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At least 235 records · Page 13

Soil microbiome resilience to short-term (30 days, 90 days) and long-term (1000 days) drought

This dataset contains data used for the paper "Drought duration does not impact soil microbiome resilience". The Related References will be updated with a full citation when available. Increasing global droughts exert large but poorly understood effects on the microbial communities and ecology of soil. Microbial communities generally show resilience and return to pre-drought conditions when short-term droughted soils are rewet; soils exposed to long-term drought, however, often show a lag upon rewetting, after which microbial communities may or may not return to their pre-stressed conditions. Though short-term droughts have been widely studied, long-term drought manipulation experiments remain rare, especially those that compare microbial response to short-term and long-term drought in tandem. We conducted a 1000-day drought simulation in controlled laboratory conditions with soil cores collected from a tidal freshwater ecosystem in Washington state, USA, and subsequently exposed them to rewetting for two weeks. We also included short-term (30-day and 90-day) drought and rewet treatments to directly compare microbial community and organic matter responses across drought durations. We found distinct microbial taxa belonging to Firmicutes and Actinobacteria enriched after the 1000-day drought, but not after the short-term droughts. While we hypothesized that the microbial community would recover from a short-term drought after rewetting to resemble pre-drought conditions, our results revealed community dissimilarities between rewet and pre-drought conditions across all drought durations. These findings suggest unique microbial life history strategies within certain microbial phyla that make them successful colonizers during an extended drought period, and the influence of environmental and physiological context on microbial responses to rewetting. The 16SrRNA gene amplicon dataset contains processed DNA sequences in the form of an ASV table with raw unrarefied read counts and representative sequences in .fasta format as described in the ESS-DIVE amplicon sequence reporting format (https://ess-dive.gitbook.io/amplicon-sequencing-reporting-format/instructions). The Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) dataset consists of processed files containing presence absence data of molecular formulae and molecular characterization of FTICR resolved peaks. The Nuclear Magnetic Resonance (NMR) dataset contains files relevant to NMR spectra and peaks. A sample key file and a sample metadata file is included for the FTICR/NMR and 16S dataset respectively.

1000-day drought↗

Technology Summary DNATRAX

DNATrax (DNA Tagged Reagents for Aerosol eXperiments) was developed to provide a safe simulant for understanding the transport and dispersion of pathogens. Specifically, it was developed as a safe surrogate for the Bacillus anthrasis spore bioagent, since most naturally occurring spores are not safe for public release. As DNA-tagged sugar particles, DNATrax aerosols are safe for public release. Scientists can add unique DNA barcode sequences to the sugar particles to produce a wide variety of test particles that can be easily differentiated, making it possible to release and test them simultaneously. The unique barcodes also eliminate the need to conduct decontamination between tests, dramatically reducing the cost and time to run experiments. Additionally, the surrogate offers a high-sensitivity detection method to understand key public health issues. We conducted both lab-based and largescale field studies using DNATrax to validate its capabilities for use as a pathogen surrogate. We have demonstrated the ability to produce DNATrax in a range of sizes, adjusting the microparticles to simulate different sized pathogens with ability to create unique sequences of DNA bases, enabling them to create a nearly unlimited variety of test particles.

59 BASIC BIOLOGICAL SCIENCES↗

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗

Bubble lifetimes in DNA gene promoters and their mutations affecting transcription

Relative lifetimes of inherent double stranded DNA openings with lengths up to ten base pairs are presented for different gene promoters and corresponding mutants that either increase or decrease transcriptional activity, in the framework of the Peyrard-Bishop-Dauxois model. Extensive microcanonical simulations are used, with energies corresponding to physiological temperature. The bubble lifetime profiles along the DNA sequences demonstrate a significant reduction of the average lifetime at the mutation sites when the mutated promoter decreases transcription, while a corresponding enhancement of the bubble lifetime is observed in the case of mutations leading to increased transcription. The relative difference of bubble lifetimes between the mutated and the wild type promoters at the position of mutation varies from 20% to more than 30% as the bubble length is decreasing.

