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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Ocean Biological Pump Sensitivities and Implications for Climate Change Impacts

The ocean is one of the principal reservoirs of CO2, a greenhouse gas, and therefore plays a crucial role in regulating Earth's climate. Currently, the ocean sequesters about a third of anthropogenic CO2 emissions, mitigating the human impact on climate. At the same time, the deeper ocean represents the largest carbon pool in the Earth System and processes that describe the transfer of carbon from the surface of the ocean to depth are intimately linked to the effectiveness of carbon sequestration.The ocean biological pump (OBP), which involves several biogeochemical processes, is a major pathway for transfer of carbon from the surface mixed layer into the ocean interior. About 75 of the carbon vertical gradient is due to the carbon pump with only 25 attributed to the solubility pump. However, the relative importance and role of the two pumps is poorly constrained. OBP is further divided to the organic carbon pump (soft tissue pump) and the carbonate pump, with the former exporting about 10 times more carbon than the latter through processes like remineralization.Major uncertainties about OBP, and hence in the carbon uptake and sequestration, stem from uncertainties in processes involved in OBP such as particulate organicinorganic carbon sinkingsettling, remineralization, microbial degradation of DOC and uptakegrowth rate changes of the ocean biology. The deep ocean is a major sink of atmospheric CO2 in scales of hundreds to thousands of years, but how the export efficiency (i.e. the fraction of total carbon fixation at the surface that is transported at depth) is affected by climate change remains largely undetermined. These processes affect the ocean chemistry (alkalinity, pH, DIC, particulate and dissolved organic carbon) as well as the ecology (biodiversity, functional groups and their interactions) in the ocean. It is important to have a rigorous, quantitative understanding of the uncertainties involved in the observational measurements, the models and the projections of future changes.

particulates↗
NASA NTRS1992

The use of typed lambda calculus for comprehension and construction of simulation models in the domain of ecology

We are concerned with two important issues in simulation modelling: model comprehension and model construction. Model comprehension is limited because many important choices taken during the modelling process are not documented. This makes it difficult for models to be modified or used by others. A key factor hindering model construction is the vast modelling search space which must be navigated. This is exacerbated by the fact that many modellers are unfamiliar with the terms and concepts catered to by current tools. The root of both problems is the lack of facilities for representing or reasoning about domain concepts in current simulation technology. The basis for our achievements in both of these areas is the development of a language with two distinct levels; one for representing domain information, and the other for representing the simulation model. Of equal importance, is the fact that we make formal connections between these two levels. The domain we are concerned with is ecological modelling. This language, called Elklogic, is based on the typed lambda calculus. Important features include a rich type structure, the use of various higher order functions, and semantics. This enables complex expressions to be constructed from relatively few primitives. The meaning of each expression can be determined in terms of the domain, the simulation model, or the relationship between the two. We describe a novel representation for sets and substructure, and a variety of other general concepts that are especially useful in the ecological domain. We use the type structure in a novel way: for controlling the modelling search space, rather than a proof search space. We facilitate model comprehension by representing modelling decisions that are embodied in the simulation model. We represent the simulation model separately from, but in terms of a domain mode. The explicit links between the two models constitute the modelling decisions. The semantics of Elklogic enables English text to be generated to explain the simulation model in domain terms.

Uschold, Michael↗
NASA NTRS1986

Development of space technology for ecological habitats

The development of closed ecological systems for space stations is discussed. Growth chambers, control systems, microgravity, ecosystem stability, lighting equipment, and waste processing systems are among the topics discussed.

Martello, N. V.↗
NASA NTRS1988

Design of components for growing higher plants in space

The overall goal of this project is to design unique systems and components for growing higher plants in microgravity during long-term space missions (Mars and beyond). Specific design tasks were chosen to contribute to and supplement NASA's Controlled Ecological Life Support System (CELSS) project. Selected tasks were automated seeding of plants, plant health sensing, and food processing. Prototype systems for planting both germinated and nongerminated seeds were fabricated and tested. Water and air pressure differences and electrostatic fields were used to trap seeds for separation and transport for planting. An absorption spectrometer was developed to measure chlorophyll levels in plants as an early warning of plant health problems. In the area of food processing, a milling system was created using high-speed rotating blades which were aerodynamically configured to produce circulation and retractable to prevent leakage. The project produced significant results having substantial benefit to NASA. It also provided an outstanding learning experience for the students involved.

