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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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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantifying metal-binding specificity of Cc NikZ-II from Clostridium carboxidivorans in the presence of competing metal ions

Many proteins bind transition metal ions as cofactors to carry out their biological functions. Despite binding affinities for divalent transition metal ions being predominantly dictated by the Irving-Williams series for wild-type proteins, in vivo metal ion binding specificity is ensured by intracellular mechanisms that regulate free metal ion concentrations. However, a growing area of biotechnology research considers the use of metal-binding proteins in vitro to purify specific metal ions from wastewater, where specificity is dictated by the protein's metal binding affinities. A goal of metalloprotein engineering is to modulate these affinities to improve a protein's specificity towards a particular metal; however, the quantitative relationship between the affinities and the equilibrium metal-bound protein fractions depends on the underlying binding mechanisms. Here we demonstrate a high-throughput intrinsic tryptophan fluorescence quenching method to validate binding models in multi-metal solutions for CcNikZ-II, a nickel-binding protein from Clostridium carboxidivorans. Using our validated models, we quantify the relationship between binding affinity and specificity in different classes of metal-binding models for CcNikZ-II. In conclusion, we further illustrate the potential relevance of data-informed models to predicting engineering targets for improved specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Beyond the Active Site: The Impact of the Outer Coordination Sphere on Electrocatalysts for Hydrogen Production and Oxidation

Hydrogenase enzymes provide inspiration for investigations of molecular catalysts utilizing structural and functional mimics of the active site. However, the resulting active site mimics cannot match the combination of high rates and low overpotentials of the enzyme, suggesting that the rest of the protein scaffold, i.e., the outer coordination sphere, is necessary for the efficiency of hydrogenase. Therefore, inclusion of outer coordination sphere elements onto molecular catalysts may enable us to achieve and ultimately surpass the overall enzymatic efficiency. In an effort to identify and include the missing enzymatic features, there has been recent effort to understand the effect of outer coordination sphere elements on molecular catalysts for hydrogen oxidation and production. Our focus has been to utilize amino acid or peptide based scaffolds on an active functional mimic for hydrogen oxidation and production, [Ni(PR2NR’2)2]2+. This bottom-up approach, i.e, building an outer coordination sphere around a functional molecular catalyst, has allowed us to evaluate individual contributions to catalysis, including enhancing proton movement, concentrating substrate and introducing structural features to control reactivity. Collectively, these studies have resulted in catalysts that can operate faster, can operate at lower overpotentials, have enhanced water solubility, and/or can provide more stability to oxygen or extreme conditions such as strongly acidic or basic conditions than their unmodified parent complexes. Common mechanisms have yet to be defined to predictably control these processes but our growing knowledge in this area is essential for the eventual mimicry of enzymes for developing efficient molecular catalysts for practical use. This account reviews previously published work supported by the US DOE Basic Energy Sciences (BES), Physical Bioscience program, the Office of Science Early Career Research Program through the USDOE, BES, the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the US DOE, Office of Science, Office of BES. Part of the research was conducted at the W.R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by U.S. DOE’s Office of Biological and Environmental Research program located at Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for the U.S. Department of Energy.

bioinspired↗
DOE OSTI2020

Bottom-Up Meets Top-Down: The Crossroads of Multiscale Chromatin Modeling

Chromatin can be viewed as a hierarchically structured fiber that regulates gene expression. It consists of a complex network of DNA and proteins whose characteristic dynamical modes facilitate compaction and rearrangement in the cell nucleus. These modes stem from chromatin's fundamental unit, the nucleosome, and their effects are propagated across length scales. Understanding the effects of nucleosome dynamics on the chromatin fiber, primarily through post-translational modifications that occur on the histones, is of central importance to epigenetics. Within the last decade, imaging and chromosome conformation capture techniques have revealed a number of structural and statistical features of the packaged chromatin fiber at a hitherto unavailable level of resolution. Such experiments have led to increased efforts to develop polymer models that aim to reproduce, explain, and predict the contact probability scaling and density heterogeneity. At nanometer scales, available models have focused on the role of the nucleosome and epigenetic marks on local chromatin structure. At micrometer scales, existing models have sought to explain scaling laws and density heterogeneity. Less work, however, has been done to reconcile these two approaches: bottom-up and top-down models of chromatin. Here, we highlight the multiscale simulation models that are driving toward an understanding of chromatin structure and function, from the nanometer to the micron scale, and we highlight areas of opportunity and some of the prospects for new frameworks that bridge these two scales. Taken together, experimental and modeling advances over the last few years have established a robust platform for the study of chromatin fiber structure and dynamics, which will be of considerable use to the chromatin community in developing an understanding of the interplay between epigenomic regulation and molecular structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Experimental and calculated infrared spectra of disubstituted naphthoquinones

