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At least 91 records · Page 5

Evidence of the Involvement of a Cyclase Gene in the Biosynthesis of Ochratoxin A in Aspergillus carbonarius

Ochratoxin A (OTA) is a well-known mycotoxin with wide distribution in food and feed. Fungal genome sequencing has great utility for identifying secondary metabolites gene clusters for known and novel compounds. A comparative analysis of the OTA-biosynthetic cluster in A. steynii, A. westerdijkiae, A. niger, A. carbonarius, and P. nordicum has revealed a high synteny in OTA cluster organization in five structural genes (otaA, otaB, ota, otaR1, and otaD). Moreover, a recent detailed comparative genome analysis of Aspergilli OTA producers led to the identification of a cyclase gene, otaY, located in the OTA cluster between the otaA and otaB genes, encoding for a predicted protein with high similarity to SnoaLs domain. These proteins have been shown to catalyze ring closure steps in the biosynthesis of polyketide antibiotics produced in Streptomyces. In the present study, we demonstrated an upregulation of the cyclase gene in A. carbonarius under OTA permissive conditions, consistent with the expression trends of the other OTA cluster genes and their role in OTA biosynthesis by complete gene deletion. Our results pointed out the involvement of a cyclase gene in OTA biosynthetic pathway for the first time. They represent a step forward in the understanding of the molecular basis of OTA biosynthesis in A. carbonarius.

59 BASIC BIOLOGICAL SCIENCES↗

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗

Elucidating algal-bacterial community interactions by tracking volatile biomarkers (Final Report)

This feasibility study project aimed to lay further groundwork for studying and understanding how microorganisms interact with each other at the molecular level using model algal-bacterial co-cultures. A better understanding of such interactions is critical to optimizing and operating biotic platforms for a number of applications, including bioenergy, algal bioproducts and agriculture, and carbon capture. Here we explored the feasibility of characterizing and following these interactions by identifying and tracking volatile metabolites and biomarkers in the complex gaseous headspace of such cultures. We set up an experimental platform using a co-culture of Phaeodactylum tricornutum and Marinobacter subspecies 3-2 as a model system, used solid-phase microextraction fibers for volatile collection at various time points throughout culture growth, and employed gas chromatography mass spectrometry-based instrumentation available at LLNL for compound identification and quantification. We found that it is feasible to determine volatile profiles from the growth of Phaeodactylum tricornutum and Marinobacter subspecies 3-2 using our methodology and monitor profile changes over time. We also observed that volatiles distinguishing between cultures of the individual species and the co-cultures could be detected. We expect that results of this project will feed into the ongoing LLNL’s DOE BER funded Biofuels Scientific Focus Area (SFA) on algal-bacterial interactions and pave the way for future expanded volatile studies supported by DOE. The approach and technologies developed here would also be applicable and transferable to other microbial communities under study, such as cyanobacteria, rhizosphere communities and biofilms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A multi-omic survey of black cottonwood tissues highlights coordinated transcriptomic and metabolomic mechanisms for plant adaptation to phosphorus deficiency

