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Biodiversity: molecular biological domains, symbiosis and kingdom origins

The number of extant species of organisms is estimated to be from fewer than 3 to more than 30 x 10(6) (May, 1992). Molecular biology, comparative genetics and ultrastructural analyses provide new insights into evolutionary relationships between these species, including increasingly precise ideas of how species and higher taxa have evolved from common ancestors. Accumulation of random mutations and large macromolecular sequence change in all organisms since the Proterozoic Eon has been importantly supplemented by acquisition of inherited genomes ('symbiogenesis'). Karyotypic alterations (polyploidization and karyotypic fissioning) have been added to these other mechanisms of species origin in plants and animals during the Phanerozoic Eon. The new evolution concepts (coupled with current rapid rates of species extinction and ignorance of the extent of biodiversity) prompted this analysis of the field of systematic biology and its role in the reorganization of extant species into higher taxa. Two superkingdoms (= Domains: Prokaryotae and Eukaryotae) and five kingdoms (Monera = Procaryotae or Bacteria; Protoctista: algae, amoebae, ciliates, foraminifera, oomycetes, slime molds, etc.; Mychota: 'true' fungi; Plantae: one phylum (division) of bryophytes and nine phyla of tracheophytes; and Animalia) are recognized. Two subkingdoms comprise the monera: the great diverse lineages are Archaebacteria and Eubacteria. The criteria for classification using molecular, ultrastructural and genetic data for this scheme are mentioned. For the first time since the nineteenth century, logical, technical definitions for each group are given with their time of appearance as inferred from the fossil record in the primary scientific literature. This classification scheme, which most closely reflects the evolutionary history, molecular biology, genetics and ultrastructure of extant life, requires changes in social organization of biologists, many of whom as botanists and zoologists, still behave as if there were only two important kingdoms (plants and animals).

Non-NASA Center↗

Comparison of repair of DNA double-strand breaks in identical sequences in primary human fibroblast and immortal hamster-human hybrid cells harboring a single copy of human chromosome 11

We have optimized a pulsed-field gel electrophoresis assay that measures induction and repair of double-strand breaks (DSBs) in specific regions of the genome (Lobrich et al., Proc. Natl. Acad. Sci. USA 92, 12050-12054, 1995). The increased sensitivity resulting from these improvements makes it possible to analyze the size distribution of broken DNA molecules immediately after the introduction of DSBs and after repair incubation. This analysis shows that the distribution of broken DNA pieces after exposure to sparsely ionizing radiation is consistent with the distribution expected from randomly induced DSBs. It is apparent from the distribution of rejoined DNA pieces after repair incubation that DNA ends continue to rejoin between 3 and 24 h postirradiation and that some of these rejoining events are in fact misrejoining events, since novel restriction fragments both larger and smaller than the original fragment are generated after repair. This improved assay was also used to study the kinetics of DSB rejoining and the extent of misrejoining in identical DNA sequences in human GM38 cells and human-hamster hybrid A(L) cells containing a single human chromosome 11. Despite the numerous differences between these cells, which include species and tissue of origin, levels of TP53, expression of telomerase, and the presence or absence of a homologous chromosome for the restriction fragments examined, the kinetics of rejoining of radiation-induced DSBs and the extent of misrejoining were similar in the two cell lines when studied in the G(1) phase of the cell cycle. Furthermore, DSBs were removed from the single-copy human chromosome in the hamster A(L) cells with similar kinetics and misrejoining frequency as at a locus on this hybrid's CHO chromosomes.

NASA Program Biomedical Research and Countermeasur↗

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate “open science” biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from “omics” (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data.

genome↗

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate "open science" biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from "omics" (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data.

genome↗

Leiomodins: larger members of the tropomodulin (Tmod) gene family

The 64-kDa autoantigen D1 or 1D, first identified as a potential autoantigen in Graves' disease, is similar to the tropomodulin (Tmod) family of actin filament pointed end-capping proteins. A novel gene with significant similarity to the 64-kDa human autoantigen D1 has been cloned from both humans and mice, and the genomic sequences of both genes have been identified. These genes form a subfamily closely related to the Tmods and are here named the Leiomodins (Lmods). Both Lmod genes display a conserved intron-exon structure, as do three Tmod genes, but the intron-exon structure of the Lmods and the Tmods is divergent. mRNA expression analysis indicates that the gene formerly known as the 64-kDa autoantigen D1 is most highly expressed in a variety of human tissues that contain smooth muscle, earning it the name smooth muscle Leiomodin (SM-Lmod; HGMW-approved symbol LMOD1). Transcripts encoding the novel Lmod gene are present exclusively in fetal and adult heart and adult skeletal muscle, and it is here named cardiac Leiomodin (C-Lmod; HGMW-approved symbol LMOD2). Human C-Lmod is located near the hypertrophic cardiomyopathy locus CMH6 on human chromosome 7q3, potentially implicating it in this disease. Our data demonstrate that the Lmods are evolutionarily related and display tissue-specific patterns of expression distinct from, but overlapping with, the expression of Tmod isoforms. Copyright 2001 Academic Press.