Source record↗
NASA NTRS1997

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Running, Steven W.↗
NASA NTRS1998

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Source record↗
NASA NTRS2022

Exploring the Relationship Between Temperature Forecast Errors and Earth System Variables

Accurate subseasonal weather forecasts, from two weeks up to a season, can help reduce costs and impacts related to weather and corresponding extremes. The quality of weather forecasts has improved considerably in recent decades as models represent more details of physical processes, and they benefit from assimilating comprehensive Earth observation data as well as increasing computing power. However, with ever–growing model complexity, it becomes increasingly difficult to pinpoint weaknesses in the forecast models’ process representations which is key to improving forecast accuracy. In this study, we use a comprehensive set of observation–based ecological, hydrological and meteorological variables to study their potential for explaining temperature forecast errors at the weekly time scale. For this purpose, we compute Spearman correlations between each considered variable and the forecast error obtained from the ECMWF subseasonal–to–seasonal (S2S) reforecasts at lead times of 1–6 weeks. This is done across the globe for the time period 2001–2017. The results show that temperature forecast errors globally are most strongly related with climate–related variables such as surface solar radiation and precipitation, which highlights the model’s difficulties in accurately capturing the evolution of the climate–related variables during the forecasting period. At the same time, we find particular regions in which other variables are more strongly related to forecast errors. For instance, in central Europe, eastern North America and southeastern Asia, vegetation greenness and soil moisture are relevant, while in western South America and central North America, circulation–related variables such as surface pressure relate more strongly with forecast errors. Overall, the identified relationships between forecast errors and independent Earth observations reveal promising variables on which future forecasting system development could focus by specifically considering related process representations and data assimilation.

Temperature↗
NASA NTRS2003

A Domain Description Language for Data Processing

We discuss an application of planning to data processing, a planning problem which poses unique challenges for domain description languages. We discuss these challenges and why the current PDDL standard does not meet them. We discuss DPADL (Data Processing Action Description Language), a language for describing planning domains that involve data processing. DPADL is a declarative, object-oriented language that supports constraints and embedded Java code, object creation and copying, explicit inputs and outputs for actions, and metadata descriptions of existing and desired data. DPADL is supported by the IMAGEbot system, which we are using to provide automation for an ecological forecasting application. We compare DPADL to PDDL and discuss changes that could be made to PDDL to make it more suitable for representing planning domains that involve data processing actions.

Golden, Keith↗
NASA NTRS2002

Biogeochemistry of Microbial Mats

The hierarchical organization of microbial ecosystems determines the rates of processes that shape Earth's environment, define the stage upon which major evolutionary events occurred, and create biosignatures in sediments and atmospheres. In cyanobacterial mats, oxygenic photosynthesis provides energy, organic substrates and oxygen to the ecosystem. Incident light changes with depth in the mat, both in intensity and spectral composition, and counteracting gradients of oxygen and sulfide shape the chemical microenvironment. A combination of benefits and hazards of light, oxygen and sulfide promotes the allocation of the various essential mat processes between light and dark periods and to various depths in the mat. Microliters produce hydrogen, small organic acids, nitrogen and sulfur species. Such compounds fuel a flow of energy and electrons in these ecosystems and thus shape interactions between groups of microorganisms. Coordinated observations of population distribution, abundance, and activity for an entire community are making fundamental questions in ecology accessible. These questions address those factors that sustain the remarkable diversity of microorganisms that are now being revealed by molecular techniques. These questions also target the processes that shape the various kinds of biosignatures that we will seek, both in ancient rocks from Earth and Mars, and in atmospheres of distant planets beyond our Solar System.