Phosphorus (P) deficiency in plants creates a variety of metabolic perturbations that decrease photosynthesis and growth. Phosphorus deficiency is especially challenging for the production of bioenergy feedstock plantation species, such as poplars (Populus spp.), where fertilization may not be practically or economically feasible. While the phenotypic effects of P deficiency are well known, the molecular mechanisms underlying whole-plant and tissue-specific responses to P deficiency, and in particular the responses of commercially valuable hardwoods, are less studied. We used a multi-tissue and multi-omics approach using transcriptomic, proteomic, and metabolomic analyses of the leaves and roots of black cottonwood (Populus trichocarpa) seedlings grown under P-deficient (5 µM P) and replete (100 µM P) conditions to assess this knowledge gap and to identify potential gene targets for selection for P efficiency. In comparison to seedlings grown at 100 µM P, P-deficient seedlings exhibited reduced dry biomass, altered chlorophyll fluorescence, and reduced tissue P concentrations. In line with these observations, growth, C metabolism, and photosynthesis pathways were downregulated in the transcriptome of the P-deficient plants. Additionally, we found evidence of strong lipid remodeling in the leaves. Metabolomic data showed that the roots of P-deficient plants had a greater relative abundance of phosphate ion, which may reflect extensive degradation of P-rich metabolites in plants exposed to long-term P-deficiency. With the notable exception of the KEGG pathway for Starch and Sucrose Metabolism (map00500), the responses of the transcriptome and the metabolome to P deficiency were consistent with one another. No significant changes in the proteome were detected in response to P deficiency. Collectively, our multi-omic and multi-tissue approach enabled the identification of important metabolic and regulatory pathways regulated across tissues at the molecular level that will be important avenues to further evaluate for P efficiency. These included stress-mediating systems associated with reactive oxygen species maintenance, lipid remodeling within tissues, and systems involved in P scavenging from the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Origin of replication discovery for environmentally isolated Pantoea strain enables expression of heterologous proteins, pathways and products

Leveraging predicted origin sequences from a previously characterized groundwater plasmidome, we constructed a barcoded plasmid library to screen for previously unknown origins. Testing this library against a panel of representative bacterial strains led to the identification of 3 previously unknown origins that replicate in gram-negative bacteria not previously associated with these origin sequences. Experimental validation confirmed that a plasmid bearing origin 6911 as the sole origin could replicate with a copy number of 9 (±2) in Pantoea sp. MT58, a fast growing and metal tolerant, environmentally important bacterium. Plasmids based on this new origin were used to express the reporter protein GFP, and non-native metabolite pathways for the natural product indigoidine and the terpenoid compound isoprenol. Functional previously unknown origins of replication in such non-model organisms can expand the toolkit for genetic manipulations of both model and less-studied bacteria.

molecular biology↗

nmRanalysis: An Open-Source Web Application for Semi-automated NMR Metabolite Profiling

Though data acquisition and initial signal pre-processing of nuclear magnetic resonance (NMR) spectra have achieved high degrees of automation, downstream processing - specifically the profiling of spectra - has bottlenecked the overall NMR analysis workflow. Several efforts have been made to mitigate this bottleneck, but these solutions often trade an increase in automation for limitations elsewhere. Here, in this technical note, we introduce nmRanalysis, a user-friendly web-application that integrates the strengths of existing profiling tools for a more automated profiling workflow. nmRa-nalysis additionally incorporates novel features, including a machine-learning-driven recommender system for me-tabolite identification, further increasing the utility of nmRanalysis over the individual tools that it incorporates.

Flores, Javier E. [Pacific Northwest National Labo↗

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics. Methods: Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls. Results: The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects. Conclusions: Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

60 APPLIED LIFE SCIENCES↗

Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012

The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. To discover obesity-related mixed chemical exposure patterns in the general U.S. population. Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (ΣOH-Nap), and a pattern of high exposure levels of MCOP, MCNP, and MCPP were positively associated with obesity. Patterns of high levels of BP3, and a pattern of higher mixed levels of MPB, PPB, and MEP were found to have negative associations. Associations were strengthened using the targeted SDR model. In the single chemical analysis by GLM, BP3, MBP, PPB, MCOP, and MCNP showed significant associations with obesity or body indexes. The SDR model exceeded the performance of PCA in pattern identification. Both SDR and BKMR identified a positive contribution of ΣOH-Nap and MCOP, as well as a negative contribution of BP3 and PPB to obesity. Our study identified five core exposure patterns of chemical mixtures significantly associated with obesity using the newly developed SDR model. The SDR model could open a new avenue for assessing health effects of environmental mixture contaminants.

