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NASA NTRSDate not supplied

NASA GeneLab: Open Science for Life in Space

NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. The open-access GeneLab repository currently consists of over 300 omics datasets generated by biological experiments, involving various model organisms, that are relevant to spaceflight. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. To aide GeneLab’s efforts to harmonize and democratize space-relevant omics data, over 130 scientists have joined one of four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG) and together helped develop and adopted standard data analysis workflows for all data types available in GeneLab. Currently, the GeneLab Data System includes a data repository with federated search capability, an online controlled-access toolshed powered by "Galaxy" for users to process data with vetted standard workflows, a workspace for data sharing, a data submission portal, and the ability to browse and visualize transcriptomics processed data. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. The visualization portal enhances GeneLab’s ability to democratize omics data by removing the need for bioinformatics expertise to interpret transcriptomics data hosted on GeneLab. This presentation will provide an over-view of NASA’s GeneLab including how to navigate the GeneLab Data System and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

Working at NASA as a (Molecular) Biologist...

Trained as a biologist, I landed my first job at NASA as a mission scientist on the Rodent Research project. As a mission scientist, I led science activities associated with development, flight, and post-flight analysis of rodent research missions on the ISS in consultation with project engineers, operational specialists, mission PI(s), and mission Implementation Partner(s). I also assessed the feasibility of scientific experiments as a technical and scientific expert in rodent research on the ISS. Eager to learn more about the molecular changes that occur as a result of spaceflight exposure, I transitioned to the NASA GeneLab project where I eventually became the data processing lead. NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. During the CA Space Grant NASA Panel event, I will provide an overview of my work at NASA on both the Rodent Research and GeneLab projects and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

My Journey to NASA and role as a (Molecular) Biologist…

My journey to NASA started in undergrad, where I performed microbiology research and became hooked in the STEM fields. From there I earned a Ph.D. in Biochemistry and Molecular Biology from Mayo Graduate school where I performed Pancreatic Cancer research and then went on to perform postdoctoral research in Developmental Biology at the University of Miami. Trained as a biologist, I landed my first job at NASA as a mission scientist on the Rodent Research project. As a mission scientist, I led science activities associated with development, flight, and post-flight analysis of rodent research missions on the ISS in consultation with project engineers, operational specialists, mission PI(s), and mission Implementation Partner(s). I also assessed the feasibility of scientific experiments as a technical and scientific expert in rodent research on the ISS. Eager to learn more about the molecular changes that occur as a result of spaceflight exposure, I transitioned to the NASA GeneLab project where I eventually became the data processing lead. NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. To maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. During the CA Space Grant Women in STEM Panel event, I will provide an overview of my journey to NASA including my work at NASA on both the Rodent Research and GeneLab projects. I will conclude by providing resources for opportunities to work with GeneLab and NASA at large followed by links to programs designed specifically to engage women in STEM fields.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

My Journey to NASA and Role as a (Molecular) Biologist…

My journey to NASA started in undergrad, where I performed microbiology research and became hooked in the STEM fields. From there I earned a Ph.D. in Biochemistry and Molecular Biology from Mayo Graduate school where I performed Pancreatic Cancer research and then went on to perform postdoctoral research in Developmental Biology at the University of Miami. Trained as a biologist, I landed my first job at NASA as a mission scientist on the Rodent Research project. As a mission scientist, I led science activities associated with development, flight, and post-flight analysis of rodent research missions on the ISS in consultation with project engineers, operational specialists, mission PI(s), and mission Implementation Partner(s). I also assessed the feasibility of scientific experiments as a technical and scientific expert in rodent research on the ISS. Eager to learn more about the molecular changes that occur as a result of spaceflight exposure, I transitioned to the NASA GeneLab project where I eventually became the data processing lead. NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. To maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. During the NASA Ames ECN at Lincoln HS Virtual Panel event, I will provide an overview of my journey to NASA including my work at NASA on both the Rodent Research and GeneLab projects. I will conclude by providing resources for opportunities to work with GeneLab and NASA at large followed by links to programs designed specifically to engage women in STEM fields.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

RNASeq and Fluorescence Analysis of the Response of ERF2 and ERF104 in Arabidopsis thaliana under Simulated Altered Gravity

