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Sub-Ångström-resolution MicroED Using a Direct Detection Camera
The recent development of microcrystal electron diffraction (MicroED) in electron cryo-microscopy (cryo-EM) has addressed many of the challenges of X-ray crystallography [1], filling a long-standing need in organic chemistry for rapid and accurate high-resolution structural characterization [2]. Like X-ray crystallography, this is also a diffraction technique requiring crystalline specimens, but because high energy electrons have a more favorable ration of elastic to inelastic scattering [3], MicroED can acquire data using crystals that are orders of magnitude smaller than those needed for X-ray crystallography—even as small as 50 nm in length [4]. Additionally, the instrumentation required for MicroED is readily available, as many chemistry and biology labs already have access to cryo-capable transmission electron microscopes (TEM).
A method for achieving complete microbial genomes and improving bins from metagenomics data
Metagenomics facilitates the study of the genetic information from uncultured microbes and complex microbial communities. Assembling complete genomes from metagenomics data is difficult because most samples have high organismal complexity and strain diversity. Some studies have attempted to extract complete bacterial, archaeal, and viral genomes and often focus on species with circular genomes so they can help confirm completeness with circularity. However, less than 100 circularized bacterial and archaeal genomes have been assembled and published from metagenomics data despite the thousands of datasets that are available. Circularized genomes are important for (1) building a reference collection as scaffolds for future assemblies, (2) providing complete gene content of a genome, (3) confirming little or no contamination of a genome, (4) studying the genomic context and synteny of genes, and (5) linking protein coding genes to ribosomal RNA genes to aid metabolic inference in 16S rRNA gene sequencing studies. We developed a semi-automated method called Jorg to help circularize small bacterial, archaeal, and viral genomes using iterative assembly, binning, and read mapping. In addition, this method exposes potential misassemblies from k-mer based assemblies. We chose species of the Candidate Phyla Radiation (CPR) to focus our initial efforts because they have small genomes and are only known to have one ribosomal RNA operon. In addition to 34 circular CPR genomes, we present one circular Margulisbacteria genome, one circular Chloroflexi genome, and two circular megaphage genomes from 19 public and published datasets. We demonstrate findings that would likely be difficult without circularizing genomes, including that ribosomal genes are likely not operonic in the majority of CPR, and that some CPR harbor diverged forms of RNase P RNA. Code and a tutorial for this method is available at https://github.com/lmlui/Jorg and is available on the DOE Systems Biology KnowledgeBase as a beta app.
Continuous-flow electrophoretic separator for biologicals
In the near absence of gravity, a continuous-flow type of electrophoretic separator can be operated with a much thicker separation chamber than is possible under 1 g conditions. This should permit either better resolution or shorter separation time per unit of sample. An apparatus to perform experiments on sounding rockets is under development and will be described. The electrophoresis cell is 5 mm thick by 5 cm wide with 10 cm long electrodes. It is supplied with buffer, sample, and coolant at about 4 C through the use of a passive refrigerant system. UV sample detection and provision for recovery and cold storage of up to 50 sample fractions are now being added to the basic unit. A wide range of operating conditions are electronically programmable into the unit, even up to a short time before flight, and a further range of some parameters can be achieved by exchanging power supplies and by changing gears in the motor drive units of the pump. The preliminary results of some separation studies on various biological products using a commercially available electrophoretic separator are also presented.
Sample selection and testing of separation processes
Phase partitioning, which has become an important tool for the separation and purification of biological materials, was studied. Instruments available for this technique were researched and a countercurrent distribution apparatus, the Biosheff MK2N, was purchased. Various proteins, polysaccharides and cells were studied as models to determine operating procedures and conditions for this piece of equipment. Results were compared with those obtained from other similar equipment, including a nonsynchronous coil planet centrifuge device. Additionally, work was done with affinity ligands attached to PEG, which can further enhance the separation capabilities of phase partitioning.
Apparent Minimum Free Energy Requirements for Methanogenic Archaea and Sulfate-Reducing Bacteria in an Anoxic Marine Sediment
Among the most fundamental constraints governing the distribution of microorganisms in the environment is the availability of chemical energy at biologically useful levels. To assess the minimum free energy yield that can support microbial metabolism in situ, we examined the thermodynamics of H2-consuming processes in anoxic sediments from Cape Lookout Bight, NC, USA. Depth distributions of H2 partial pressure, along with a suite of relevant concentration data, were determined in sediment cores collected in November (at 14.5 C) and August (at 27 C) and used to calculate free energy yields for methanogenesis and sulfate reduction. At both times of year, and for both processes, free energy yields gradually decreased (became less negative) with depth before reaching an apparent asymptote. Sulfate reducing bacteria exhibited an asymptote of -19.1 +/- 1.7 kj(mol SO4(2-)(sup -1) while methanogenic archaea were apparently supported by energy yields as small as -10.6 +/- 0.7 kj(mol CH4)(sup -1).