54 ENVIRONMENTAL SCIENCES↗

Molecular basis for catabolism of the abundant metabolite trans-4-hydroxy-L-proline by a microbial glycyl radical enzyme

The glycyl radical enzyme (GRE) superfamily utilizes a glycyl radical cofactor to catalyze difficult chemical reactions in a variety of anaerobic microbial metabolic pathways. Recently, a GRE, trans-4-hydroxy-L-proline (Hyp) dehydratase (HypD), was discovered that catalyzes the dehydration of Hyp to (S)-Δ 1 -pyrroline-5-carboxylic acid (P5C). This enzyme is abundant in the human gut microbiome and also present in prominent bacterial pathogens. However, we lack an understanding of how HypD performs its unusual chemistry. Here, we have solved the crystal structure of HypD from the pathogen Clostridioides difficile with Hyp bound in the active site. Biochemical studies have led to the identification of key catalytic residues and have provided insight into the radical mechanism of Hyp dehydration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selection and development of aptamers for pyoverdine

The rhizosphere is a small region surrounding plant roots that is enriched in biochemicals from root exudates and populated with fungi, nematode, and bacteria. Interaction of rhizosphere organisms with plants is mainly promoted by exudates from the roots. Root exudates contain biochemicals that come from primary and secondary metabolisms of plants. These biochemicals attract microbes, which influence plant nutrition. The rhizosphere bacteria (microbiome) are vital to plant nutrient uptake and influence biotic and abiotic stress and pathogenesis. Pseudomonas is a genus of gammaproteobacteria known for its ubiquitous presence in natural habitats and its striking ecological, metabolic, and biochemical diversity. Within the genus, members of the Pseudomonas fluorescens group are common inhabitants of soil and plant surfaces, and certain strains function in the biological control of plant disease, protecting plants from infection by soilborne and aerial plant pathogens. The soil bacterium Pseudomonas protegens Pf-5 (also known as Pseudomonas fluorescensPf-5) is a well-characterized biological strain, which is distinguished by its prolific production of the secondary metabolite, pyoverdine. Knowledge of the distribution of P. fluorescens secretory activity around plant roots is very important for understanding the interaction between P. fluorescens and plants and can be achieved by real time tracking of pyoverdine. To achieve the capability of real-time tracking in soil, we have used a structure-switching SELEX strategy to select high affinity ssDNA and 2’ F-Y-RNA aptamers with specificity for pyoverdine over other siderophores. Pyoverdines from various strains possess a conserved chromophore along with strain-specific peptide chain. Some of the isolated aptamers bind to chromophore of pyoverdine. These will identify pyoverdines from a variety of pseudomonads. Identification of aptamers that selectively bind the peptide portion of pyoverdine Pf-5 is underway. The identified aptamers that are broadly and narrowly specific for pyoverdines or Pf-5 will be optimized for integration into an electrochemical biosensor to track, in real time, P fluorescens activity and other pseudomonads in and around the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Data Science-Driven Analysis of Substrate-Permissive Diketopiperazine Reverse Prenyltransferase NotF: Applications in Protein Engineering and Cascade Biocatalytic Synthesis of (-)-Eurotiumin A

Prenyltransfer is an early-stage carbon-hydrogen bond (C-H) functionalization prevalent in the biosynthesis of a diverse array of biologically active bacterial, fungal, plant, and metazoan diketopiperazine (DKP) alkaloids. Toward the development of a unified strategy for biocatalytic construction of prenylated DKP indole alkaloids, we sought to identify and characterize a substrate-permissive C2 reverse prenyltransferase (PT). As the first tailoring event within the biosynthesis of cytotoxic notoamide metabolites, PT NotF catalyzes C2 reverse prenyltransfer of brevianamide F. Solving a crystal structure of NotF (in complex with native substrate and prenyl donor mimic dimethylallyl S-thiolodiphosphate (DMSPP)) revealed a large, solvent-exposed active site, intimating NotF may possess a significantly broad substrate scope. To assess the substrate selectivity of NotF, we synthesized a panel of 30 sterically and electronically differentiated tryptophanyl DKPs, the majority of which were selectively prenylated by NotF in synthetically useful conversions (2 to > 99%). Quantitative representation of this substrate library and development of a descriptive statistical model provided insight into the molecular origins of NotF's substrate promiscuity. This approach enabled the identification of key substrate descriptors (electrophilicity, size, and flexibility) that govern the rate of NotF-catalyzed prenyltransfer, and the development of an "induced fit docking (IFD)-guided" engineering strategy for improved turnover of our largest substrates. We further demonstrated the utility of NotF in tandem with oxidative cyclization using flavin monooxygenase, BvnB. This one-pot, in vitro biocatalytic cascade enabled the first chemoenzymatic synthesis of the marine fungal natural product, (-)-eurotiumin A, in three steps and 60% overall yield.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-technique characterization of iron reduction by an Antarctic Shewanella : an analog system for putative Martian biosignature identification