DesMarais, David J.↗
NASA NTRS2003

Carbon and Oxygen Budgets of Hypersaline Cyanobacterial Mats: Effects of Tidal Cycle and Temperature

The hierarchical organization of microbial ecosystems determines the rates of processes that shape Earth#s environment, define the stage upon which major evolutionary events occurred, and create biosignatures in sediments and atmospheres. In cyanobacterial mats, oxygenic photosynthesis provides energy, organic substrates and oxygen to the ecosystem. Incident light changes with depth in the mat, both in intensity and spectral composition, and counteracting gradients of oxygen and sulfide shape the chemical microenvironment. A combination of benefits and hazards of light, oxygen and sulfide promotes the allocation of the various essential mat processes between light and dark periods and to various depths in the mat. Microbiota produce hydrogen, small organic acids, and nitrogen and sulfur species. Such compounds fuel a flow of energy and electrons in these ecosystems and thus shape interactions between groups of microorganisms. Coordinated observations of population distribution, abundance, and activity for an entire community are making fundamental questions in ecology accessible. These questions address those factors that sustain the remarkable diversity of microorganisms that are now being revealed by molecular techniques. These questions also target the processes that shape the various kinds of biosignatures that we will seek, both in ancient rocks from Earth and Mars, and in atmospheres of distant planets beyond our Solar System.

David J Des Marais↗
NASA NTRSDate not supplied

Does Collection Time Bias the Ecology of Cleanroom Air Samples?