In recent years there has been interest in incorporating substituted 1,4-naphthoquinones (NQs) into the A 1 binding site in photosystem I (PSI) photosynthetic protein complexes. This interest in part stems from the considerably altered bioenergetics of electron transfer that occur in PSI with such substitutions. Time resolved FTIR studies of PSI complexes with disubstituted NQs incorporated have and currently are being undertaken, and with this in mind it is worth considering FTIR absorption spectra of these disubstituted NQs in solution. Here we present FTIR absorbance spectra for 2-bromo-3-methyl-1,4-naphthoquinone (BrMeNQ), 2-chloromethyl-3-methyl-1,4-naphthoquinone (CMMeNQ) and 2-ethylthio-3-methyl-1,4-naphthoquinone (ETMeNQ) in tetrahydrofuran (THF). The FTIR spectra of these di-substituted naphthoquinones (NQs) were compared to FTIR spectra of 2-methyl-3-phytyl-1,4-naphthoquinone [phylloquinone (PhQ)], 2,3-dimethyl-1,4-naphthoquinone (DMNQ), and 2-methyl-1,4-naphthoquinone (2MNQ). To aid in the assignment of bands in the experimental spectra, density functional theory (DFT) based vibrational frequency calculations for all the substituted NQs in solution were undertaken. The calculated and experimental spectra agree well. By calculating normal mode potential energy distributions, unambiguous quantitative band assignments were made. The calculated and experimental spectra together make predictions about what may be observable in time resolved FTIR difference spectra obtained using PSI with the different NQs incorporated. As a result, time resolved FTIR difference spectra are presented that support these predictions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

RegPrecise 3.0 – A resource for genome-scale exploration of transcriptional regulation in bacteria

Background: Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). Description: RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. Conclusions: RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Conformational heterogeneity in closed and open states of the KcsA potassium channel in lipid bicelles

The process of ion channel gating—opening and closing—involves local and global structural changes in the channel in response to external stimuli. Conformational changes depend on the energetic landscape that underlies the transition between closed and open states, which plays a key role in ion channel gating. For the prokaryotic, pH-gated potassium channel KcsA, closed and open states have been extensively studied using structural and functional methods, but the dynamics within each of these functional states as well as the transition between them is not as well understood. In this study, we used solution nuclear magnetic resonance (NMR) spectroscopy to investigate the conformational transitions within specific functional states of KcsA. We incorporated KcsA channels into lipid bicelles and stabilized them into a closed state by using either phosphatidylcholine lipids, known to favor the closed channel, or mutations designed to trap the channel shut by disulfide cross-linking. A distinct state, consistent with an open channel, was uncovered by the addition of cardiolipin lipids. Using selective amino acid labeling at locations within the channel that are known to move during gating, we observed at least two different slowly interconverting conformational states for both closed and open channels. The pH dependence of these conformations and the predictable disruptions to this dependence observed in mutant channels with altered pH sensing highlight the importance of conformational heterogeneity for KcsA gating.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Charging of Proteins in Native Mass Spectrometry

Factors that influence the charging of protein ions formed by electrospray ionization from aqueous solutions in which proteins have native structures and function were investigated. Protein ions ranging in molecular weight from 12.3 to 79.7 kDa and pI values from 5.4 to 9.6 were formed from different solutions and reacted with volatile bases of gas-phase basicities higher than that of ammonia in the cell of a Fourier-transform ion cyclotron resonance mass spectrometer. The charge-state distribution of cytochrome c ions formed from aqueous ammonium or potassium acetate is the same. Moreover, ions formed from these two solutions do not undergo proton transfer to 2-fluoropyridine, which is 8 kcal/mol more basic than ammonia. These results provide compelling evidence that proton transfer between ammonia and protein ions does not limit protein ion charge in native electrospray ionization. Both circular dichroism and ion mobility measurements indicate that there are differences in conformations of proteins in pure water and aqueous ammonium acetate, and these differences can account for the difference in the extent of charging and proton-transfer reactivities of protein ions formed from these solutions. The extent of proton transfer of the protein ions with higher gas-phase basicity bases trends with how closely the protein ions are charged to the value predicted by the Rayleigh limit for spherical water droplets approximately the same size as the proteins. These results indicate that droplet charge limits protein ion charge in native mass spectrometry and are consistent with these ions being formed by the charged residue mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Heregulin, a new interactor of the telosome/shelterin complex in human telomeres