ABSTRACT Microbes from terrestrial extreme environments enable testing of biosignature production in conditions relevant to astrobiological targets. Mars, which was likely more conducive to life during early warmer and wetter epochs, has inspired missions that search for signs of early life in the surficial rock record, including mineral or organic biosignatures. Microbial iron reduction is a common and ancient metabolism that may have also operated on other rocky celestial bodies. To investigate biosignature production during iron reduction, aShewanellasp. (strain BF02_Schw) isolated from a subglacial discharge known as Blood Falls, Antarctica, was incubated with the electron acceptor ferrihydrite (Fh). Biosignatures associated with Fh reduction were identified using a suite of techniques currently utilized or proposed for Mars missions, including X-ray diffraction and infrared, Mössbauer, and Raman spectroscopy. The biotic origin of features was validated by transcriptional changes observed between treatments with and without Fh and comparison to killed controls. In live treatments, Fh was reduced to magnetite and goethite, both detected in Martian lacustrine basins. Several soluble and volatile metabolites were also detected, including riboflavin and dimethyl sulfide (DMS), which could be astrobiological indicators of active microbial processes. While none of the identified biosignatures individually would serve as definitive proof of life (past or present), detecting concomitant features associated with known terrestrial biotic processes would provide compelling rationale for more targeted life detection missions. Terrestrial extremophiles can support the exploration of astrobiologically relevant microbial processes, validation of life detection instrumentation, and potentially the discovery of new biomarkers. IMPORTANCE Culture-based experiments with terrestrial extremophiles can elucidate biosignatures that may be analogous to those produced under extraterrestrial conditions, and thus inform sampling and technology strategies for future missions. Here, we demonstrate the production of several biosignatures under iron-reducing conditions byShewanellasp. BF02_Schw, originally isolated from an Antarctic analog feature. These biosignatures could be detectable using flight-ready instrumentation. Growth experiments with terrestrial extremophiles can identify biosignatures measurable by current methodologies and inform the development and optimization of techniques for detecting extant or extinct life on other worlds.

Biotechnology & Applied Microbiology↗

Neutral Loss Mass Spectral Data Enhances Molecular Similarity Analysis in $\mathrm{METLIN}$

We report Neutral loss (NL) spectral data presents a mirror of MS 2 data and is a valuable yet largely untapped resource for molecular discovery and similarity analysis. Tandem mass spectrometry (MS 2 ) data is effective for the identification of known molecules and the putative identification of novel, previously uncharacterized molecules (unknowns). Yet, MS 2 data alone is limited in characterizing structurally related molecules. To facilitate unknown identification and complement the METLIN-MS 2 fragment ion database for characterizing structurally related molecules, we have created a MS 2 to NL converter as a part of the METLIN platform. The converter has been used to transform METLIN’s MS 2 data into a neutral loss database (METLIN-NL) on over 860 000 individual molecular standards. The platform includes both the MS 2 to NL converter and a graphical user interface enabling comparative analyses between MS 2 and NL data. Examples of NL spectral data are shown with oxylipin analogues and two structurally related statin molecules to demonstrate NL spectra and their ability to help characterize structural similarity. Mirroring MS 2 data to generate NL spectral data offers a unique dimension for chemical and metabolite structure characterization.

