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Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

NASA NTRS1999

Plasma membrane ordering agent pluronic F-68 (PF-68) reduces neurotransmitter uptake and release and produces learning and memory deficits in rats

A substantial body of evidence indicates that aged-related changes in the fluidity and lipid composition of the plasma membrane contribute to cellular dysfunction in humans and other mammalian species. In the CNS, reductions in neuronal plasma membrane order (PMO) (i.e., increased plasma membrane fluidity) have been attributed to age as well as the presence of the beta-amyloid peptide-25-35, known to play an important role in the neuropathology of Alzheimer's disease (AD). These PMO increases may influence neurotransmitter synthesis, receptor binding, and second messenger systems as well as signal transduction pathways. The effects of neuronal PMO on learning and memory processes have not been adequately investigated, however. Based on the hypothesis that an increase in PMO may alter a number of aspects of synaptic transmission, we investigated several neurochemical and behavioral effects of the membrane ordering agent, PF-68. In cell culture, PF-68 (nmoles/mg SDS extractable protein) reduced [3H]norepinephrine (NE) uptake into differentiated PC-12 cells as well as reduced nicotine stimulated [3H]NE release. The compound (800-2400 microg/kg, i.p., resulting in nmoles/mg SDS extractable protein in the brain) decreased step-through latencies and increased the frequencies of crossing into the unsafe side of the chamber in inhibitory avoidance training. In the Morris water maze, PF-68 increased the latencies and swim distances required to locate a hidden platform and reduced the time spent and distance swam in the previous target quadrant during transfer (probe) trials. PF-68 did not impair performance of a well-learned working memory task, the rat delayed stimulus discrimination task (DSDT), however. Studies with 14C-labeled PF-68 indicated that significant (pmoles/mg wet tissue) levels of the compound entered the brain from peripheral (i.p.) injection. No PF-68 related changes were observed in swim speeds or in visual acuity tests in water maze experiments, rotorod performance, or in tests of general locomotor activity. Furthermore, latencies to select a lever in the DSDT were not affected. These results suggest that PF-68 induced deficits in learning and memory without confounding peripheral motor, sensory, or motivational effects at the tested doses. Furthermore, none of the doses induced a conditioned taste aversion to a novel 0.1% saccharin solution indicating a lack of nausea or gastrointestinal malaise induced by the compound. The data indicate that increases in neuronal plasma membrane order may have significant effects on neurotransmitter function as well as learning and memory processes. Furthermore, compounds such as PF-68 may also offer novel tools for studying the role of neuronal PMO in mnemonic processes and changes in PMO resulting from age-related disorders such as AD.

Poloxamer/pharmacology↗

NASA NTRS2005

Use of a Novel Rover-mounted Fluorescence Imager and Fluorescent Probes to Detect Biological Material in the Atacama Desert in Daylight

We have developed an imaging system, the Fluorescence Imager (FI), for detecting fluorescence signals from sparse microorganisms and biofilms during autonomous rover exploration. The fluorescence signals arise both from naturally occurring chromophores, such as chlorophyll of cyanobacteria and lichens, and from fluorescent probes applied to soil and rocks. Daylight imaging has been accomplished by a novel use of a high-powered flashlamp synchronized to a CCD camera. The fluorescent probes are cell permanent stains that have extremely low intrinsic fluorescence (quantum yields less than 0.01) and a large fluorescence enhancement (quantum yields greater than 0.4) when bound to the target. Each probe specifically targets either carbohydrates, proteins, nucleic acids or membrane lipids, the four classes of macromolecules found in terrestrial life. The intent of the probes is to interrogate the environment for surface and endolithic life forms.