Telomere length, shape and function depend on a complex of six core telomere-associated proteins referred to as the telosome or shelterin complex. We here demonstrate that the isoform β2 of the heregulin family of growth factors (HRGβ2) is a novel interactor of the telosome/shelterin complex in human telomeres. Analysis of protein-protein interactions using a high-throughput yeast two-hybrid (Y2H) screen identified RAP1, the only telomere protein that is conserved from yeasts to mammals, as a novel interacting partner of HRGβ2. Deletion analysis of RAP1 revealed that the linker domain, a region previously suggested to recruit negative regulators of telomere length, interacts specifically with HRGβ2. Co-immunoprecipitation and imaging experiments demonstrated that, in addition to RAP1, HRGβ2 could associate with the RAP1-associated telomeric repeat binding factor 2 (TRF2). Deletion analysis of HRGβ2 confirmed that a putative nuclear localization signal (NLS) was necessary for nuclear HRGβ2 to exert a negative regulation of telomere length whereas the N-terminus (extracellular) amino acids of HRGβ2 were sufficient to interact with RAP1/TRF2 and promote telomere shortening. Taken together, our studies identify nuclear HRGβ2 as one of the previously unknown regulators predicted to be recruited by the RAP1 linker domain to negatively regulate telomere length in human cells. Our current findings reveal that a new, but likely not the last, unexpected visitor has arrived to the “telosome/shelterin town”.

Cell Biology↗
DOE OSTI2020

Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction

Oxidation states of individual metal atoms within a metalloprotein can be assigned by examining X-ray absorption edges, which shift to higher energy for progressively more positive valence numbers. Indeed, X-ray crystallography is well suited for such a measurement, owing to its ability to spatially resolve the scattering contributions of individual metal atoms that have distinct electronic environments contributing to protein function. However, as the magnitude of the shift is quite small, about +2 eV per valence state for iron, it has only been possible to measure the effect when performed with monochromated X-ray sources at synchrotron facilities with energy resolutions in the range 2–3 × 10 −4 (Δ E / E ). This paper tests whether X-ray free-electron laser (XFEL) pulses, which have a broader bandpass (Δ E / E = 3 × 10 −3 ) when used without a monochromator, might also be useful for such studies. The program nanoBragg is used to simulate serial femtosecond crystallography (SFX) diffraction images with sufficient granularity to model the XFEL spectrum, the crystal mosaicity and the wavelength-dependent anomalous scattering factors contributed by two differently charged iron centers in the 110-amino-acid protein, ferredoxin. Bayesian methods are then used to deduce, from the simulated data, the most likely X-ray absorption curves for each metal atom in the protein, which agree well with the curves chosen for the simulation. The data analysis relies critically on the ability to measure the incident spectrum for each pulse, and also on the nanoBragg simulator to predict the size, shape and intensity profile of Bragg spots based on an underlying physical model that includes the absorption curves, which are then modified to produce the best agreement with the simulated data. This inference methodology potentially enables the use of SFX diffraction for the study of metalloenzyme mechanisms and, in general, offers a more detailed approach to Bragg spot data reduction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Systemic Microgravity Response: Utilizing GeneLab to Develop Hypotheses for Spaceflight Risks

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales.