Carrier Proteins/biosynthesis/genetics↗

Horizontal transfer of archaeal genes into the deinococcaceae: detection by molecular and computer-based approaches

Members of the Deinococcaceae (e.g., Thermus, Meiothermus, Deinococcus) contain A/V-ATPases typically found in Archaea or Eukaryotes which were probably acquired by horizontal gene transfer. Two methods were used to quantify the extent to which archaeal or eukaryotic genes have been acquired by this lineage. Screening of a Meiothermus ruber library with probes made against Thermoplasma acidophilum DNA yielded a number of clones which hybridized more strongly than background. One of these contained the prolyl tRNA synthetase (RS) gene. Phylogenetic analysis shows the M. ruber and D. radiodurans prolyl RS to be more closely related to archaeal and eukaryal forms of this gene than to the typical bacterial type. Using a bioinformatics approach, putative open reading frames (ORFs) from the prerelease version of the D. radiodurans genome were screened for genes more closely related to archaeal or eukaryotic genes. Putative ORFs were searched against representative genomes from each of the three domains using automated BLAST. ORFs showing the highest matches against archaeal and eukaryotic genes were collected and ranked. Among the top-ranked hits were the A/V-ATPase catalytic and noncatalytic subunits and the prolyl RS genes. Using phylogenetic methods, ORFs were analyzed and trees assessed for evidence of horizontal gene transfer. Of the 45 genes examined, 20 showed topologies in which D. radiodurans homologues clearly group with eukaryotic or archaeal homologues, and 17 additional trees were found to show probable evidence of horizontal gene transfer. Compared to the total number of ORFs in the genome, those that can be identified as having been acquired from Archaea or Eukaryotes are relatively few (approximately 1%), suggesting that interdomain transfer is rare.

Non-NASA Center↗

An Integrated Design Tool for Tow-Steered Laminates of Composites in Abaqus and MSC.Patran/Nastran

Tow-steered composites can be tailored for optimal mechanical performance of lightweight structures. However, there are no commercial-grade design tools for tow-steered composite structures, which hinders the design innovation of tow-steered composites in realistic structures. The novelty of this paper is to develop an integrated design framework along with the development of graphical user interface (GUI) plug-ins in commercial finite element (FE) software Abaqus and MSC.Patran/Nastran. The GUI plug-ins take all the design setups and communicate with external codes for the material modeling and optimization, and hence provide a unified design environment within the FE codes. The mechanics of structure genome (MSG) plate model computes shell element properties based on user-defined fiber paths and layup, which are defined via the GUI plug-ins. The optimization is performed by an open-source code, Dakota, from Sandia National Laboratories (Sandia), which also coordinates the structural analysis, material modeling, and optimization in design iterations. Two examples are presented to demonstrate the user-friendliness and versatility of the developed GUI plug-ins. The developed tools will ease the design process and facilitate the application of tow-steered composites in realistic aerospace structures.

Xin Liu↗

An Integrated Design Tool for Tow-Steered Laminates of Composites in Abaqus and MSC.Patran/Nastran

Tow-steered composites can be tailored for optimal mechanical performance of lightweight structures. However, there are no commercial-grade design tools for tow-steered composite structures, which hinders the design innovation of tow-steered composites in realistic structures. The novelty of this paper is to develop an integrated design framework along with the development of graphical user interface (GUI) plug-ins in commercial finite element (FE) software Abaqus and MSC.Patran/Nastran. The GUI plug-ins take all the design setups and communicate with external codes for the material modeling and optimization, and hence provide a unified design environment within the FE codes. The mechanics of structure genome (MSG) plate model computes shell element properties based on user-defined fiber paths and layup, which are defined via the GUI plug-ins. The optimization is performed by an open-source code, Dakota, from Sandia National Laboratories (Sandia), which also coordinates the structural analysis, material modeling, and optimization in design iterations. Two examples are presented to demonstrate the user-friendliness and versatility of the developed GUI plug-ins. The developed tools will ease the design process and facilitate the application of tow-steered composites in realistic aerospace structures.