DNA in a Tunnel: A Comfy Spot for Recognition - or -The Structure of BsoBI Complexed with DNA. What can we Learn about Function via Structure Determination and how can this be Applied to Bone or Muscle Biology?
The structure and function of a biologically active molecule are related. To understand its function, it is necessary (but not always sufficient) to know the structure of the molecule. There are many ways of relating the molecular function with the structure. Mutation analysis can identify pertinent amino acids of an enzyme, or alternatively structure comparison of the of two similar molecules with different function may lead to understanding which parts are responsible for a functional aspect, or a series of "structural cartoons" - enzyme structure, enzyme plus substrate, enzyme with transition state analog, and enzyme with product - may give insight in the function of a molecule. As an example we will discuss the structure and function of the restriction enzyme BsoBI from Bacillus stearothemzophilus in complex with its cognate DNA. The enzyme forms a unique complex with DNA in that it completely encircles the DNA. The structure reveals the enzyme-DNA contacts, how the DNA is distorted compared with the canonical forms, and elegantly shows how two distinct DNA sequences can be recognized with the same efficiency. Based on the structure we may also propose a hypothesis how the enzymatic mechanism works. The knowledge gained thru studies such as this one can be used to alter the function by changing the molecular structure. Usually this is done by design of inhibitors specifically active against and fitting into an active site of the enzyme of choice. In the case of BsoBI one of the objectives of the study was to alter the enzyme specificity. In bone biology there are many candidates available for molecular study in order to explain, alter, or (temporarily) suspend activity. For example, the understanding of a pathway that negatively regulates bone formation may be a good target for drug design to stimulate bone formation and have good potential as the basis for new countermeasures against bone loss. In principle the same approach may aid muscle atrophy, radiation damage, immune response changes and other risks identified for long-duration Space travel.
An Open-Science Approach to Address Individual Response to Simulated GCR In Genetically Diverse Populations of Mice and Humans
This project addresses the challenge of understanding and predicting individual radiation sensitivity by integrating genetics, demographics and biomarker characteristics across species (mice and humans). We hypothesize that ex vivo DNA repair response to GCR components is a central determinant of cancer risk from space radiation and can serve as a biomarker of radiation risk in combination with genetics. Automated image quantification of 53BP1+ radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET in non-immortalized primary skin fibroblasts derived from 76 mice across 15 strains (5 inbred reference strains and 10 collaborative-cross strains) exposed to X rays (0.1, 1 and 4 Gy), 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm), as well as in peripheral blood mononuclear cells (PBMCs) from 768 healthy donors (matched ethnicity, 50/50 male/female, 18-70 years old) exposed to gamma rays (0.1 and 1 Gy), 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100sq. μm). A genome-wide association study (GWAS) was performed on the mouse strains between DNA damage responses to space radiation and single nucleotide polymorphisms (SNPs). We found SNPs, which were significantly associated to the RIF phenotype, mapped to genes and pathways that are functionally linked to health hazards for deep space exploration (e.g. carcinogenesis, nervous system damage and immune dysfunction). Some of these SNPs were located within protein coding regions, potentially interfering with protein functions and providing promising genetic targets for countermeasures. We also found correlations between both spontaneous and radiation-induced DNA damage and SNPs mapped to pathways associated with cellular metabolism. GWAS is undergoing for the human data. All data have been made available via the NASA Space Biology Open-Science database (genelab.nasa.gov) and we will discuss how various genomic and transcriptomic datasets can be accessed for modeling and integrated using machine learning methods for discovering new radiation biology.
Importance of Sulfur for Phosphorus Mobility on the Martian Surface
Sulfur and phosphorus were mobile on the martian surface, and we present evidence that sulfate was likely a control on phosphate mobility. Mobility of the two elements on the martian surface is crucial for the habitability of Mars because their availability for biochemical reactions and biological structures is a major constraint on life. In the sedimentary rocks of Gale crater, the rover Curiosity has discovered evidence of mobile S and P with the alpha particle X-ray spectrometer (APXS). Sulfur-rich fluids are evident in ubiquitous Ca-sulfate veins that crosscut the bedrock. Compelling evidence of P mobility is in nodules, veins, crusts, and haloes with P2O5 enrichments (1.5-7.5 wt%) relative to the median bedrock (0.9-1.2 wt%) and average basaltic crust (~0.9 wt%). We have investigated phosphorus mobility in Hawaiian analogues, where the primary P2O5 (0.2-2.1 wt%) is contained in Ca-apatite. Four relevant processes have emerged: (1) In open-system, circumneutral regolith weathering profiles, we found up to 40% of the P was leached over 10s-100s ka. (2) Natural acid-sulfate alteration at the Maunakea summit resulted in the dissolution of apatite and mobilization of phosphate 10s-1000s µm to rock surfaces where it formed Al-phosphates and substituted into crystalline sulfates (alunite and jarosite). (3) Experimental results indicate that basaltic sediment chemisorbs phosphate (pH < 7). (4) In experimental systems containing water, basaltic sediment, and a starting pH = 2-7, phosphate has higher solubility in chloride-rich fluids, but significantly lower solubility in sulfate-rich fluids. For example, in water doped with phosphate (~100-500 mg/L), ~60-80% of the PO43- was removed from the sulfate-rich fluid, whereas ~20% of the PO43- was removed from the Cl-rich and pure water fluids (likely via adsorption). Gypsum precipitated from the sulfate-rich fluids; the fate of phosphate in the solid residue is unconfirmed. The potential for phosphate incorporation in martian sulfates is reflected in the enrichment of P2O5 in Gale Ca-sulfate veins, based on preliminary analyses of APXS data. Models for the mobility of phosphorus in Gale crater should consider these conflicting P characteristics: (1) P solubility may have been inhibited by sulfate and (2) P¬ is enriched in diagenetic features and was therefore mobile.