GeneLab↗
DOE OSTI2025

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

The Study of Microbial Environmental Processes Related to the Natural Attenuation of Uranium at the Rifle Site using Systems-level Biology

Microbes exist in communities in the environment where they are fundamental drivers of global carbon, nutrient and metal cycles. In subsurface environments, they possess significant metabolic potential to affect these global cycles including the transformation of radionuclides. This study examined the influence of microbial communities in sediment zones undergoing biogeochemical cycling of carbon, nutrients and metals including natural attenuation of uranium. This study examined the relationship of both the microbiota (taxonomy) and their metabolic capacity (function) in driving carbon, nutrient and metal cycles including uranium reduction at the Department of Energy (DOE) Rifle Integrated Field Research Challenge (RIFRC). Objectives of this project were: 1) to apply systems-level biology through application of ‘metaomics’ approaches (collective analyses of whole microbial community DNA, RNA and protein) to the study of microbial environmental processes and their relationship to C, N and metals including the influence of microbial communities on uranium contaminant mobility in subsurface settings undergoing natural attenuation, 2) improve methodologies for data generation using metaomics (collectively metagenomics, metatranscriptomics and proteomics) technologies and analysis and interpretation of that data and 3) use the data generated from these studies towards microbial community-scale metabolic modeling. The strategy for examining these subsurface microbial communities was to generate sequence reads from microbial community DNA (metagenomics or whole genome shotgun sequencing (WGS)) and RNA (metatranscriptomcs or RNAseq) and protein information using proteomics. Results were analyzed independently and through computational modeling. Overall, the community model generated information on the microbial community structure that was observed using metaomic approaches at RIFRC sites and thus provides an important framework for continued community modeling development. The model as created is capable of predicting the response of the community structure in changing environments such as anoxic/oxic conditions or limitations by carbon or nutrients. The ability to more accurately model these responses is critical to understanding carbon and energy flows in an ecosystem is critical towards improving our ability to make predictions that can be used to design more efficient remediation and management strategies, and better understand the implications of environmental perturbations on these ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Selective Labeling and Decoration of the Ends and Sidewalls of Single-Walled Carbon Nanotubes Using Mono- and Bispecific Solid-Binding Fluorescent Proteins

Simple and robust strategies for the noncovalent functionalization of carbon nanostructures with proteins are of considerable interest in hybrid nanomaterials synthesis, part-to-part assembly, and biosensor development. In this work, we show that fusion of the Car9 and Car15 carbon-binding peptides to the C-termini of the sfGFP and mCherry fluorescent proteins enables selective labeling of the ends or the sidewalls of single walled carbon nanotubes. By installing a gold-binding peptide or a single cysteine residue in carbon-binding variants of sfGFP, we further produce heterobifunctional solid-binding proteins that support the decoration of nanotubes sidewalls or termini with gold nanoparticles. The approach described here is generic and should prove useful for the controlled assembly of other hybrid materials.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Systemic Response to Microgravity: Utilizing GeneLab Datasets to Identify Molecular Targets for Future Hypotheses-Driven Spaceflight Studies

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF(beta)1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF(beta)1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales.

GeneLab↗
DOE OSTI2016

Improved Understanding of Microbial Iron and Sulfate Reduction Through a Combination of Bottom-up and Top-down Functional Proteomics Assays

Our overall goal was to improve the understanding of microbial iron and sulfate reduction by evaluating a diverse iron and sulfate reducing organisms utilizing a multi-omics approach combining “top-down” and “bottom-up” omics methodologies. We initiated one of the first combined comparative genomics, shotgun proteomics, RTqPCR, and heterologous expression studies in pursuit of our project objectives. Within the first year of this project, we created a new bioinformatics tool for ortholog identification (“SPOCS”). SPOCS is described in our publication, Curtis et al., 2013. Using this tool we were able to identify conserved orthologous groups across diverse iron and sulfate reducing microorganisms from Firmicutes, gamma-proteobacteria and delta-proteobacteria. For six iron and sulfate reducers we also performed shotgun proteomics (“bottom-up” proteomics including accurate mass and time (AMT) tag and iTRAQ approaches). Cultures include Gram (-) and Gram (+) microbes. Gram (-) were: Geobacter sulfureducens (grown on iron citrate and fumarate), Geobacter bemidjiensis (grown on iron citrate and fumarate), Shewanella oneidiensis (grown on iron citrate and fumarate) and Anaeromyxobacter dehalogenans (grown on iron citrate and fumarate). Although all cultures grew on insoluble iron, the iron precipitates interfered with protein extraction and analysis; which remains a major challenge for researchers in disparate study systems. Among the Gram (-) organisms studied, Anaeromyxobacter dehalogenans remains the most poorly characterized. Yet, it is arguably the most versatile organisms we studied. In this work we have used comparative proteomics to hypothesize which two of the dozens of predicted c-type cytochromes within Anaeromyxobacter dehalogenans may be directly involved in soluble iron reduction. Unfortunately, heterologous expression of these Anaeromyxobacter dehalogenans ctype cytochromes led to poor protein production and/or formation of inclusion bodies, even when we co-expressed several genes known to be important for assembly of cytochrome holoenzymes. We confirmed the proteomics trends at the RNA level by designing specific primer sets for hypothesized iron reductases in Anaeromyxobacter dehalogenans, and performed Reverse Transcription-qPCR. AD_0127 was 20 fold upregulated only on iron citrate conditions. AD_0127 is described as a hypothetical protein, but Pfam predicts it to be C554 type cytochrome having a possible role in nitrification (Wang et al., in preparation).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