Microbial monitoring of astromaterials collections has taken on increased importance with the return of biologically sensitive samples from the asteroids Ryugu and Bennu and the initiation of the Mars Sample Return Program. Terrestrial bacteria and fungi can alter the mineralogy and organic composition of our collections causing irreversible contamination of pristine samples and increasing the risk of false positives for life detection measurements. NASA has conducted routine microbial monitoring of its existing collections since 20181. Initial monitoring focused on surface samples collected with foam swabs. Although, airborne microbiology is often decoupled from surface microbiology in the built environment2 culture-based air sampling techniques like impactors were not compliant with existing contamination control requirements. Bringing organic rich media, gelatin or liquids into curation cleanrooms presents an unacceptable risk to pristine samples. In 2022 NASA purchased a materials complaint air sampler and began collecting air samples from the cleanrooms in addition to surface samples3. The new instrument uses an electret filter to collect samples that are suitable for cultivating organisms or for direct DNA sequencing. Preliminary DNA sequencing results appeared to indicate that longer sampling times biased the microbial community in favor of hearty, spore-forming bacteria3. We present the results of a study comparing overnight sampling (17 hours) to short (1 hour) sampling of unoccupied curation cleanrooms. The results will help us optimize our monitoring protocols and develop a more detailed inventory of the ecology of astromaterials curation cleanrooms. Methods: We analyzed 72 paired air samples from six different cleanrooms including the meteorite processing lab (ISO 7 equivalent, 16 samples), the lunar lab (ISO 6 equivalent, 10 samples), the stardust lab (ISO 5 equivalent 14 samples), the OSIRIS-REx lab (ISO 5 equivalent, 12 samples), the Hayabusa2 lab (ISO 5 equivalent, 14 samples), and the Genesis lab (ISO 4 equivalent, 6 samples). All the samples were collected with an InnovaPrep Bobcat air sampler operating at a sampling rate of 200 L/min. The sampler operates for 5 minutes out of every 20 minute period. Half of the samples were collected by filtering 3,000L (15 min. of active sampling) of air across an electret filter for one hour. The rest of the samples were collected by filtering approximately 51,000 L air across the filter overnight (~17 hours, 255 min. of active sampling). Cells were eluted from the filter using 6-7 ml of pressurized 0.15% tween 20 in PBS (phosphate buffered saline). This liquid was used to cultivate bacteria according to previously published methods1,4,5 and for DNA extraction and next generation sequencing. DNA was extracted with a Qiagen MagAttract PowerMicrobiome kit6. To identify bacteria and archaea, the 16S rRNA gene was amplified using Earth Microbiome primers for the V4 region 7. The amplified DNA was sequenced on an Illumina MiSeq using a V3 reagent kit. The resulting sequences were processed using DADA2 and QIIME2 as implemented on the EDGE bioinformatics platform8–10. Results: Only two of the 72 samples had no amplifiable DNA. Amplified DNA concentrations ranged from 2.67 – 0.272 ng/µl. The median concentration of amplified DNA for the 1 hour samples was 0.770 ± 0.368 ng/µl. The median concentration of amplified DNA for the overnight samples was 0.877 ± 0.434 ng/µl. On average the overnight samples had slightly more sequences (58,960 vs. 59,456) and ASV’s (amplicon sequence variants) (60 vs 64.5) than the one hour samples, but these differences are not statistically significant. The most abundant ASV in every sample mapped to the genus Cupravidus. ASV’s mapping to the genuses Bacillus, Schlegelella, Thermus, and Staphylococcus were also common. Discussion and Future Work: Alpha diversity statistics like Shannon Entropy and Faith Phylogenetic Diversity are used to describe the diversity of organisms in a single sample. If a longer sampling time was biasing the data, we would expect to see a change in these diversity statistics vs. sample time. However, we did not observe this in our data. The median Shannon entropy was slightly higher for the overnight samples (3.773 vs 3.611) as was the Faith Phylogenetic Diversity (4.042 vs 3.596), but both values were within a standard deviation of each other for the two sampling times (Fig. 1). It is unlikely, that the longer sampling time is introducing bias into our data. We do observe a significant decrease in diversity when comparing the air samples by lab. The Genesis lab (ISO 4 equivalent) has a lower median number of ASV’s (45.5) than the other labs (62). Median values for Shannon Entropy (3.717 vs. 3.430) and Faith Phylogenetic Diversity (3.796 vs. 3.548) are also lower for Genesis, but those values are with one standard deviation of each other for the different sampling times. This is consistent with previous culture-based results suggesting that the environment in cleanrooms tends to select for a core group of organisms capable of surviving under dry, low nutrient, conditions. The presence of the ASV’s mapping to Cupravidus and Thermus in our sequencing blanks and controls suggests that several of the most common organisms in our samples represent contaminants from the reagents used to perform the DNA extractions and sequencing. Further work is needed to identify these contaminants, remove them from our data and recalculate the diversity statistics. This is a systematic error. Therefore, we do not expect removing the sequencing contaminants to change our conclusions. Longer air sample collection times appear to result in slightly higher diversity and do not bias the results towards “hardy” bacteria like spore-formers. Based on these preliminary results we conclude that sampling at least 3,000 liters of air is sufficient to capture the microbial diversity of cleanrooms, and that air samples can also be collected overnight without negatively impacting diversity. These results allow us to be flexible when designing microbial monitoring plans so that they do not interfere with routine lab activity. References: 1. Regberg, A. B. et al. 49th Lunar and Planetary Science Conference (2018). 2. The United States Pharmacopeial Convention. USP General Chapter <1116> (2013). 3. Regberg, A. B., et al. 54th Lunar and Planetary Science Conference (2023). 4. Regberg, A. B. et al. 53rd Lunar and Planetary Science Conference ( 2022). 5. Davis, R. E.,et al. 50th Lunar and Planetary Science Conference (2019). 6. Qiagen. MagAttract® PowerMicrobiome® DNA/RNA EP Kit Handbook. (2018). 7. Walters, W. et al. mSystems 1, (2015). 8. Callahan, B. J. et al. Nat. Methods 13, 581–583 (2016). 9. Hall, M. & Beiko, R. G. Microbiome Analysis: Methods and Protocols113–129 (Springer, 2018). 10. Philipson, C. et al. Bio-Protoc. 7, e2622 (2017).

A. B. Regberg↗
NASA NTRS1986

Potential for utilization of algal biomass for components of the diet in CELSS

The major nutritional components of the green algae (Scenedesmus obliquus) grown in a Constant Cell Density Apparatus were determined. Suitable methodology to prepare proteins from which three major undesirable components of these cells (i.e., cell walls, nucleic acids, and pigments) were either removed or substantially reduced was developed. Results showed that processing of green algae to protein isolate enhances is potential nutritional and organoleptic acceptability as a diet component in controlled Ecological Life Support System.

