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NASA NTRS2015

GeneLab: A Systems Biology Platform for Spaceflight Omics Data

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. Resources to support large numbers of spaceflight investigations are limited. NASA's GeneLab project is maximizing the science output from these experiments by: (1) developing a unique public bioinformatics database that includes space bioscience relevant "omics" data (genomics, transcriptomics, proteomics, and metabolomics) and experimental metadata; (2) partnering with NASA-funded flight experiments through bio-sample sharing or sample augmentation to expedite omics data input to the GeneLab database; and (3) developing community-driven reference flight experiments. The first database, GeneLab Data System Version 1.0, went online in April 2015. V1.0 contains numerous flight datasets and has search and download capabilities. Version 2.0 will be released in 2016 and will link to analytic tools. In 2015 Genelab partnered with two Biological Research in Canisters experiments (BBRIC-19 and BRIC-20) which examine responses of Arabidopsis thaliana to spaceflight. GeneLab also partnered with Rodent Research-1 (RR1), the maiden flight to test the newly developed rodent habitat. GeneLab developed protocols for maxiumum yield of RNA, DNA and protein from precious RR-1 tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected. GeneLab is establishing partnerships with at least three planned flights for 2016. Organism-specific nationwide Science Definition Teams (SDTs) will define future GeneLab dedicated missions and ensure the broader scientific impact of the GeneLab missions. GeneLab ensures prompt release and open access to all high-throughput omics data from spaceflight and ground-based simulations of microgravity and radiation. Overall, GeneLab will facilitate the generation and query of parallel multi-omics data, and deep curation of metadata for integrative analysis, allowing researchers to uncover cellular networks as observed in systems biology platforms. Consequently, the scientific community will have access to a more complete picture of functional and regulatory networks responsive to the spaceflight environment.. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and enable emerging terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space. As a result, open access to the data will foster new hypothesis-driven research for future spaceflight studies spanning basic science to translational science.

proteomics↗

DOE OSTI2019

Data from pH Selectively Regulates Citric Acid and Lipid Production in Yarrowia lipolytica W29 During Nitrogen-limited Growth on Glucose

Yarrowia lipolytica has been used to produce both citric acid and lipid-based bioproducts at high titers. In this study, we found that pH differentially affects citric acid and lipid production in Y. lipolytica W29, with citric acid production enhanced at more neutral pH’s and lipid production enhanced at more acid pH’s. To determine the mechanism governing this pH-dependent switch between citric acid and lipid production, we profiled gene expression at different pH’s and found that the relative expression of multiple transporters is increased at neutral pH. These results suggest that this pH-dependent switch is mediated at the level of citric acid transport rather than changes in the expression of the enzymes involved in citric acid and lipid metabolism. In further support of this mechanism, thermodynamic calculations suggest that citric acid secretion is more energetically favorable at neutral pH’s, assuming the fully protonated acid is the substrate for secretion. Collectively, these results provide new insights regarding citric acid and lipid production in Y. lipolytica and may offer new strategies for metabolic engineering and process design.

Conversion↗

DOE OSTI2016

Equol inhibits growth, induces atresia, and inhibits steroidogenesis of mouse antral follicles in vitro

Equol is a non-steroidal estrogen metabolite produced by microbial conversion of daidzein, a major soy isoflavone, in the gut of some humans and many animal species. Isoflavones and their metabolites can affect endogenous estradiol production, action, and metabolism, potentially influencing ovarian follicle function. However, no studies have examined the effects of equol on intact ovarian antral follicles, which are responsible for sex steroid synthesis and further development into ovulatory follicles. Thus, the present study tested the hypothesis that equol inhibits antral follicle growth, increases follicle atresia, and inhibits steroidogenesis in the adult mouse ovary. To test this hypothesis, antral follicles isolated from adult CD-1 mice were cultured with vehicle control (dimethyl sulfoxide; DMSO) or equol (600 nM, 6 μM, 36 μM, and 100 μM) for 48 and 96 h. Every 24 h, follicle diameters were measured to monitor growth. At 48 and 96 h, the culture medium was subjected to measurement of hormone levels, and the cultured follicles were subjected to gene expression analysis. Additionally, follicles were histologically evaluated for signs of atresia after 96 h of culture. The results indicate that equol (100 μM) inhibited follicle growth, altered the mRNA levels of bcl2-associated X protein and B cell leukemia/lymphoma 2, and induced follicle atresia. Further, equol decreased the levels of estradiol, testosterone, androstenedione, and progesterone, and it decreased mRNA levels of cholesterol side-chain cleavage, steroid 17-α-hydroxalase, and aromatase. Collectively, these data indicate that equol inhibits growth, increases atresia, and inhibits steroidogenesis of cultured mouse antral follicles. - Highlights: • Equol exposure inhibits antral follicle growth. • Equol exposure increases follicle atresia. • Equol exposure inhibits sex steroid hormone levels. • Equol exposure inhibits mRNA levels of certain steroidogenic enzymes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

miR-125b targets DNMT3b and mediates p53 DNA methylation involving in the vascular smooth muscle cells proliferation induced by homocysteine