CRAGE-Duet Facilitates Modular Assembly of Biological Systems for Studying Plant–Microbe Interactions
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Differential methods for assessing sensitivity in biological models
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to determine which method is best suited for a particular model. In this paper, we explain a variety of differential sensitivity methods and assess their value in some typical biological models. First, we explain the mathematical basis for three numerical methods: adjoint sensitivity analysis, complex perturbation sensitivity analysis, and forward mode sensitivity analysis. We then carry out four instructive case studies. (a) The CARRGO model for tumor-immune interaction highlights the additional information that differential sensitivity analysis provides beyond traditional naive sensitivity methods, (b) the deterministic SIR model demonstrates the value of using second-order sensitivity in refining model predictions, (c) the stochastic SIR model shows how differential sensitivity can be attacked in stochastic modeling, and (d) a discrete birth-death-migration model illustrates how the complex perturbation method of differential sensitivity can be generalized to a broader range of biological models. Finally, we compare the speed, accuracy, and ease of use of these methods. We find that forward mode automatic differentiation has the quickest computational time, while the complex perturbation method is the simplest to implement and the most generalizable.
A genomic perspective on fungal diversity and evolution
Originating from aquatic unicellular ancestors, over the course of ~1 billion years, the fungi have evolved to occupy nearly all aerobic environments on the planet, diversified into millions of different ‘species’ and have developed complex multicellular structures. Their relatively small, simple genomes have facilitated massive-scale sequencing and allowed us to explore genome evolution across an ancient eukaryotic kingdom. With thousands of genomes from diverse lineages now available, this Review will discuss insights into fungal biology and evolution gleaned with genomics and other multi-omics approaches. Using published genomes available through GenBank and the Joint Genome Institute’s MycoCosm platform, we generated kingdom-wide phylogenies and used them to highlight how fungal genomes have changed over time. With this phylogeny as a guide, we also discuss major evolutionary transitions that occurred across the fungal kingdom. Although progress has been made, these efforts are hampered by biases in genome representation and limited characterization of gene functions. Here, in this study, we discuss these challenges and possible future directions to address them, including initiatives to characterize conserved genes of unknown function and scale up sequencing towards 10,000 annotated fungal genomes.
Thinking of biology: toward a theory of cellularity--speculations on the nature of the living cell
No abstract available
Light and carbon: Synthetic biology toward new cyanobacteria-based living biomaterials
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Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution
Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO 2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including E. coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate limiting steps in biological ethylene production. We employed a combination of genome scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to the EFE enzyme (WT vs mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.
Editorial: Systems Biology and Synthetic Biology in Relation to Drought Tolerance or Avoidance in Plants
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Creating Benchmark Data for Artificial Intelligence and Machine Learning Space Biology Research
To identify an appropriate AI/ML approach for a specific problem, the best practice is to measure algorithm performance through the benchmarking process. A scientific benchmark consists of an AI-ready dataset and a reference implementation on a specific scientific question. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML to create scientific benchmark datasets in three applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. Currently, there are no standardized datasets available to benchmark AI/ML algorithms in the domain of space biology. In this work, we constructed two AI/ML-ready biological datasets from experiments in space-flown mice: cellular imaging and RNA-seq. First, radiation-exposed immune cells harbor DNA damage foci that can be fluorescently marked to visualize the amount of damage following exposure to ionizing radiation. However, such large datasets are difficult to analyze visually, due to imaging inconsistencies and human bias, and classical image processing approaches can fail on imaging artifacts. AI/ML are therefore exciting alternative, providing the speed of machines and the accuracy of humans. We have made this dataset available at https://registry.opendata.aws/bps_microscopy/. Second, high-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. However, most sequencing datasets suffer from high dimensionality and low sample count. In this work, we used a generative adversarial network to synthesize a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data with sufficient space-flown and ground control mouse liver samples from NASA GeneLab. This dataset is available at https://registry.opendata.aws/bps_rnaseq/. These datasets are now fully open the Space Biology community to test their favorite AI/ML approaches.