The Sovaris Aerospace capabilities are focused on the following areas.
Space Biomedicine and MetaboLogicsTM
Sovaris utilizes the MetaboLogicsTM Platform applied to space biomedicine. Developed by its sister company MetaboLogics, LLC, the MetaboLogicsTM Platform is focused on metabolomics and systems biology applied to personalized medicine, clinical biomarker discovery, predictive modeling, and human performance. The metabolomics component of MetaboLogicsTM Platform is based on targeted and non-targeted metabolomics as a means to identify systematic changes associated with real or simulated space flight conditions and as a tool to develop countermeasures related to these changes.
Metabolomics is generally regarded as the study of small molecules, or metabolites, found in cells, tissue, and fluids. Though Sovaris’ work is focused on humans, metabolomics is also applied to plants, microbes, and other organisms. The human metabolome consists of small molecules that are required for the growth, repair, maintenance, and normal function of a cell. It is first useful to describe the molecular classes traditionally considered not a part of the metabolome. These compound classes can be summarized as follows: [i]
- Enzymes. All enzymes are proteins, the domain of proteomics. Other proteins and most peptides are generally not small molecules and are excluded from the metabolome. Many members of this class participate in biochemical reactions with small molecules, but the products of these reactions, modified proteins, are not small molecules and thus are better considered within proteomics.
- Genetic material (all forms of DNA and RNA) is also excluded according to size and function. These are better considered within genomics and transcriptomics. Construction and degradation of genetic material utilizes or yields small molecules and, thus, has a relationship to the metabolome. Nucleotides would be considered a component of genetic material that is part of the metabolome.
- Structural molecules. Glycosaminoglycans, and other polymeric units that form tissue such as bone and cartilage, may be built up from and degraded to small molecules but they do not otherwise participate in metabolic reactions.
- Polymer compounds, such as glycogen, are actively involved in metabolic reactions, but they are not chemically definable. Like all the previous categories, they represent a source of metabolites, but are not metabolites themselves.
- Metabolites of xenobiotics. Xenobiotics include drugs, pesticides, herbicides, and a wide range of compounds that are not native and not required for the maintenance, growth or normal function of a cell.
It is important to consider that essential and conditionally-essential nutrients contribute significantly to the metabolome. We refer to these as Essential Inputs and Conditionally Essential Inputs. This includes vitamins, essential fatty acids, essential amino acids, trace elements, and other compounds. While they are not synthesized de novo, they are central to metabolism and are, thus, part of the metabolome. Molecular families considered within the human metabolome include:
- Organic acids
- Amino acids
- Trace elements
The study of metabolomics is partially defined by molecular mass. While sources vary on the exact cutoff, metabolomics is generally concerned with molecules smaller than 1500-2000Da (Dalton; a unit of mass, defined as 1/12 the mass of a carbon-12 nucleus. It’s also called the atomic mass unit, abbreviated as either “amu” or “u”.).
Definitions in Metabolomics and Metabolic Assessment: Classification of Approaches to Assessment
Various terms have been used to describe approaches to assess the metabolome. These can be summarized as below:
- Metabolic fingerprinting: Method of classification of samples based on biological relevance or origin.[ii]
- Metabolic profiling: Analysis focused on pre-specified analytes; often used interchangeably with metabolite profiling.[iii][vi]
- Metabolite profiling: Analysis focused on a group of metabolites, for example, a class such as amino acids, fatty acids, or those associated with a specific pathway, such as citric acid cycle metabolites.[v]
- Metabolomics: Comprehensive analysis of the metabolome under selected conditions.[vi]
- Metabonomics: Measure of the biochemical perturbations associated with disease, toxins, and drugs. [vii][viii]
- Frequently, metabolomics is combined with some form of profiling, fingerprinting, or analysis that considers pre-determined analytes. Metabolomics can be used to generate non-hypothesis-driven data from suborbital and orbital space flight conditions. This can be done with tissue models flown as part of biotechnology experiments or as a part of human studies.