Kamarei, A. R.↗
NASA NTRS1993

Using emergent order to shape a space society

A fast-growing movement in the scientific community is reshaping the way that we view the world around us. The short-hand name for this movement is 'chaos'. Chaos is a science of the global, nonlinear nature of systems. The center of this set of ideas is that simple, deterministic systems can breed complexity. Systems as complex as the human body, ecology, the mind or a human society. While it is true that simple laws can breed complexity, the other side is that complex systems can breed order. It is the latter that I will focus on in this paper. In the past, nonlinear was nearly synonymous with unsolvable because no general analytic solutions exist. Mathematically, an essential difference exists between linear and nonlinear systems. For linear systems, you just break up the complicated system into many simple pieces and patch together the separated solutions for each piece to form a solution to the full problem. In contrast, solutions to a nonlinear system cannot be added to form a new solution. The system must be treated in its full complexity. While it is true that no general analytical approach exists for reducing a complex system such as a society, it can be modeled. The technical involves a mathematical construct called phase space. In this space stable structures can appear which I use as analogies for the stable structures that appear in a complex system such as an ecology, the mind or a society. The common denominator in all of these systems is that they rely on a process called feedback loops. Feedback loops link the microscopic (individual) parts to the macroscopic (global) parts. The key, then, in shaping a space society, is in effectively using feedback loops. This paper will illustrate how one can model a space society by using methods that chaoticists have developed over the last hundred years. And I will show that common threads exist in the modeling of biological, economical, philosophical, and sociological systems.

Graps, Amara L.↗
NASA NTRS2016

Xeropreservation of Functionalized Lipid Biomarkers in Hyperarid Soils in the Atacama Desert

Our understanding of long-term organic matter preservation comes mostly from studies in aquatic systems. In contrast, taphonomic processes in extremely dry environments are relatively understudied and are poorly understood. We investigated the accumulation and preservation of lipid biomarkers in hyperarid soils in the Yungay region of the Atacama Desert. Lipids from seven soil horizons in a 2.5 m vertical profile were extracted and analyzed using GC-MS and LC-MS. Diagnostic functionalized lipids and geolipids were detected and increased in abundance and diversity with depth. Deeper clay units contain fossil organic matter (radiocarbon dead) that has been protected from rainwater since the onset of hyperaridity. We show that these clay units contain lipids in an excellent state of structural preservation with functional groups and unsaturated bonds in carbon chains. This indicates that minimal degradation of lipids has occurred in these soils since the time of their deposition between greater than 40,000 and 2 million years ago. The exceptional structural preservation of biomarkers is likely due to the long-term hyperaridity that has minimized microbial and enzymatic activity, a taphonomic process we term xeropreservation (i.e., preservation by drying). The degree of biomarker preservation allowed us to reconstruct major changes in ecology in the Yungay region that reflect a shift in hydrological regime from wet to dry since the early Quaternary. Our results suggest that hyperarid environments, which comprise 7.5 percent of the continental landmass, could represent a rich and relatively unexplored source of paleobiological informationon Earth.

Hyperarid↗
NASA NTRS2016

Xeropreservation of Functionalized Lipid Biomarkers in Hyperarid Soils in the Atacama Desert

Our understanding of long-term organic matter preservation comes mostly from studies in aquatic systems. In contrast, taphonomic processes in extremely dry environments are relatively understudied and are poorly understood. We investigated the accumulation and preservation of lipid biomarkers in hyperarid soils in the Yungay region of the Atacama Desert. Lipids from seven soil horizons in a 2.5 meter vertical profile were extracted and analyzed using GC-MS ( Gas Chromatography-Mass Spectrometry) and LC-MS (Liquid Chromatography-Mass Spectrometry). Diagnostic functionalized lipids and geolipids were detected and increased in abundance and diversity with depth. Deeper clay units contain fossil organic matter (radiocarbon dead) that has been protected from rainwater since the onset of hyperaridity. We show that these clay units contain lipids in an excellent state of structural preservation with functional groups and unsaturated bonds in carbon chains. This indicates that minimal degradation of lipids has occurred in these soils since the time of their deposition between more than 40,000 and up to 2 million years ago. The exceptional structural preservation of biomarkers is likely due to the long-term hyperaridity that has minimized microbial and enzymatic activity, a taphonomic process we term xeropreservation (i.e. preservation by drying). The degree of biomarker preservation allowed us to reconstruct major changes in ecology in the Yungay region that reflect a shift in hydrological regime from wet to dry since the early Quaternary. Our results suggest that hyperarid environments, which comprise 7.5 percent of the continental landmass, could represent a rich and relatively unexplored source of paleobiological information on Earth.