As NASA moves closer to long-term human space exploration, the need to understand how to sustain life in space is increasingly pressing. Plants are essential to human sustenance, making it important to understand how spaceflight affects plant health. We used differential gene expression analysis to examine GLDS-251 (RNAseq analysis of the response of Arabidopsis thaliana to fractional gravity under blue-light stimulation during spaceflight) from NASA’s GeneLab data repository and found downregulation of ERF2 and ERF104, transcription factors of the ethylene response factor families, that integrate hormonal pathways involved in abiotic stress responses. Downregulation of ERF2 and ERF104 during spaceflight may indicate a dysregulation of the ethylene signaling pathway. Our hypothesis is that altered gravity downregulates the expression of ERF2 and ERF104 in Arabidopsis thaliana, altering the ethylene signaling pathway and affecting the electron transport chain and light-dependent reactions in chloroplast thylakoids. To test this hypothesis, we propose to grow A. thaliana seedlings (wild-type and mutant/knockout of ERF2 and ERF104) in altered gravity conditions to determine the effects on the expression of ERF2, ERF104, and photosynthesis. We anticipate that ERF2 and ERF104 will be underexpressed in altered gravity conditions and result in decreased regulation of the ethylene signaling pathway.

Arabidopsis↗
NASA NTRSDate not supplied

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗
NASA NTRS2023

Uncovering Unique Molecular Adaptations in the Arabidopsis Thaliana Cvi-0 Ecotype

This research proposal aims to investigate the unique molecular adaptations exhibited by Arabidopsis Thaliana, specifically focusing on the Cape Verde Islands (Cvi-0) ecotype, in response to microgravity conditions. The study examines data from NASA’s Open Science Data Repository and applies a multifaceted RNAseq analysis pipeline using tools in the UseGalaxy.org open platform. Through transcriptomic analysis, differential gene expression patterns were identified in Cvi-0, revealing an absence of heat shock protein (HSP) upregulation and an upregulation of Rubisco Activase (RCA) and chloroplast-related pathways. To test the hypothesis that these adaptations may contribute to Cvi-0’s increased adaptability in microgravity, a three-fold experimental design is proposed. Four experimental groups will be cultivated under simulated microgravity and ground control conditions, including Cvi-0, Col-0, and genetically modified Col-0 with silenced HSP genes, and genetically modified Col-0 with upregulated RCA gene. Growth parameters will be measured to assess plant resilience, and RNA sequencing will provide transcriptomic data for pathway analysis. Anticipated outcomes include improved markers of plant health (mass, growth, etc.) of Cvi-0 in simulated microgravity and enhanced resilience in genetically altered Col-0 variants, providing insights into potential mechanisms of adaptation. This research would bear significance for space agriculture, nutrition for extended space missions, and sustainable terrestrial crop enhancement. Moreover, the insights gained could reshape crop engineering on Earth, enhancing robustness to climate induced stresses and bolstering global food security. The proposal’s trajectory blends scientific curiosity with practical applicability, forging a path towards sustainable food production and improving human exploration beyond our planet.

GL4HS↗
NASA NTRS1999

Delayed expression of hpS2 and prolonged expression of CIP1/WAF1/SDI1 in human tumour cells irradiated with X-rays, fission neutrons or 1 GeV/nucleon Fe ions

PURPOSE: Differences in gene expression underlie the phenotypic differences between irradiated and unirradiated cells. The goal was to identify late-transcribed genes following irradiations differing in quality, and to determine the RBE of 1 GeV/n Fe ions. MATERIALS AND METHODS: Clonogenic assay was used to determine the RBE of Fe ions. Differential hybridization to cDNA target clones was used to detect differences in expression of corresponding genes in mRNA samples isolated from MCF7 cells irradiated with iso-survival doses of Fe ions (0 or 2.5 Gy) or fission neutrons (0 or 1.2 Gy) 7 days earlier. Northern analysis was used to confirm differential expression of cDNA-specific mRNA and to examine expression kinetics up to 2 weeks after irradiation. RESULTS: Fe ion RBE values were between 2.2 and 2.6 in the lines examined. Two of 17 differentially expressed cDNA clones were characterized. hpS2 mRNA was elevated from 1 to 14 days after irradiation, whereas CIP1/WAF1/SDI1 remained elevated from 3 h to 14 days after irradiation. Induction of hpS2 mRNA by irradiation was independent of p53, whereas induction of CIP1/WAF1/SDI1 was observed only in wild-type p53 lines. CONCLUSIONS: A set of coordinately regulated genes, some of which are independent of p53, is associated with change in gene expression during the first 2 weeks post-irradiation.