Sovaris Aerospace is actively engaged in development of physiologic monitoring systems through our sister company Sovaris Neurosystems, LLC. These systems are based on sensor technology that integrate signals from EEG, EMG, ECG, capnometry, cranial Doppler, and an array of electrophysiologic measures. These systems are both stationary and ambulatory. A core focus is on EEG-EMG coherence (corticomuscular coherence), with attention to the molecular pathways that influence these interactions. The platform is focused on development of new signal processing algorithms that can help us better understand coupling and uncoupling of signals between the cerebral cortex and the musculoskeletal system. Uncoupling of these signals can have a profound effect on human performance. We are also focused on measuring signal directionality within the corticomuscular circuit. Based on our proprietary electroencephalography technology, we are also measuring signal directionality in the brain under different rest and challenge conditions. The molecular and genetic influences on these circuits are of special interest.
This platform is being applied to human performance under extreme conditions, such as spaceflight. These same tools are also being studied disease state management and recovery in earth based medicine.
For more information, see: www.sovarisneurosystems.com
Space Biotechnology and 3-D Tissue ‘Omics
For more than twenty years, our partners’ at NASA (Disease Modeling and Tissue Analogues Laboratory) have been developing 3D tissue models, which are superior to 2D systems in their ability to emulate many of the physiological characteristics of normal human tissues. This revolutionary development has led to the publication of more than 800 scientific articles and at least 28 US patents over as many years.These advanced 3-dimensional human tissue models have flown on 16 Shuttle and ISS missions, which has given us insight into the rigor of these models under varied space and earthbound conditions.
Sovaris Aerospace utilizes systems biology, which includes genomics, proteomics, and metabolomics.These ‘omics platforms typically include analysis of several hundred to several thousand analytes (genes, proteins, or small molecule metabolites). Data reduction techniques are applied to these large datasets to identify the variance associated with various test conditions or in the comparison of different interventions.
The Human Tissue Analogues Laboratory at Johnson Space Center has developed 3-dimensional tissue modeling capabilities. These 3-D tissue models perform better than 2-dimensional models and they are a more accurate analogue to humans.Through our Space Act Agreement with Dr. Tom Goodwin’s laboratory at Johnson Space Center, we have coupled our ‘omics initiative with the 3-D tissue analogues capability to provide a unique capacity to understand complex conditions related to spaceflight.
We are working to employ scientifically validated models of 3D human lung, neural, and other tissues, to study the cellular and sub-cellular changes observable during suborbital transition to microgravity.This strategy separates the initial microgravity response from later phenomena, which include radiation and electromagnetic influences. Adaptive cellular responses are assessed by concomitant cultivation of human 3D models with human microbes, which are constitutively expressed as a consequence of pre-flight stress and in-flight exposure to a reduced gravity environment. These data are then coupled with previously acquired data from space flight missions assessing human genomics.
Gene expression and proteomic profiles are used to characterize the behavior of these human tissue models at various stages of the suborbital trajectory and the suborbital environment. These tissue models are also used to characterize the metabolome (or the non-targeted small molecule pool) associated with the suborbital environment for the purpose of understanding metabolic networks. ‘Omic data (gene, protein, metabolite) is correlated with physical data (acceleration, G-force, vibration, etc) at each stage of flight to help us better describe the transitional biological and biochemical events associated with suborbital flight.
This work allows us to begin mapping the human tissue genome, proteome, and metabolome for suborbital spaceflight. This will help us better understand events associated with human tolerance, host defenses, and array of performance-related issues. Ultimately these analyses will permit us to associate the suborbital changes with adaptations seen in longer term habitation of microgravity, thus serving to predict possible health risks and the need for countermeasure development in long-range missions, such as those to Mars.It will also provide insights into human medicine.
[i] Beecher, CWW. The Human Metabolome. In: Harrigan, G.G. and Goodacre, R. Eds. Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis. London: Kluwer Academic Publishers, 2003:311-19.
[ii] Fiehn, O. Combining genomics, metabolome analysis, and biochemical modeling to understand metabolic networks. Comp Funct Genomics 2001;2:155–168
[iv] Harrigan, G.G. and Goodacre, R. Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis. London: Kluwer Academic Publishers, 2003;335.
[vii] Lindon, JC, et al. So what’s the deal with metabonomics? Metabonomics measures the fingerprint of biochemical perturbations caused by disease, drugs, and toxins. Anal Chem 2003;75:384A–391A
[viii] Nicholson, JK, et al. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999;29:1181–1189.
[ix] Goodacre, R. Metabolomics of a superorganism. J Nutr 2007;137:259S-266S.