MicroRNAs (miRNAs) are short non-coding RNA and play crucial roles in a wide array of biological processes, including cell proliferation, differentiation and apoptosis. Our previous studies found that homocysteine(Hcy) can stimulate the proliferation of vascular smooth muscle cells (VSMCs), however, the underlying mechanisms were not fully elucidated. Here, we found proliferation of VSMCs induced by Hcy was of correspondence to the miR-125b expression reduced both in vitro and in the ApoE knockout mice, the hypermethylation of p53, its decreased expression, and DNA (cytosine-5)-methyltransferase 3b (DNMT3b) up-regulated. And, we found DNMT3b is a target of miR-125b, which was verified by the Dual-Luciferase reporter assay and western blotting. Besides, the siRNA interference for DNMT3b significantly decreased the methylation level of p53, which unveiled the causative role of DNMT3b in p53 hypermethylation. miR-125b transfection further confirmed its regulative roles on p53 gene methylation status and the VSMCs proliferation. Our data suggested that a miR-125b-DNMT3b-p53 signal pathway may exist in the VSMCs proliferation induced by Hcy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Dynamic enhancer landscapes in human craniofacial development

The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

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

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Metatranscriptomic Analysis Reveals Unexpectedly Diverse Microbial Metabolism in a Biogeochemical Hot Spot in an Alluvial Aquifer

Organic matter deposits in alluvial aquifers have been shown to result in the formation of naturally reduced zones (NRZs), which can modulate aquifer redox status and influence the speciation and mobility of metals, affecting groundwater geochemistry. In this study, we sought to better understand how natural organic matter fuels microbial communities within anoxic biogeochemical hot spots (NRZs) in a shallow alluvial aquifer at the Rifle (CO) site. We conducted a 20-day microcosm experiment in which NRZ sediments, which were enriched in buried woody plant material, served as the sole source of electron donors and microorganisms. The microcosms were constructed and incubated under anaerobic conditions in serum bottles with an initial N 2 headspace and were sampled every 5 days for metagenome and metatranscriptome profiles in combination with biogeochemical measurements. Biogeochemical data indicated that the decomposition of native organic matter occurred in different phases, beginning with mineralization of dissolved organic matter (DOM) to CO 2 during the first week of incubation, followed by a pulse of acetogenesis that dominated carbon flux after 2 weeks. A pulse of methanogenesis co-occurred with acetogenesis, but only accounted for a small fraction of carbon flux. The depletion of DOM over time was strongly correlated with increases in expression of many genes associated with heterotrophy (e.g., amino acid, fatty acid, and carbohydrate metabolism) belonging to a Hydrogenophaga strain that accounted for a relatively large percentage (~8%) of the metatranscriptome. This Hydrogenophaga strain also expressed genes indicative of chemolithoautotrophy, including CO 2 fixation, H 2 oxidation, S-compound oxidation, and denitrification. The pulse of acetogenesis appears to have been collectively catalyzed by a number of different organisms and metabolisms, most prominently pyruvate:ferredoxin oxidoreductase. Unexpected genes were identified among the most highly expressed (>98th percentile) transcripts, including acetone carboxylase and cell-wall-associated hydrolases with unknown substrates (numerous lesser expressed cell-wall-associated hydrolases targeted peptidoglycan). Many of the most highly expressed hydrolases belonged to a Ca . Bathyarchaeota strain and may have been associated with recycling of bacterial biomass. Overall, these results highlight the complex nature of organic matter transformation in NRZs and the microbial metabolic pathways that interact to mediate redox status and elemental cycling.