Evolution and folding of repeat proteins

Repeat proteins are made with tandem copies of similar amino acid stretches that fold into elongated architectures. These proteins constitute excellent model systems to investigate how evolution relates to structure, folding, and function. Here, we propose a scheme to map evolutionary information at the sequence level to a coarse-grained model for repeat-protein folding and use it to investigate the folding of thousands of repeat proteins. We model the energetics by a combination of an inverse Potts-model scheme with an explicit mechanistic model of duplications and deletions of repeats to calculate the evolutionary parameters of the system at the single-residue level. These parameters are used to inform an Ising-like model that allows for the generation of folding curves, apparent domain emergence, and occupation of intermediate states that are highly compatible with experimental data in specific case studies. We analyzed the folding of thousands of natural Ankyrin repeat proteins and found that a multiplicity of folding mechanisms are possible. Fully cooperative all-or-none transitions are obtained for arrays with enough sequence-similar elements and strong interactions between them, while noncooperative element-by-element intermittent folding arose if the elements are dissimilar and the interactions between them are energetically weak. Additionally, we characterized nucleation-propagation and multidomain folding mechanisms. We show that the global stability and cooperativity of the repeating arrays can be predicted from simple sequence scores.

Ezequiel A. Galpern↗
DOE OSTI2016

Crystal structure and DNA binding activity of a PadR family transcription regulator from hypervirulent Clostridium difficile R20291

Background: Clostridium difficile is a spore-forming obligate anaerobe that can remain viable for extended periods, even in the presence of antibiotics, which contributes to the persistence of this bacterium as a human pathogen during host-to-host transmission and in hospital environments. We examined the structure and function of a gene product with the locus tag CDR20291_0991 (cdPadR1) as part of our broader goal aimed at elucidating transcription regulatory mechanisms involved in virulence and antibiotic resistance of the recently emergent hypervirulent C. difficile strain R20291. cdPadR1 is genomically positioned near genes that are involved in stress response and virulence. In addition, it was previously reported that cdPadR1 and a homologue from the historical C. difficile strain 630 (CD630_1154) were differentially expressed when exposed to stressors, including antibiotics. Results: The crystal structure of cdPadR1 was determined to 1.9 Å resolution, which revealed that it belongs to the PadR-s2 subfamily of PadR transcriptional regulators. cdPadR1 binds its own promoter and other promoter regions from within the C. difficile R20291 genome. DNA binding experiments demonstrated that cdPadR1 binds a region comprised of inverted repeats and an AT-rich core with the predicted specific binding motif, GTACTAT(N2)ATTATA(N) AGTA, within its own promoter that is also present in 200 other regions in the C. difficile R20291 genome. Mutation of the highly conserved W in α4 of the effector binding/oligomerization domain, which is predicted to be involved in multi-drug recognition and dimerization in other PadR-s2 proteins, resulted in alterations of cdPadR1 binding to the predicted binding motif, potentially due to loss of higher order oligomerization. Conclusions: Our results indicate that cdPadR1 binds a region within its own promoter consisting of the binding motif GTACTAT(N2)ATTATA(N)AGTA and seems to associate non-specifically with longer DNA fragments in vitro, which may facilitate promoter and motif searching. This suggests that cdPadR1 acts as a transcriptional auto-regulator, binding specific sites within its own promoter, and is part of a broad gene regulatory network involved, in part, with environmental stress response, antibiotic resistance and virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