NASA Discipline Radiation Health↗
DOE OSTI2024

Enhanced Resistance Pines for Improved Renewable Biofuel and Chemical Production (Technical Report)

We completed phenotyping constitutive and inducible oleoresin flow across two seasons, constitutive resin canal number and density and wood terpene content in our ADEPT2 and CCLONES populations. We completed genetic association between 19 oleoresin phenotypes and a total of 523,192 SNP markers from ADEPT2 and 13,883 SNP markers in CCLONES using four mixed linear models. A total of 293 significant SNPs (FDR = 0.20) were identified. We used the MENTOR tool to mine mechanistic connections from a multiplex network constructed from poplar multi-omic data to construct a conceptual model for a subset of these significant SNPs. Our model contains 6 transcriptional regulators in addition to 3 monoterpene synthases. To generate more lines of evidence for these significant SNPs, we completed a time course RNAseq experiment after inducing vascular zone cells to differentiate into new resin canals with a methyl jasmonate treatment, a single nuclei RNAseq that identified differentiating resin canal epithelial cells and are completing analysis for a QTL study in a hybrid pine population. The time course identified 4634 significantly down and 1890 significantly up regulated transcripts after treatment with methyl jasmonate, an inducer of new resin canal formation in the vascular cambial meristem. To analyze this large set of differentially regulated genes, we created a predictive expression network and analyzed it with random walk restart using 6 seed genes coding for transcription factors regulating xylem differentiation in poplar. Of the top ranked 200 transcripts, 119 transcripts were significant differentially expressed supporting these transcripts as potential candidates regulating resin canal formation. Analysis of single nuclei sequencing of shoot tips that contain differentiating resin canals, identified 10 clusters. One cluster was highly enriched in transcripts coding for 9 of the enzymes in the MEP pathway 3 prenyl synthetases, and 3 monoterpene synthases strongly suggesting that this cluster represents resin canal epithelial cells. We are mining the additional transcripts to create a trajectory analysis. In summary, we have identified > 10 novel genes that are strongly supported candidates for further analysis in breeding lines and for genetic engineering over- and under- expressing lines to increase wood terpene content to improve resistance to insect and fungal pathogens while simultaneously increasing terpene supplies for renewable chemicals and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Developmental Regulation of the Collagenase-3 Promoter in Osteoblasts

Previously, we have shown that collagenase-3 MRNA is developmentally expressed in normal, differentiating rat osteoblasts. In vivo, the gene is expressed in a tissue-specific fashion in hypertrophic chondrocytes and osteoblasts and developmentally regulated. Our studies aim at determining the promoter elements and proteins binding to the promoter responsible for tissue and developmental regulation of collagenase-3.

Partridge, N. C.↗
DOE OSTI2021

Necrosulfonamide reverses pyroptosis-induced inhibition of proliferation and differentiation of osteoblasts through the NLRP3/caspase-1/GSDMD pathway

The acute inflammatory stimulation occurring after a bone fracture regulates the repair and healing of local bone injury; however, under certain conditions, pyroptosis may occur in osteoblasts, which affects osteoblast proliferation and differentiation, thereby affecting the growth, development and morphological changes of bone tissue. The aim of the present study was to examine the effect of the pyroptosis inhibitor necrosulfonamide (NSA) on the proliferation and differentiation of osteoblasts and elucidate the underlying mechanism. The results revealed that NSA reversed the effects of ATP/lipopolysaccharide (LPS) on cell viability and pyroptosis, and on the mRNA and protein expression of pyroptosis-related genes. It also suppressed the secretion of IL-6, TNF-α and IL-1β and reversed the effects of ATP/LPS on the activity of ALP and the mRNA expression of differentiation-related genes in osteoblasts. The fact that overexpression of caspase-1, gasdermin D (GSDMD) and NLRP3 abolished the effects of NSA on the viability and pyroptosis of osteoblasts, as well as the mRNA expression of differentiation-related genes and the activity of ALP in osteoblasts, indicated that NSA promoted the proliferation and differentiation of osteoblasts by inhibiting the NLRP3/caspase-1/GSDMD pyroptosis pathway. The present study provides proof supporting the potential application of NSA for improving the function of osteoblasts in fracture repair and indicates the value of the NLRP3/caspase-1/GSDMD pyroptosis pathway as a pharmaceutical target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Exploring drought-responsive crucial genes in Sorghum