59 BASIC BIOLOGICAL SCIENCES↗

Physical, resource supply, and biological controls on nutrient processing along the river continuum

Nutrient impairment has led to damages to US surface and groundwater systems in excess of 100 billion dollars per year. Therefore, there is a strong need to develop methods to predict the transport, uptake, and export of nutrients along fluvial networks. We present results that are based on a data-driven mechanistic understanding of three factors that largely control nutrient uptake and export: 1) interactions between transport-related processes (mass transfer to metabolically active zones), 2) resource supply dynamics (nutrient concentration, stoichiometric constraints, etc.), and 3) biological controls (microbial community structure and function). Our results were generated from column experiments conducted along the Jemez River-Rio Grande continuum, which spans four orders of magnitude in mean annual discharge, more than 2000 m in altitude, and more than 500 km of stream longitude. Two resource supply injections were performed on each of the columns, i.e., a nitrate only addition, followed by a stoichiometrically ‘balanced’ 106Carbon:16Nitrogen:1Phosphorus addition. We quantified NO3-N uptake kinetics while constraining three variables: stream order, sediment type and type of injection (N vs stoichiometrically ‘balanced’ C:N:P). Following the laboratory nutrient uptake experiments, the columns were destructively sampled and the contents were homogenized to collect subsamples for DNA sequencing. Amplicon analysis was carried out as described by the Earth Microbiome Protocol for 16s and ITS sequencing.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Ice Nucleating Particles and Their Sources in the Central Arctic during MOSAiC

The Arctic is warming faster than any other region on Earth, causing glaciers to melt, frozen ground to thaw, and the Arctic Ocean's ice to shrink. These consequential changes induce feedback loops that exacerbate warming and affect weather and climate worldwide. Microscopic airborne particles called "aerosols" and clouds in the sky are crucial for regulating heat and light reaching the Arctic surface. However, the magnitude of their effects is not adequately quantified, especially in the central Arctic, where they impact temperatures directly over the sea ice. Unique aerosols called "ice nucleating particles" (INPs), which play a significant role in cloud ice production, remain understudied. Understanding how ice forms in clouds is critical in the Arctic, as it affects cloud lifespan, interactions with heat and light, and precipitation. In this project, we conducted the first-ever observations of INPs in the middle of the Arctic over a whole year, covering the entire period when sea ice grows and melts. Furthermore, these are the first observations of INPs in different size ranges throughout the year, anywhere in the world. We use DNA sequencing to evaluate the presence of various types of microorganisms, while INP measurements on seawater, sea ice, snow, and meltwater samples help assess potential local Arctic sources of INPs. The results from this work are currently being used to improve the accuracy of Arctic cloud formation in various models.

54 ENVIRONMENTAL SCIENCES↗

MR13A-3183: Microbial and Geochemical Characterization of Groundwater: Implications for Underground Hydrogen Storage Leakage

Underground hydrogen storage (UHS) in geological formations is a key element of the clean energy transition as it enables the decarbonization of the transportation and industrial sectors by decoupling hydrogen production and storage. UHS has many benefits, including low cost, much wider availability, large storage capacity, well-established infrastructure, and increased safety because of geological sealing capabilities. However, the impact of hydrogen (H2) biogeochemical interactions in the presence of subsurface microorganisms is largely neglected from UHS perspectives. These interactions might affect the effectiveness of storage and can even cause H2 to leak into the shallow aquifers. Leakage of H2 into groundwater can change the geochemistry and induce several microbial-driven processes. Microorganisms, such as sulfate-reducers, are naturally abundant in groundwater and consume H2 to produce hydrogen sulfide (H2S), which can contaminate the freshwater drinking groundwater and cause damage to infrastructure. Hydrogen leakage can also trigger microbial reactions responsible for metal mobility, which can impact the water quality. However, the kinetics of these reactions and the temporal impact of hydrogen leakage in groundwater are still unknown. Therefore, a time series hydrogen-groundwater interaction experiment was conducted, and the changes in fluid chemistry and headspace gas composition will be analyzed along with DNA sequencing results to understand the extent and kinetics of biogeochemical reactions that occur if hydrogen leaks into groundwater. In the experiments, Ultra High Purity (UHP) hydrogen gas will be injected into glass vials with groundwater samples, for a designated time period. For each glass-sealed vial, 16S rRNA gene sequencing, IC, ICP-MS, and GC-TCD will be performed. The experiments provide insights into plausible impacts of hydrogen leakage into shallow drinking water aquifers.