Weinstein, S.↗

NASA NTRS2008

Progress in Development of Improved Ion-Channel Biosensors

Further improvements have recently been made in the development of the devices described in Improved Ion-Channel Biosensors (NPO-30710), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 30. As discussed in more detail in that article, these sensors offer advantages of greater stability, greater lifetime, and individual electrical addressability, relative to prior ion-channel biosensors. In order to give meaning to a brief description of the recent improvements, it is necessary to recapitulate a substantial portion of the text of the cited previous article. The figure depicts one sensor that incorporates the recent improvements, and can be helpful in understanding the recapitulated text, which follows: These sensors are microfabricated from silicon and other materials compatible with silicon. Typically, the sensors are fabricated in arrays in silicon wafers on glass plates. Each sensor in the array can be individually electrically addressed, without interference with its neighbors. Each sensor includes a well covered by a thin layer of silicon nitride, in which is made a pinhole for the formation of a lipid bilayer membrane. In one stage of fabrication, the lower half of the well is filled with agarose, which is allowed to harden. Then the upper half of the well is filled with a liquid electrolyte (which thereafter remains liquid) and a lipid bilayer is painted over the pinhole. The liquid contains a protein that forms an ion channel on top of the hardened agarose. The combination of enclosure in the well and support by the hardened agarose provides the stability needed to keep the membrane functional for times as long as days or even weeks. An electrode above the well, another electrode below the well, and all the materials between the electrodes together constitute a capacitor. What is measured is the capacitive transient current in response to an applied voltage pulse. One notable feature of this sensor, in comparison with prior such sensors, is a relatively thick dielectric layer between the top of the well and the top electrode. This layer greatly reduces the capacitance of an aperture across which the ion channels are formed, thereby increasing the signal-to-noise ratio. The use of a relatively large aperture with agarose support makes it possible to form many ion channels instead of only one, thereby further increasing the signal-to-noise ratio and effectively increasing the size of the available ionic reservoir. The relatively large reservoir makes it possible to measure AC rather than DC. This concludes the recapitulation from the cited previous article.

Nadeau, Jay L.↗

NASA NTRS2001

Visualization of Microbial Biomarkers by Scanning Electron Microscopy

We are developing tools to link the biochemical structure of selected biomarkers with putative biogenic structures observed in mineralized samples. The detection of evidence of life on Mars and other planets will rely on methods that can discriminate compounds formed exclusively by living organisms. While biogenic compounds, such as amino acids and nucleotides have been discovered in extraterrestrial sources, such as meteorites and comets, their formation can be explained by abiotic means. The formation of cellular structures, or more elaborate organic molecules, such as complex lipids, proteins or nucleic acids, however, is strongly correlated to the presence of even the most primitive life processes. Recent evidence lends support to the hypothesis that life may have once existed on Mars. Carbonate globules and ppm concentrations of polycyclic aromatic hydrocarbons (PAHs) have been described in ALH84001, a meteorite originating from Mars ejecta captured by Earth over 13,000 years ago. The localized high concentration of PAHs that follow an increasing gradient from the intact fusion crust towards the interior corresponds to microgram quantities of hydrocarbon. Even though ALH84001 and other similar meteorites have withstood the forces capable of ejecting rock through Mars' escape velocity, upon entering Earth's atmosphere, their core temperatures are likely not to have been raised significantly, as evidenced by the survival of remanent magnetic signatures. Ideal biomarkers of ancient or modern biological life would include molecules that are (or were) pervasive and highly resistant to degradation. Also, requisite methods of detection should be simple, extremely sensitive and broadly inclusive (NASA SP-530). Lipopolysaccharide (LPS), peptidoglycan or pseudopeptidoglycan and beta-glucan are microbial cell wall components which together cover the entire microbial spectrum of eubacteria, archea and fungi. They are all remarkably resistant to thermal degradation. Fortunately, many antimicrobial defense systems of higher organisms require sensitive detection to combat microbial pathogens. We employ here the primitive immune system of the evolutionarily ancient horseshoe crab, Limulus polyphemus. This species relies on multi-enzyme signal amplification detection of cell wall molecules and they can be applied to the development of useful detectors of life. An extension of this work includes the visualization of microbial signatures by labeling LAL components with chromogenic or electron dense markers. The protein Limulus Anti-LPS Factor (LALF) has an extremely high affinity for LPS. By coupling LALF binding with colloidal gold labels we demonstrate a correlation of the structures visible by electron microscopy with biochemical evidence of microbial cell wall materials. Pure silica particles were mixed with cultures of E. coli (10(exp 6) cfu/mL). Samples were washed sequentially with buffered saline, LALF, antibody to LALF and finally colloidal gold-labeled Protein A. Negative controls were not exposed to E. coli but received identical treatment otherwise. Samples were coated with carbon and imaged on a JEOL JSM-840 scanning electron microscope with LaB6 source in the back scatter mode with the JEOL annular back scatter detector. 20 nm-scale black spots in this contrast-reversed image originate from electrons back-scattered by gold atoms. Negative controls did not give any signal. Future work will expand application of this technique to soil simulants and mineralized rock samples.

Wainwright, Norman R.↗