, GeneSat-1, which demonstrated decreased growth rates for flight samples of Escherichia coli in low Earth orbit (Parra et al. 2008); 2) PharmaSat, demonstrated that Saccharomyces cerevisiae in the microgravity environment exhibits a significant level of metabolic activity even at high doses of applied antifungal (Ricco et al. 2011); 3) O/OREOS, which used Bacillus subtilis(bacteria) to demonstrate for the first time that microorganisms can be loaded in a dried, dormant form and then rehydrated and grown in orbit months after launch (Nicholson et al. 2011; Ehrenfreund et al. 2014; 4) the SporeSat payload, which investigated Ceratopteris richardii(fern spores) using lab-on-a-chip devices (BioCDs) and minicentrifuges to produce artificial gravitational forces in ground studies (Park et al. 2017), with demonstration of the BioCD and minicentrifuge in space; 5) EcAMSat, the first CubeSat to be directly deployed from the ISS for an experiment assessing antibiotic resistance of E. coli in the microgravity environment (Padgen et al. 2020); 6) BioSentinel, exposed a culture of yeast to galactic cosmic radiation (GCR) and solar particle events while in heliocentric orbit to measure the rate of double-strand-break repair using DNA-repair-deficient mutants. This effort measures the metabolic parameters of yeast in a deep-space environment compared to Earth ambient conditions using a 3-color LED detection system (Ricco et al. 2020; Padgen et al. 2021). We aim to expand this list to include a Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS). SAMMS will allow for the genome level understanding of changes in growth and metabolic activity for any organism. While microbes are suitable for early studies in our proposed platform because of their small size, small and relatively less-complicated genomes, fast generation times, and relevance to life support systems; multicellular organisms can similarly be evaluated for their genetic response to the spaceflight environment. The Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) will enable autonomous sequencing of biological samples in plant production units, cislunar orbit and on the lunar surface to examine spaceflight effects (ie. radiation, altered gravity, reduced pressures) on plant and microbial genomes.On this team a Kennedy Space Center (KSC) space crop production and water systems microbiologist/molecular biologist works with a Johnson Space Center (JSC) International Space Station (ISS) microbial sequencing expert and an Ames Research Center (ARC) CubeSat Engineering team to convert an automated Oxford Nanopore librarypreparation and sequencing method to a fluidic CubeSat payload system. The Oxford Nanopore MinION sequencing platform has proven successful in the spaceflight environment onboard the ISS (Stahl-Rommel et al. 2021). Further long-duration spaceflight and exposure to high levels of radiation will cause genotypic effects in biological organisms that may affect their function. Monitoring the adaption of a population to the spaceflight environment and any subsequent beneficial mutations will allow for the harnessing of organisms best suited for use in life support systems. This will ensure that the selected life support-essential microorganisms maintain their intended specified function over generations of culturing in the relevant spaceflight environment without becoming hazardous to crew or spacecraft systems.

Aubrie E Orourke↗

Metabolic flux, metabolite, and transcript analysis uncover reprogramming of metabolism toward higher seed oil

Overexpression of WRINKLED1 (WRI1), a master regulator of glycolysis and fatty acid biosynthesis, together with DIACYLGLYCEROL ACYLTRANSFERASE1 (DGAT1), which catalyzes the final step of triacylglycerol assembly, is a promising strategy for enhancing seed oil content. However, how these regulators coordinate system-wide metabolic reprogramming at the levels of gene expression, metabolite pools, and fluxes remains poorly understood. To address this, we performed 13 C-metabolic flux analysis, metabolomics, and transcriptomics on in vitro cultured pennycress (Thlaspi arvense L.) embryos overexpressing the native WRI1 and DGAT1 homologs. Here, in cultured embryos, WRI1/DGAT1 overexpression increased triacylglycerol accumulation by 28% while reducing protein content by 34%, relative to the wild type. Embryos showed ∼20-fold and 50-fold upregulation of WRI1 and DGAT1 along with induction of WRI1 target genes in glycolysis and fatty acid biosynthesis. Genes associated with photosynthesis and Calvin cycle functions were also upregulated, whereas genes encoding ribosomal proteins and seed storage proteins were strongly repressed, consistent with the observed lipid–protein tradeoff. Flux analysis revealed that enhanced triacylglycerol biosynthesis is supported by increased flux through the Rubisco shunt and cytosolic pyruvate kinase, while the oxidative pentose phosphate pathway and malic enzyme contributed little to NADPH or pyruvate supply. Metabolomic profiling revealed extensive perturbations in glycolytic intermediates, tricarboxylic acid cycle metabolites, and amino acids. In plant grown seeds, WRI1/DGAT1 lines also showed a modest but significant increase in total lipid content. Collectively, these findings reveal how WRI1 and DGAT1 reprogram central metabolism to enhance oil accumulation, with relevance to mature seeds.

59 BASIC BIOLOGICAL SCIENCES↗

Model-informed, Adaptive Physical Vapor Deposition to Fabricate Hierarchical Binary-alloy Thin-films

Designing next generation thin films, tailor-made for specific applications, relies on the availability of robust processing-structure-property relationships. Traditional structure zone diagrams are limited to low-dimensional mappings, with machine-learning methods only recently attempting to relate multiple processing parameters to the final microstructure. Despite this progress, structure-processing relationships are unknown for processing conditions that vary during thin-film deposition, limiting the range of microstructures and properties achievable. In this project, we employed a phase-field computational model combined with a genetic algorithm (GA) to identify and design time-dependent processing protocols that achieve tailor-made microstructures. We simulate the physical vapor deposition of a binary-alloy thin film by employing a phase-field model, where deposition rates and diffusivities are controlled via the genetic algorithm. Our GA-guided protocols achieve targeted microstructures with lateral and vertical concentration modulations, as well as more complex, hierarchical microstructures previously not described in simple structure zone diagrams. Our algorithm provides insight to experimentalists looking for additional avenues to design novel thin-film microstructures.

36 MATERIALS SCIENCE↗

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Overall, our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

42 ENGINEERING↗

Whole genome resequencing data from a collection of Clostridium Thermocellum strains

Clostridium thermocellum is an anaerobic thermophilic bacterium that natively ferments cellulose to ethanol and organic acids. This data set is a collection of whole genome resequencing data for several hundred strains of Clostridium thermocellum. It includes strains that have been engineered to increase ethanol production, strains that have been engineered to understand microbial physiology, and strains that have been adapted for desired phenotypes including increased ethanol tolerance. Resequencing data consists of paired Illumina reads, 100-150 bp on each end, with a ~500 bp insert size. One data file containing raw Illumina data (interleaved) is available for each strain. We also provide data describing the mutations identified in each strain, and distinguish between inherited and newly observed mutations. In addition to resequencing data, we also provide metadata describing the lineage of each strain, and any targeted genetic modifications.

resequencing bio energy fermentation↗

Deterministic Design Optimization of Structures in OpenMDAO Framework

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

Coroneos, Rula M.↗