Clark, Allison [West Virginia University (WVU)]↗

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗

Nanopore Readable Activity Probes for Ribosomal Inactivating Protein (RIP) Toxins

Ribosome inactivating proteins (RIPs) such as ricin and abrin depurinate an adenine base in the sarcin/ricin loop in the large ribosomal subunit, leading to inhibtion of protein synthesis and cell death. Here, we demonstrate that RIP toxin activity can be detected via nanopore-based DNA sequencing using synthetic oligonucleotide substrates. This is achieved by monitoring the mismatch proportion at the canonical target sequences incorporated into the synthetic substrate and determining the sequence length distribution throughout the entire substrate sequence. The mismatch proportion increases and sequence length distribution decreases with increasing toxin concentration for both ricin and abrin in buffer as well as in more complex backgrounds such as saliva and nasal secretions.

Turner, Matthew W [Pacific Northwest National Labo↗

Introduction to Metadata and Ontologies: Everything You Always Wanted to Know About Metadata and Ontologies (But Were Afraid to Ask)

Metadata are contextual data about your experimental data. Metadata are the who, what, when, where, and why of these data. Metadata puts these data into context. In microbiome research, metadata includes information about the sample: when it was collected, where it was collected from, what kind of sample it is, and what were the properties of the environment or experimental condition from which the sample was taken. Information about sample processing is also metadata: methods used to extract and purify molecules (e.g., DNA) from the sample, type of DNA sequencing or other ’omics analyses done, and where the raw experimental data are located. This documentation includes information on the following topics: What are metadata? What kinds of metadata are there? Why are metadata important? Why should metadata be standardized? Why should metadata be machine readable? What is an ontology? Why are ontologies important? What are some examples of ontologies? The documentation also includes further resources on metadata guides and tools and tips for formatting metadata for maximum utility.

59 BASIC BIOLOGICAL SCIENCES↗

Investigation of microorganisms in cannabis after heating in a commercial vaporizer

There are concerns about microorganisms present on cannabis materials used in clinical settings by individuals whose health status is already compromised and are likely more susceptible to opportunistic infections from microbial populations present on the materials. Most concerning is administration by inhalation where cannabis plant material is heated in a vaporizer, aerosolized, and inhaled to receive the bioactive ingredients. Heating to high temperatures is known to kill microorganisms including bacteria and fungi; however, microbial death is dependent upon exposure time and temperature. It is unknown whether the heating of cannabis at temperatures and times designated by a commercial vaporizer utilized in clinical settings will significantly decrease the microbial loads in cannabis plant material. To assess this question, bulk cannabis plant material supplied by National Institute on Drug Abuse (NIDA) was used to assess the impact of heating by a commercial vaporizer. Initial method development studies using a cannabis placebo spiked with Escherichia coli were performed to optimize culture and recovery parameters. Subsequent studies were carried out using the cannabis placebo, low delta-9 tetrahydrocannabinol (THC) potency and high THC potency cannabis materials exposed to either no heat or heating for 30 or 70 seconds at 190°C. Phosphate-buffered saline was added to the samples and the samples agitated to suspend the microorganism. Microbial growth after no heat or heating was evaluated by plating on growth media and determining the total aerobic microbial counts and total yeast and mold counts. Overall, while there were trends of reductions in microbial counts with heating, these reductions were not statistically significant, indicating that heating using standard vaporization parameters of 70 seconds at 190°C may not eliminate the existing microbial bioburden, including any opportunistic pathogens. When cultured organisms were identified by DNA sequence analyses, several fungal and bacterial taxa were detected in the different products that have been associated with opportunistic infections or allergic reactions including Enterobacteriaceae, Staphylococcus, Pseudomonas, and Aspergillus.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative Analysis of Microbial Diversity Across Temperature Gradients in Hot Springs From Yellowstone and Iceland