Drought severely affects global food production. Sorghum is a typical drought-resistant model crop. Based on RNA-seq data for Sorghum with multiple time points and the gray correlation coefficient, this paper firstly selects candidate genes via mean variance test and constructs weighted gene differential co-expression networks (WGDCNs); then, based on guilt-by-rewiring principle, the WGDCNs and the hidden Markov random field model, drought-responsive crucial genes are identified for five developmental stages respectively. Enrichment and sequence alignment analysis reveal that the screened genes may play critical functional roles in drought responsiveness. A multilayer differential co-expression network for the screened genes reveals that Sorghum is very sensitive to pre-flowering drought. Furthermore, a crucial gene regulatory module is established, which regulates drought responsiveness via plant hormone signal transduction, MAPK cascades, and transcriptional regulations. The proposed method can well excavate crucial genes through RNA-seq data, which have implications in breeding of new varieties with improved drought tolerance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Differential Regulation of Maize and Sorghum Orthologs in Response to the Fungal Pathogen Exserohilum turcicum

Pathogens that infect more than one host offer an opportunity to study how resistance mechanisms have evolved across different species. Exserohilum turcicum infects both maize and sorghum and the isolates are host-specific, offering a unique system to examine both compatible and incompatible interactions. We conducted transcriptional analysis of maize and sorghum in response to maize-specific and sorghum-specific E. turcicum isolates and identified functionally related co-expressed modules. Maize had a more robust transcriptional response than sorghum. E. turcicum responsive genes were enriched in core orthologs in both crops, but only up to 16% of core orthologs showed conserved expression patterns. Most changes in gene expression for the core orthologs, including hub genes, were lineage specific, suggesting a role for regulatory divergent evolution. We identified several defense-related shared differentially expressed (DE) orthologs with conserved expression patterns between the two crops, suggesting a role for parallel evolution of those genes in both crops. Many of the differentially expressed genes (DEGs) during the incompatible interaction were related to quantitative disease resistance (QDR). This work offers insights into how different hosts with relatively recent divergence interact with a common pathogen. Our results are important for developing resistance to this critical pathogen and understanding the evolution of host-pathogen interactions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Fibronectin gene expression, synthesis and accumulation during in vitro differentiation of chicken osteoblasts

A well-defined chicken osteoblast culture system(18) has been used to examine fibronectin (FN) mRNA levels, synthesis, and accumulation during in vitro differentiation and matrix mineralization. Immunofluorescent staining of cells after 6 or 18 days in culture revealed that FN was initially associated with the cell surface and in partial coalignment with cytoskeletal elements while at the latter time most FN was associated with the extracellular matrix as a ubiquitous fibrillar network. Western blot analysis of total cell-associated proteins also detected FN at all culture times. However, when results were normalized to cellular DNA, FN levels increased until 12-16 and remained relatively constant thereafter. Similarly, FN synthesis as measured by [35S]-methionine labeling, and immunoprecipitation was greatest in early cultures (culture day 3) and then declined such that synthesis decreased 60% at day 18 and 94% after 24-31 days. FN mRNA levels as measured by Northern blot analysis were well correlated with FN synthesis. These results clearly show that FN is made by primary osteoblasts during their in vitro maturation. In contrast to other osteoblast markers such as alkaline phosphatase, osteocalcin, and osteopontin, whose expression increases as cells differentiate, FN accumulates in the matrix during periods of early cell growth and attachment and then remains proportional to cell number. Results with FN differ from those obtained with collagen which continues to accumulate in the extracellular matrix during osteoblast maturation. These results are consistent with FN being important for the initial attachment of early osteoblasts or osteoblast precursors to the pericellular matrix.

NASA Discipline Musculoskeletal↗
DOE OSTI2026

Identifying stochastic dynamics via finite expression methods

Modeling stochastic differential equations (SDEs) is crucial for understanding complex dynamical systems in various scientific fields. Recent methods often employ neural network-based models, which typically represent SDEs through a combination of deterministic and stochastic terms. However, these models usually lack interpretability and have difficulty in generalizing beyond their training domain. Here, this paper introduces the Finite Expression Method (FEX), a symbolic learning approach designed to derive interpretable mathematical representations of the deterministic component of SDEs. For the stochastic component, we integrate FEX with advanced generative modeling techniques to provide a comprehensive representation of SDEs. The numerical experiments on linear, nonlinear, and multidimensional SDEs demonstrate that FEX generalizes well beyond the training domain and delivers more accurate long-term predictions compared to neural network-based methods. The symbolic expressions identified by FEX not only improve prediction accuracy but also offer valuable scientific insights into the underlying dynamics of the systems.