Hydrogenophaga↗

NASA NTRS2024

Space Algae-2 Ground and Lunar Analog Studies in Preparation for Long-Duration Propagation of Cyanobacteria in Spaceflight

There are numerous applications for microalgae in spaceflight missions and on Earth, such as oxygen production, carbon dioxide removal, nutrition, wastewater processing, and biofuel production. Space Algae-2 aims to test the genetic stability of Arthrospira platensis, commonly known as spirulina, during six-months of continuous culture on the International Space Station. Long-duration exposure to ionizing radiation and microgravity may impact growth, nutrient composition, and genetic stability. The high protein, vitamin, antioxidant content, and radiation resistance make spirulina a promising candidate for bioregenerative life support systems. A concept of operations was developed to grow and harvest algal biomass in space. Preflight testing experiments optimized conditions for an extended growth period in a gas permeable bioreactor bag. Preflight and post-harvest storage methods were developed in addition to a novel cryopreservation method. After sample return, multi-omics analysis will be conducted to determine the mutation rate, gene expression, and the protein and metabolite profile. The concept of operations for Space Algae-2 was tested during a lunar mission simulation within a semi-controlled environment. During a six-day lunar analog mission at the Hawai’i Space Exploration Analog and Simulation (HI-SEAS) A. platensis was successfully grown using flight-like hardware. The cyanobacteria were harvested and used to supplement bread as an example of spirulina biomass utilization. Overall, the data collected from Space Algae-2 will inform potential bioengineering of spirulina for space and terrestrial applications.

Algae↗

NASA NTRSDate not supplied

Space Algae-2 Ground and Lunar Analog Studies in Preparation for Long-Duration Propagation of Cyanobacteria in Spaceflight

Algae↗

DOE OSTI2018

FBXW 7 deletion contributes to lung tumor development and confers resistance to gefitinib therapy

Gefitinib, an epidermal growth factor receptor–tyrosine kinase inhibitor ( EGFR ‐ TKI ), is an effective treatment for non‐small‐cell lung cancer ( NSCLC ) with EGFR activating mutations, but inevitably, the clinical efficacy is impeded by the emergence of acquired resistance. The tumor suppressor gene FBXW 7 modulates chemosensitivity in various human cancers. However, its role in EGFR ‐ TKI therapy in NSCLC has not been well studied. Here, we demonstrate that the mice with deficient Fbxw7 have greater susceptibility to urethane‐induced lung tumor development. Through analysis of The Cancer Genome Atlas data, we show that deletion of FBXW 7 occurs in 30.9% of lung adenocarcinomas and 63.5% of lung squamous cell carcinomas, which significantly leads to decrease in FBXW 7 mRNA expression. The reduction in FBXW 7 mRNA level is associated with poor overall survival in lung cancer patients. FBXW 7 knockdown dramatically promotes epithelial–mesenchymal transition, migration, and invasion in NSCLC cells. Moreover, with silenced FBXW 7, EGFR ‐ TKI ‐sensitive cells become resistant to gefitinib, which is reversed by the mammalian target of rapamycin inhibitor, rapamycin. Furthermore, xenograft mouse model studies show that FBXW 7 knockdown enhances tumorigenesis and resistance to gefitinib. Combination of gefitinib with rapamycin treatment suppresses tumor formation of gefitinib‐resistant (GR) FBXW 7‐knockdown cells. In conclusion, our findings suggest that loss of FBXW 7 promotes NSCLC progression as well as gefitinib resistance and combination of gefitinib and rapamycin may provide an effective therapy for GR NSCLC.

Oncology↗

DOE OSTI2018

Lenalidomide regulates osteocytes fate and related osteoclastogenesis via IL-1β/NF-κB/RANKL signaling

Highlights: • Lenalidomide regulated IL-1β induced osteocyte fate with decreased expressions of RANKL and Sclerostin. • Lenalidomide inhibited subsequent osteoclastogenesis via osteocytes. • Lenalidomide inactivated NF-κB signaling in osteocytes to reduce osteoclast formation. • Lenalidomide attenuated in vivo osteocyte apoptosis and following osteoclastogenesis in osteoarthritis mice. Osteolytic diseases are closely associated with osteocyte fate, indicating a more efficient and crucial role of osteocyte-targeting strategy in inhibiting osteoclastogenesis. Here, we investigated the effects of lenalidomide (Lena) on osteocyte fate in order to regulate osteoclastogenesis via effective cascade-controlling response. Our data revealed that lenalidomide treatment notably rescued IL-1β induced loss of osteocyte viability by inhibiting osteocyte apoptosis with decreased osteoclast-related factors, RANKL and Sclerostin, as demonstrated by the restricted osteoclast formation and reduced bone resorption. Additionally, iTRAQ assay revealed that IL-1β induced activation of NF-κB inhibitor α/β were remarkably downregulated by lenalidomide, showing that lenalidomide impaired NF-κB signaling in osteocytes for inhibiting the expression of osteoclast specific genes in osteoclasts, which was further confirmed by KEGG pathway analysis and Western blot. More interestingly, the in vivo analysis of osteocyte apoptosis and osteoclastogenesis in osteoarthritis mice model indicated a role of lenalidomide in the regulation of osteocyte fate and the consequent inhibition of RANKL-induced osteoclastogenesis. Together, these results suggest that lenalidomide regulates osteocyte fate by attenuating IL-1β/NF-κB signaling, thereby inhibiting RANKL expression for the attenuated osteoclastogenesis both in vitro and vivo, indicating a more efficient remedy among future anti-osteoclastogenesis approaches.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Energy metabolic capacities of human adipose-derived mesenchymal stromal cells in vitro and their adaptations in osteogenic and adipogenic differentiation