Xeropreservation↗
NASA NTRS2010

Gray Wave of the Great Transformation: A Satellite View of Urbanization, Climate Change, and Food Security

Land cover change driven by human activity is profoundly affecting Earth's natural systems with impacts ranging from a loss of biological diversity to changes in regional and global climate. This change has been so pervasive and progressed so rapidly, compared to natural processes, scientists refer to it as "the great transformation". Urbanization or the 'gray wave' of land transformation is being increasingly recognized as an important process in global climate change. A hallmark of our success as a species, large urban conglomerates do in fact alter the land surface so profoundly that both local climate and the basic ecology of the landscape are affected in ways that have consequences to human health and economic well-being. Fortunately we have incredible new tools for planning and developing urban places that are both enjoyable and sustainable. A suite of Earth observing satellites is making it possible to study the interactions between urbanization, biological processes, and weather and climate. Using these Earth Observatories we are learning how urban heat islands form and potentially ameliorate them, how urbanization can affect rainfall, pollution, and surface water recharge at the local level and climate and food security globally.

Imhoff, Marc Lee↗
NASA NTRS2009

NASA Satellite Monitoring of Water Clarity in Mobile Bay for Nutrient Criteria Development

This project has demonstrated feasibility of deriving from MODIS daily measurements time series of water clarity parameters that provide coverage of a specific location or an area of interest for 30-50% of days. Time series derived for estuarine and coastal waters display much higher variability than time series of ecological parameters (such as vegetation indices) derived for land areas. (Temporal filtering often applied in terrestrial studies cannot be used effectively in ocean color processing). IOP-based algorithms for retrieval of diffuse light attenuation coefficient and TSS concentration perform well for the Mobile Bay environment: only a minor adjustment was needed in the TSS algorithm, despite generally recognized dependence of such algorithms on local conditions. The current IOP-based algorithm for retrieval of chlorophyll a concentration has not performed as well: a more reliable algorithm is needed that may be based on IOPs at additional wavelengths or on remote sensing reflectance from multiple spectral bands. CDOM algorithm also needs improvement to provide better separation between effects of gilvin (gelbstoff) and detritus. (Identification or development of such algorithm requires more data from in situ measurements of CDOM concentration in Gulf of Mexico coastal waters (ongoing collaboration with the EPA Gulf Ecology Division))

Blonski, Slawomir↗
NASA NTRS2006

The Molecular Ecology of Guerrero Negro: Justifying the Need for Environmental Genomics

The record of life on the only planet where it is known to exist is contained in the biogeochemical processes that organisms catalyze for their survival, in the compounds that they produce, and in their phylogenetic (evolutionary) relationships to each other. We manipulated sulfate and nutrient concentrations in intact microbial mats over periods of time up to a year. The objectives of the manipulations were: 1) characterize the diversity of process-associated functional genes; 2) understand environmental conditions leading to shifts in microbial guilds; 3) monitor/identify competitive responses of organisms sharing a metabolic niche. Characterization of functional genes associated with carbon (mcrA), nitrogen (nifH, nirK) and sulfur (dsrkB) cycling performed to date provided insight into the diversity and metabolic potential of the system; however, we only identified broad scale correlations between gene abundances and changes in mat physiology. For instance, increases in methane production by mats subjected to lowered sulfate and salinity concentrations were correlated with an observed increase in abundance of hydrogenotroph-like mcrA genes. However, due to low sequence similarity to any cultured isolates, phylogenetic associations only allow order level taxonomic commentary, preventing any associations being made on the cellular level. In each of the genes characterized from these experiments, a significant portion of sequences recovered show minimal phylogenetic affiliation to cultured organisms, preventing any understanding of inter-community dynamics and the functional capacities of these unknown organisms. Environmental genomics may provide insight into mat systems by allowing the correlation of functional genes with phylogenetic markers.

Smith, Jason M.↗