Complex dynamical systems↗
NASA NTRS1990

The Design-To-Cost Manifold

Design-to-cost is a popular technique for controlling costs. Although qualitative techniques exist for implementing design to cost, quantitative methods are sparse. In the launch vehicle and spacecraft engineering process, the question whether to minimize mass is usually an issue. The lack of quantification in this issue leads to arguments on both sides. This paper presents a mathematical technique which both quantifies the design-to-cost process and the mass/complexity issue. Parametric cost analysis generates and applies mathematical formulas called cost estimating relationships. In their most common forms, they are continuous and differentiable. This property permits the application of the mathematics of differentiable manifolds. Although the terminology sounds formidable, the application of the techniques requires only a knowledge of linear algebra and ordinary differential equations, common subjects in undergraduate scientific and engineering curricula. When the cost c is expressed as a differentiable function of n system metrics, setting the cost c to be a constant generates an n-1 dimensional subspace of the space of system metrics such that any set of metric values in that space satisfies the constant design-to-cost criterion. This space is a differentiable manifold upon which all mathematical properties of a differentiable manifold may be applied. One important property is that an easily implemented system of ordinary differential equations exists which permits optimization of any function of the system metrics, mass for example, over the design-to-cost manifold. A dual set of equations defines the directions of maximum and minimum cost change. A simplified approximation of the PRICE H(TM) production-production cost is used to generate this set of differential equations over [mass, complexity] space. The equations are solved in closed form to obtain the one dimensional design-to-cost trade and design-for-cost spaces. Preliminary results indicate that cost is relatively insensitive to changes in mass and that the reduction of complexity, both in the manufacturing process and of the spacecraft, is dominant in reducing cost.

Dean, Edwin B.↗
NASA NTRS1978

The coupled states approximation for scattering of two diatoms

The paper presents a detailed development of the coupled-states approximation for the general case of two colliding diatomic molecules. The high-energy limit of the exact Lippman-Schwinger equation is applied, and the analysis follows the Shimoni and Kouri (1977) treatment of atom-diatom collisions where the coupled rotor angular momentum and projection replace the single diatom angular momentum and projection. Parallels to the expression for the differential scattering amplitude, the opacity function, and the nondiagonality of the T matrix are reported. Symmetrized expressions and symmetrized coupled equations are derived. The present correctly labeled coupled-states theory is tested by comparing its calculated results with other computed results for three cases: H2-H2 collisions, ortho-para H2-H2 scattering, and H2-HCl.

Heil, T. G.↗
NASA NTRS2000

Enhanced expression of extracellular calcium sensing receptor in monocyte-differentiated versus undifferentiated HL-60 cells: potential role in regulation of a nonselective cation channel

Human promyelocytic leukemia cells (HL-60) have been used widely as a model for studying the differentiation of hematopoietic progenitor cells in vitro. After treatment with phorbol-12-myristate-13-acetate (PMA) or 1,25-dihydroxyvitamin D(3) [1,25(OH)(2)D(3)], HL-60 cells differentiate into cells with the phenotype of monocytes/macrophages. We previously showed that peripheral blood monocytes and the murine J774 monocytic cell line express the CaR, and myeloid progenitors in the bone marrow and myeloid cells in peripheral blood other than monocytes express lower levels of the CaR. Therefore, we investigated whether undifferentiated HL-60 cells express a functional G protein-coupled, extracellular calcium (Ca(2+)(o))-sensing receptor (CaR) and if the expression of the CaR increases as these cells differentiate along the monocytic lineage. The use of reverse transcription-polymerase chain reaction (RT-PCR) with CaR-specific primers, followed by sequencing of the amplified products, identified an authentic CaR transcript in undifferentiated HL-60 cells. Both immunocytochemistry and Western blot analysis using a CaR-specific antiserum detected low levels of CaR protein expression in undifferentiated HL-60 cells. The levels of CaR protein increased considerably following treatment of the cells with PMA (50 nM) or 1,25(OH)(2)D(3) (100 nM) for 5 days. Northern analysis using a CaR-specific riboprobe identified CaR transcripts in undifferentiated HL-60 cells, but CaR mRNA levels did not change appreciably after treatment with either agent, suggesting that upregulation of CaR protein occurs at a translational level. PMA-treated HL-60 cells expressed a nonselective cation channel (NCC), and the calcimimetic CaR activator, NPS R-467, but not its less active stereoisomer, NPS S-467, as well as the polycationic CaR agonist, neomycin, activated this NCC, demonstrating that the CaR expressed in these cells is functionally active. Therefore, HL-60 cells exhibit an increase in CaR protein expression, occurring at a translational level during their differentiation into cells with a monocyte/macrophage phenotype in response to treatment with PMA or 1, 25(OH)(2)D(3), which is functionally linked to activation of a nonselective cation channel.

NASA Discipline Musculoskeletal↗