Highlights: • Mesenchymal differentiation of adMSC causes adaptations of the energy metabolism. • Mesenchymal differentiation of adMSC comes along with changes in cell proliferation. • Osteogenic differentiation entails an increase of all metabolic pathways tested. • Adipogenic differentiation entails a decreasing capacity of carbohydrate metabolism. • Adipogenic differentiation indicates a shift towards lipid metabolism. Mesenchymal stromal/stem cells (MSC) are important in tissue homeostasis and regeneration due to their ability for self-renewal and multipotent differentiation. Differentiation, as well as proliferation, requires adaptations in the cell metabolism. However, only few data exist concerning the energy metabolism of non-differentiating and differentiating MSC. In this study we compared capacities of major energy metabolic pathways of MSC from human adipose tissue (adMSC) in vitro in the non-differentiated state with those of osteogenically or adipogenically differentiating adMSC. To this end we quantified the proliferation and differentiation status of adMSC and analyzed maximum enzyme capacities and several enzyme isoforms of major energy metabolic pathways regarding their activity and gene expression. We could show that non-differentiating and osteogenic cultivation conditions induced proliferation and showed increasing capacities of the glycolytic marker enzyme phosphofructokinase as well as the marker enzyme of the pentose phosphate pathway glucose-6-phosphate dehydrogenase. Adipogenic stimulation, which was accompanied by the absence of proliferation, reduced the glycolytic capacity (e.g. decreased glyceraldehyde 3-phosphate dehydrogenase capacity) and induced an increase in mitochondrial enzyme capacities. These changes in energy metabolism might represent an adaptation of adMSC to the high energy demand during proliferation and to the specific cellular functions during osteogenic or adipogenic differentiation respectively.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-DE-207B-05: Predicting Gene Mutations in Renal Cell Carcinoma Based On CT Imaging Features: Validation Using TCGA-TCIA Datasets

Purpose: The goal of this work is to investigate the use of contrast enhanced computed tomographic (CT) features for the prediction of mutations of BAP1, PBRM1, and VHL genes in renal cell carcinoma (RCC). Methods: For this study, we used two patient databases with renal cell carcinoma (RCC). The first one consisted of 33 patients from our institution (UT Southwestern Medical Center, UTSW). The second one consisted of 24 patients from the Cancer Imaging Archive (TCIA), where each patient is connected by a unique identi?er to the tissue samples from the Cancer Genome Atlas (TCGA). From the contrast enhanced CT image of each patient, tumor contour was first delineated by a physician. Geometry, intensity, and texture features were extracted from the delineated tumor. Based on UTSW dataset, we completed feature selection and trained a support vector machine (SVM) classifier to predict mutations of BAP1, PBRM1 and VHL genes. We then used TCIA-TCGA dataset to validate the predictive model build upon UTSW dataset. Results: The prediction accuracy of gene expression of TCIA-TCGA patients was 0.83 (20 of 24), 0.83 (20 of 24), and 0.75 (18 of 24) for BAP1, PBRM1, and VHL respectively. For BAP1 gene, texture feature was the most prominent feature type. For PBRM1 gene, intensity feature was the most prominent. For VHL gene, geometry, intensity, and texture features were all important. Conclusion: Using our feature selection strategy and models, we achieved predictive accuracy over 0.75 for all three genes under the condition of using patient data from one institution for training and data from other institutions for testing. These results suggest that radiogenomics can be used to aid in prognosis and used as convenient surrogates for expensive and time consuming gene assay procedures.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Transient knockdown of Anopheles stephensi LRIM1 using RNAi increases Plasmodium falciparum sporozoite salivary gland infections