59 BASIC BIOLOGICAL SCIENCES↗

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology↗

Swimming and the human microbiome at the intersection of sports, clinical, and environmental sciences: A scoping review of the literature

The human microbiota is comprised of more than 10–100 trillion microbial taxa and symbiotic cells. Two major human sites that are host to microbial communities are the gut and the skin. Physical exercise has favorable effects on the structure of human microbiota and metabolite production in sedentary subjects. Recently, the concept of “athletic microbiome” has been introduced. To the best of our knowledge, there exists no review specifically addressing the potential role of microbiomics for swimmers, since each sports discipline requires a specific set of techniques, training protocols, and interactions with the athletic infrastructure/facility. Therefore, to fill in this gap, the present scoping review was undertaken. Four studies were included, three focusing on the gut microbiome, and one addressing the skin microbiome. It was found that several exercise-related variables, such as training volume/intensity, impact the athlete’s microbiome, and specifically the non-core/peripheral microbiome, in terms of its architecture/composition, richness, and diversity. Swimming-related power-/sprint- and endurance-oriented activities, acute bouts and chronic exercise, anaerobic/aerobic energy systems have a differential impact on the athlete’s microbiome. Therefore, their microbiome can be utilized for different purposes, including talent identification, monitoring the effects of training methodologies, and devising ad hoc conditioning protocols, including dietary supplementation. Microbiomics can be exploited also for clinical purposes, assessing the effects of exposure to swimming pools and developing potential pharmacological strategies to counteract the insurgence of skin infections/inflammation, including acne. In conclusion, microbiomics appears to be a promising tool, even though current research is still limited, warranting, as such, further studies.

59 BASIC BIOLOGICAL SCIENCES↗

Natural Product Gene Clusters in the Filamentous Nostocales Cyanobacterium HT-58-2

Cyanobacteria are known as rich repositories of natural products. One cyanobacterial-microbial consortium (isolate HT-58-2) is known to produce two fundamentally new classes of natural products: the tetrapyrrole pigments tolyporphins A–R, and the diterpenoid compounds tolypodiol, 6-deoxytolypodiol, and 11-hydroxytolypodiol. The genome (7.85 Mbp) of the Nostocales cyanobacterium HT-58-2 was annotated previously for tetrapyrrole biosynthesis genes, which led to the identification of a putative biosynthetic gene cluster (BGC) for tolyporphins. Here, bioinformatics tools have been employed to annotate the genome more broadly in an effort to identify pathways for the biosynthesis of tolypodiols as well as other natural products. A putative BGC (15 genes) for tolypodiols has been identified. Four BGCs have been identified for the biosynthesis of other natural products. Two BGCs related to nitrogen fixation may be relevant, given the association of nitrogen stress with production of tolyporphins. The results point to the rich biosynthetic capacity of the HT-58-2 cyanobacterium beyond the production of tolyporphins and tolypodiols.