Geothermal hot springs are a natural setting to study microbial adaptation to a wide range of temperatures reaching up to boiling. Temperature gradients lead to distinct microbial communities that inhabit their optimum niches. We sampled three alkaline, high temperature (80–100°C) hot springs in Yellowstone and Iceland that had cooling outflows and whose microbial communities had not been studied previously. The microbial composition in sediments and mats was determined by DNA sequencing of rRNA gene amplicons. Over three dozen phyla of Archaea and Bacteria were identified, representing over 1700 distinct organisms. We observed a significant non-linear reduction in the number of microbial taxa as the temperature increased from warm (38°C) to boiling. At high taxonomic levels, the community structure was similar between the Yellowstone and Iceland hot springs. We identified potential endemism at the genus level, especially in thermophilic phototrophs, which may have been potentially driven by distinct environmental conditions and dispersal limitations.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial Community Characteristics Largely Unaffected by X-Ray Computed Tomography of Sediment Cores

X-ray computed tomography (CT) scanning is used to study the physical characteristics of soil and sediment cores, allowing scientists to analyze stratigraphy without destroying core integrity. Microbiologists often work with geologists to understand the microbial properties in such cores; however, we do not know whether CT scanning alters microbial DNA such that DNA sequencing, a common method of community characterization, changes as a result of X-ray exposure. Our objective was to determine whether CT scanning affects the estimates of the composition of microbial communities that exist in cores. Sediment cores were extracted from a salt marsh and then submitted for CT scanning. We observed a minimal effect of CT scanning on microbial community composition in the sediment cores either when the cores were examined shortly after recovery from the field or after the cores had been stored for several weeks. In contrast, properties such as sediment layer and marsh location did affect microbial community structure. While we observed that CT scanning did not alter microbial community composition as a whole, we identified a few amplicon sequence variants (13 out of 7,037) that showed differential abundance patterns between scanned and unscanned samples among paired sample sets. Our overall conclusion is that the CT-scanning conditions typically used to obtain images for geological core characterization do not significantly alter microbial community structure. We stress that minimizing core exposure to X-rays is important if cores are to be studied for biological properties. Future investigations might consider variables, such as the length and energy of radiation exposure, the volume of the core, or the degree, to which microbial communities are stressed as important factors in assessing the impact of X-rays on microbes in geological cores.

59 BASIC BIOLOGICAL SCIENCES↗

Isolation of phosphorus-hyperaccumulating microalgae from revolving algal biofilm (RAB) wastewater treatment systems

Excess phosphorus (P) in wastewater effluent poses a serious threat to aquatic ecosystems and can spur harmful algal blooms. Revolving algal biofilm (RAB) systems are an emerging technology to recover P from wastewater before discharge into aquatic ecosystems. In RAB systems, a community of microalgae take up and store wastewater P as polyphosphate as they grow in a partially submerged revolving biofilm, which may then be harvested and dried for use as fertilizer in lieu of mined phosphate rock. In this work, we isolated and characterized a total of 101 microalgae strains from active RAB systems across the US Midwest, including 82 green algae, 9 diatoms, and 10 cyanobacteria. Strains were identified by microscopy and 16S/18S ribosomal DNA sequencing, cryopreserved, and screened for elevated P content (as polyphosphate). Seven isolated strains possessed at least 50% more polyphosphate by cell dry weight than a microalgae consortium from a RAB system, with the top strain accumulating nearly threefold more polyphosphate. These top P-hyperaccumulating strains include the green alga Chlamydomonas pulvinata TCF-48 g and the diatoms Eolimna minima TCF-3d and Craticula molestiformis TCF-8d, possessing 11.4, 12.7, and 14.0% polyphosphate by cell dry weight, respectively. As a preliminary test of strain application for recovering P, Chlamydomonas pulvinata TCF-48 g was reinoculated into a bench-scale RAB system containing Bold basal medium. The strain successfully recolonized the system and recovered twofold more P from the medium than a microalgae consortium from a RAB system treating municipal wastewater. These isolated P-hyperaccumulating microalgae may have broad applications in resource recovery from various waste streams, including improving P removal from wastewater.