Xin Liu↗

Calmodulin Gene Family in Potato: Developmental and Touch-Induced Expression of the mRNA Encoding a Novel Isoform

Eight genomic clones of potato calmodulin (PCM1 to 8) were isolated and characterized. Sequence comparisons of different genes revealed that the deduced amino acid sequence of PCM1 had several unique substitutions, especially in the fourth Ca(2+)-binding area. The expression patterns of different genes were studied by northern analysis using the 3'-untranslated regions as probes. The expression of PCM1, 5, and 8 was highest in the stolon tip and it decreased during tuber development. The expression of PCM6 did not vary much in the tissues tested, except in the leaves, where the expression was lower; whereas, the expression of PCM4 was very low in all the tissues. The expression of PCM2 and PCM3 was not detected in any of the tissues tested. Among these genes, only PCM1 showed increased expression following touch stimulation. To study the regulation of PCM1, transgenic potato plants carrying the PCM1 promoter fused to the beta-glucuronidase (GUS) reporter gene were produced. GUS expression was found to be developmentally regulated and touch-responsive, indicating a positive correlation between the expression of PCM1 and GUS mRNAs. These results suggest that the 5'-flanking region of PCM1 controls developmental and touch-induced expression. X-Gluc staining patterns revealed that GUS localization is high in meristematic tissues such as the stem apex, stolon tip, and vascular regions.

Takezawa, D.↗

Network Analysis of Rodent Transcriptomes in Spaceflight

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

genomics↗

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗

GeneLab for High Schools: Data Mining for the Next Generation

Modern biological sciences have become increasingly based on molecular biology and high-throughput molecular techniques, such as genomics, transcriptomics, and proteomics. NASA Scientists and the NASA Space Biology Program have aimed to examine the fundamental building blocks of life (RNA, DNA and protein) in order to understand the response of living organisms to space and aid in fundamental research discoveries on Earth. In an effort to enable NASA funded science to be available to everyone, NASA has collected the data from omics studies and curated them in a data system called GeneLab. Whilst most college-level interns, academics and other scientists have had some interaction with omics data sets and analysis tools, high school students often have not. Therefore, the Space Biology Program is implementing a new Summer Program for high-school students that aims to inspire the next generation of scientists to learn about and get involved in space research using GeneLabs Data System. The program consists of three main components core learning modules, focused on developing students knowledge on the Space Biology Program and Space Biology research, Genelab and the data system, and previous research conducted on model organisms in space; networking and team work, enabling students to interact with guest lecturers from local universities and their fellow peers, and also enabling them to visit local universities and genomics centers around the Bay area; and finally an independent learning project, whereby students will be required to form small groups, analyze a dataset on the Genelab platform, generate a hypothesis and develop a research plan to test their hypothesis. This program will not only help inspire high-school students to become involved in space-based research but will also help them develop key critical thinking and bioinformatics skills required for most college degrees and furthermore, will enable them to establish networks with their peers and connections with university Professors that may help them achieve their educational goals.

genelab↗

Prochlorococcus phage ferredoxin: structural characterization and electron transfer to cyanobacterial sulfite reductases

Marine cyanobacteria are infected by phages whose genomes encode ferredoxin (Fd) electron carriers. These Fds are thought to redirect the energy harvested from light to phage-encoded oxidoreductases that enhance viral fitness, but it is unclear how the biophysical properties and partner specificities of phage Fds relate to those of photosynthetic organisms. Here, results of a bioinformatics analysis using a sequence similarity network revealed that phage Fds are most closely related to cyanobacterial Fds that transfer electrons from photosystems to oxidoreductases involved in nutrient assimilation. Structural analysis of myovirus P-SSM2 Fd (pssm2-Fd), which infects the cyanobacterium Prochlorococcus marinus, revealed high levels of similarity to cyanobacterial Fds (root mean square deviations of ≤0.5 Å). Additionally, pssm2-Fd exhibited a low midpoint reduction potential (–336 mV versus a standard hydrogen electrode), similar to other photosynthetic Fds, although it had lower thermostability (Tm = 28 °C) than did many other Fds. When expressed in an Escherichia coli strain deficient in sulfite assimilation, pssm2-Fd complemented bacterial growth when coexpressed with a P. marinus sulfite reductase, revealing that pssm2-Fd can transfer electrons to a host protein involved in nutrient assimilation. The high levels of structural similarity with cyanobacterial Fds and reactivity with a host sulfite reductase suggest that phage Fds evolved to transfer electrons to cyanobacterially encoded oxidoreductases.

cyanobacteria↗

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↗

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↗

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↗