Abstract Background Plasmodium falciparum (Pf) sporozoites (PfSPZ) can be administered as a highly protective vaccine conferring the highest protection seen to date. Sanaria® PfSPZ vaccines are produced using aseptically reared Anopheles stephensi mosquitoes. The bionomics of sporogonic development of P. falciparum in A. stephensi to fully mature salivary gland PfSPZ is thought to be modulated by several components of the mosquito innate immune system. In order to increase salivary gland PfSPZ infections in A. stephensi and thereby increase vaccine production efficiency, a gene knock down approach was used to investigate the activity of the immune deficiency (IMD) signaling pathway downstream effector leucine-rich repeat immune molecule 1 ( LRIM1 ), an antagonist to Plasmodium development. Methods Expression of LRIM1 in A. stephensi was reduced following injection of double stranded (ds) RNA into mosquitoes. By combining the Gal4/UAS bipartite system with in vivo expression of short hairpin (sh) RNA coding for LRIM1 reduced expression of LRIM1 was targeted in the midgut, fat body, and salivary glands. RT-qPCR was used to demonstrate fold-changes in gene expression in three transgenic crosses and the effects on P. falciparum infections determined in mosquitoes showing the greatest reduction in LRIM1 expression. Results LRIM1 expression could be reduced, but not completely silenced, by expression of LRIM1 dsRNA. Infections of P. falciparum oocysts and PfSPZ were consistently and significantly higher in transgenic mosquitoes than wild type controls, with increases in PfSPZ ranging from 2.5- to tenfold. Conclusions Plasmodium falciparum infections in A. stephensi can be increased following reduced expression of LRIM1. These data provide the springboard for more precise knockout of LRIM1 for the eventual incorporation of immune-compromised A. stephensi into manufacturing of Sanaria’s PfSPZ products.

Billingsley, Peter F. (ORCID:0000000311424813)↗

DOE OSTI2021

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

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

Conversion↗

DOE OSTI2021

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants

Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food production. Biotic and abiotic stresses predominantly affect metabolite biosynthesis, gene and protein expression, and genome variations. However, light doses of stress result in the production of positive attributes in crops, like tolerance to stress and biosynthesis of metabolites, called hormesis. Advancement in artificial intelligence (AI) has enabled the development of high-throughput gadgets such as high-resolution imagery sensors and robotic aerial vehicles, i.e., satellites and unmanned aerial vehicles (UAV), to overcome biotic and abiotic stresses. These High throughput (HTP) gadgets produce accurate but big amounts of data. Significant datasets such as transportable array for remotely sensed agriculture and phenotyping reference platform (TERRA-REF) have been developed to forecast abiotic stresses and early detection of biotic stresses. For accurately measuring the model plant stress, tools like Deep Learning (DL) and Machine Learning (ML) have enabled early detection of desirable traits in a large population of breeding material and mitigate plant stresses. In this review, advanced applications of ML and DL in plant biotic and abiotic stress management have been summarized.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Combinations of Single Chain Variable Fragments From HIV Broadly Neutralizing Antibodies Demonstrate High Potency and Breadth

Broadly neutralizing antibodies (bNAbs) are currently being assessed in clinical trials for their ability to prevent HIV infection. Single chain variable fragments (scFv) of bNAbs have advantages over full antibodies as their smaller size permits improved diffusion into mucosal tissues and facilitates vector-driven gene expression. We have previously shown that scFv of bNAbs individually retain significant breadth and potency. Here we tested combinations of five scFv derived from bNAbs CAP256-VRC26.25 (V2-apex), PGT121 (N332-supersite), 3BNC117 (CD4bs), 8ANC195 (gp120-gp41 interface) and 10E8v4 (MPER). Either two or three scFv were combined in equimolar amounts and tested in the TZM-bl neutralization assay against a multiclade panel of 17 viruses. Experimental IC 50 and IC 80 data were compared to predicted neutralization titers based on single scFv titers using the Loewe additive and the Bliss-Hill model. Like full-sized antibodies, combinations of scFv showed significantly improved potency and breadth compared to single scFv. Combinations of two or three scFv generally followed an independent action model for breadth and potency with no significant synergy or antagonism observed overall although some exceptions were noted. The Loewe model underestimated potency for some dual and triple combinations while the Bliss-Hill model was better at predicting IC 80 titers of triple combinations. Given this, we used the Bliss-Hill model to predict the coverage of scFv against a 45-virus panel at concentrations that correlated with protection in the AMP trials. Using IC 80 titers and concentrations of 1μg/mL, there was 93% coverage for one dual scFv combination (3BNC117+10E8v4), and 96% coverage for two of the triple combinations (CAP256.25+3BNC117+10E8v4 and PGT121+3BNC117+10E8v4). Combinations of scFv, therefore, show significantly improved breadth and potency over individual scFv and given their size advantage, have potential for use in passive immunization.

60 APPLIED LIFE SCIENCES↗