60 APPLIED LIFE SCIENCES↗

A Quantitative Study of Oxygen as a Metabolic Regulator

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Radhakrishnan, Krishnan↗

ISS Technology Demonstrations for Future Spaceflight Medical Systems

Throughout the history of human spaceflight, crewmembers have experienced various in-flight medical conditions including illness and injury. Planned missions to the Moon and Mars will require capabilities to maintain the health of future space travelers. Mass, power, and volume available in the vehicles and habitats for these missions will be severely constrained; resupply of resources will be limited or non-existent, as will opportunities for evacuation to Earth. Furthermore, ground-based support will be hampered by communication latencies and blackouts. These vehicle and mission constraints will necessitate a medical system that has been efficiently planned, providing on-board procedural guidance in addition to a variety of medical devices and consumable resources. Medical capabilities required for the diagnosis and treatment of potential medical conditions during future spaceflight missions may include real-time health monitoring, medical imaging, and biomarker analyses ( e.g., blood or urine). Terrestrial medicine shares these needs, thus many of these medical capabilities could likely be satisfied by Commercial-Off-The-Shelf (COTS) devices and methodologies; however, in some cases the unique space environment and increased mission duration will drive the need to modify technologies and the way care is provided. NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) Element and Mars Campaign Office’s Exploration Medical Integrated Product Team (XMIPT) are working together to decrease medical risk during exploration missions. Flight-tested medical diagnostic and treatment technologies are necessary to effectively manage medical conditions relevant to exploration missions while meeting vehicle constraints, integrating with medical decision-support tools, and enabling increasingly Earth-independent operations. Several projects have leveraged the ISS as a testbed for exploration, including 1) i n- situ blood analysis, 2) medical inventory, 3) intravenous fluid generation, and 4) autonomous medical procedure guidance. Management of several in-flight medical conditions, such as bacterial and viral infections and acute radiation syndrome, is dramatically improved with ability to assess blood cell populations, electrolytes, and metabolites. I n December 2020 and January 2021 ExMC performed an ISS technology demonstration (Tech Demo) of the HemoCue® WBC DIFF analyzer (HemoCue, Brea, CA), a COTS device that was modified to enable functionality in a spaceflight environment. This Tech Demo marked the first time that hematology measurements were successfully performed real-time in microgravity. Also modified and demonstrated was the reusable Handheld Electrolytes and Lab Technology for Humans (rHEALTH) ONE analyzer (rHEALTH, Bedford, MA), which uses flow cytometry and sheath-based hydrodynamic focusing methodologies. The rHEALTH ONE ISS Tech Demo in May 2022 demonstrated test results obtained in-flight matched those on the ground. NASA currently relies on crew self-reporting to manage and maintain medical inventory on ISS.The ability to maintain an accurate inventory becomes more critical during long duration missions since the crew will need to be increasingly autonomous in finding and utilizing medical items, including those scenarios when alternative treatments need to be considered due to limited or no resupply. HRP’s Medical Consumables Tracking (MCT) project was developed by ZIN Technologies, Inc. (Cleveland, OH), and demonstrated real-time tracking of medical supplies aboard the ISS between December 2016 and July 2018. The MCT system design utilized Radio Frequency Identification Device (RFID) technology to perform automated inventory and was installed in the Crew Health Care System (CHeCS) Resupply Stowage Rack (RSR). The challenge of limited shelf life, exacerbated by the lack of resupply opportunities, affects a plethora of medical system components including consumables, pharmaceuticals, and intravenous (IV) fluid. In 2010, ExMC funded ZIN Technologies, Inc. (Cleveland, OH), to develop the Intravenous Fluid Generation (IVGEN) system. IV fluids were successfully generated with IVGEN using the potable water supply on ISS during ISS Expedition 23. The XMIPT is in the process of developing a miniaturized version of the original IVGEN hardware for a future Tech Demo aboard the ISS. Current ISS medical operations rely heavily on preflight training and real-time remote guidance, both of which become impractical or impossible for exploration missions. The primary goal of the Autonomous Medical Officer Support (AMOS) Software Tech Demos on ISS was to confirm telemedical proof-of-concept for autonomous medical imaging in an operational setting. This novel software tool shifts emphasis from preflight training and real-time remote guidance to in-flight just-in-time instruction, a new and necessary paradigm for crew medical autonomy. AMOS introduces a novel, streamlined skill management concept for exploration missions featuring comprehensive training and guidance modules for ultrasound examinations using the ISS Ultrasound 2 (a modified GE Vivid-q™; General Electric HealthCare, Chicago, IL). With no prior crew training or remote guidance, two Tech Demos on the ISS (April 2020 and June 2022) resulted in high quality, clinically useful image sets. We will provide a review of historical, current, and planned medical devices and technologies considered for inclusion within future spaceflight medical systems and summarize hardware development activities and medical device tech demos conducted on the ISS.

Astronaut health and performance↗