54 ENVIRONMENTAL SCIENCES↗

Engineering custom morpho- and chemotypes of Populus for sustainable production of biofuels, bioproducts, and biomaterials

Humans have been modifying plant traits for thousands of years, first through selection (i.e., domestication) then modern breeding, and in the last 30 years, through biotechnology. These modifications have resulted in increased yield, more efficient agronomic practices, and enhanced quality traits. Precision knowledge of gene regulation and function through high-resolution single-cell omics technologies, coupled with the ability to engineer plant genomes at the DNA sequence, chromatin accessibility, and gene expression levels, can enable engineering of complex and complementary traits at the biosystem level. Populus spp., the primary genetic model system for woody perennials, are among the fastest growing trees in temperate zones and are important for both carbon sequestration and global carbon cycling. Ample genomic and transcriptomic resources for poplar are available including emerging single-cell omics datasets. To expand use of poplar outside of valorization of woody biomass, chassis with novel morphotypes in which stem branching and tree height are modified can be fabricated thereby leading to trees with altered leaf to wood ratios. These morphotypes can then be engineered into customized chemotypes that produce high value biofuels, bioproducts, and biomaterials not only in specific organs but also in a cell-type-specific manner. For example, the recent discovery of triterpene production in poplar leaf trichomes can be exploited using cell-type specific regulatory sequences to synthesize high value terpenes such as the jet fuel precursor bisabolene specifically in the trichomes. By spatially and temporally controlling expression, not only can pools of abundant precursors be exploited but engineered molecules can be sequestered in discrete cell structures in the leaf. The structural diversity of the hemicellulose xylan is a barrier to fully utilizing lignocellulose in biomaterial production and by leveraging cell-type-specific omics data, cell wall composition can be modified in a tailored and targeted specific manner to generate poplar wood with novel chemical features that are amenable for processing or advanced manufacturing. Precision engineering poplar as a multi-purpose sustainable feedstock highlights how genome engineering can be used to re-imagine a crop species.

09 BIOMASS FUELS↗

Roles for epigenetics in wood formation and stress response intrees–from basic biology to forest management

Annual model and crop species have been the subject of most epigenetic studies for plants. In contrast to annuals, forest trees persist on natural landscapes and experience environmental variation within and across seasons, years, and decades or even centuries. Most forest trees species are undomesticated and typically grown on variable landscapes with no irrigation or application of agricultural chemicals. Forest trees must thus rely on their inherent ability to alter growth and physiology to mitigate the effects of changing abiotic and biotic stressors. Like other plants, trees have mechanisms encoded in their genomic DNA sequence that can respond directly to stress events such as drought or heat. Hypothetically, it would be highly advantageous to join these mechanisms with a dynamic “memory” of past exposure to stress. It is now well established that annual model and crop plants can establish epigenetic-based memory of stress events that support more rapid and robust response to stress in the future. Here, evidence is discussed for epigenetic regulation and “memory” in two fundamental biological processes in trees, wood formation and abiotic stress response. Wood formation is an ideal trait for epigenetic research in trees, as wood formation is highly responsive to environmental conditions and includes multiple rapid developmental changes as cells adopt distinct fates within complex tissues. This is followed by a discussion of research needs that would provide the foundation for new epigenetic applications for forestry.

Groover, Andrew↗

Cloned Hemoglobin Genes Enhance Growth Of Cells

Experiments show that portable deoxyribonucleic acid (DNA) sequences incorporated into host cells make them produce hemoglobins - oxygen-binding proteins essential to function of red blood cells. Method useful in several biotechnological applications. One, enhancement of growth of cells at higher densities. Another, production of hemoglobin to enhance supplies of oxygen in cells, for use in chemical reactions requiring oxygen, as additive to serum to increase transport of oxygen, and for binding and separating oxygen from mixtures of gases.

Khosla, Chaitan↗

In vitro selection of optimal DNA substrates for T4 RNA ligase

We have used in vitro selection techniques to characterize DNA sequences that are ligated efficiently by T4 RNA ligase. We find that the ensemble of selected sequences ligated about 10 times as efficiently as the random mixture of sequences used as the input for selection. Surprisingly, the majority of the selected sequences approximated a well-defined consensus sequence.

Harada, Kazuo↗