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At least 217 records · Page 12

Identification of novel small molecule inhibitors of twin arginine translocation (Tat) pathway and their effect on the control of Campylobacter jejuni in chickens

Introduction Control ofCampylobacterfrom farm to fork is challenging due to the frequent emergence of antimicrobial-resistant isolates. Furthermore, poultry production systems are known reservoirs ofCampylobacter. The twin-arginine translocation (Tat) pathway is a crucial bacterial secretion system that allowsCampylobacterto colonize the host intestinal tract by using formate as the main source of energy. However, Tat pathway is also a major contributing factor for resistance to copper sulfate (CuSO 4 ). Methods Since mammals and chickens do not have proteins or receptors that are homologous to bacterial Tat proteins, identification of small molecule (SM) inhibitors targeting the Tat system would allow the development of safe and effective control methods to mitigateCampylobacterin infected or colonized hosts in both pre-harvest and post-harvest. In this study, we screened 11 commercial libraries (n = 50,917 SM) for increased susceptibility to CuSO 4 (1 mM) inC. jejuni81–176, a human isolate which is widely studied. Results Furthermore, we evaluated 177 SM hits (2.5 μg/mL and above) that increased the susceptibility to CuSO 4 for the inhibition of formate dehydrogenase (Fdh) activity, a Tat-dependent substrate. Eight Tat-dependent inhibitors (T1–T8) were selected for further studies. These selected eight Tat inhibitors cleared all testedCampylobacterstrains (n = 12) at >10 ng/mL in the presence of 0.5 mM CuSO 4 in vitro. These selected SMs were non-toxic to colon epithelial (Caco-2) cells when treated with 50 μg/mL for 24 h and completely cleared intracellularC. jejunicells when treated with 0.63 μg/mL of SM for 24 h in the presence of 0.5 mM of CuSO 4 . Furthermore, 3 and 5-week-old chicks treated with SM candidates for 5 days had significantly decreased cecal colonization (up to 1.2 log;p < 0.01) with minimal disruption of microbiota.In silicoanalyses predicted that T7 has better drug-like properties than T2 inhibitor and might target a key amino acid residue (glutamine 165), which is located in the hydrophobic core of TatC protein. Discussion Thus, we have identified novel SM inhibitors of the Tat pathway, which represent a potential strategy to controlC. jejunispread on farms.

Microbiology↗

Overview of office of space transportation systems future planning

The Space Transportation Systems' key milestones as well as the future planning of the Office of Space Transportation Systems are summarized. A brief description and identification of candidate new starts with target development initiation and first flight dates are included.

Savage, M.↗

System identification for Space Station Freedom using observer/Kalman filter Markov parameters

The Modal Identification Experiment (MIE) is a proposed experiment to define the dynamic characteristics of Space Station Freedom. Previous studies emphasized free-decay modal identification. The feasibility of using a forced response method (Observer/Kalman Filter Identification (OKID)) is addressed. The interest in using OKID is to determine the input mode shape matrix which can be used for controller design or control-structure interaction analysis, and investigate if forced response methods may aid in separating closely spaced modes. A model of the SC-7 configuration of Space Station Freedom was excited using simulated control system thrusters to obtain acceleration output. It is shown that an 'optimum' number of outputs exists for OKID. To recover global mode shapes, a modified method called Global-Local OKID was developed. This study shows that using data from a long forced response followed by free-decay leads to the 'best' modal identification. Twelve out of the thirteen target modes were identified for such an output.

Papadopoulos, Michael↗

Applicability of Electrical and Electroanalytical Techniques to Detect Water and Characterize the Geochemistry of Undisturbed Planetary Soils

The search for life is a primary goal of NASA s planetary exploration program. The search is, of necessity, tiered in both the detection approach (looking for evidence of microbial fossils or the presence of water in the geological history of a planetary body and/or looking for evidence of water, energy sources, precursors to life, signatures of life and/or life itself in the present day planetary environment) and in the survey method (scale, range, specificity) employed. Terrestrial investigations suggests that life as we know it requires water. Thus, the search for extant microbial life and habitats requires identifying water-bearing soils. Determining Reduction-Oxidation (REDOX) couples present in water, once it is found, provides information on soil geochemistry and identifies potential chemical energy sources for life. Mars offers a near-term target for conducting this search. The identification of gully formation [1], layered deposits [2] and elemental ratios of bromine and chlorine [3] present indirect evidence that water was abundant locally in the Martian past. Additionally, Viking images of polar ice and frost formation on the surface of Mars demonstrate that water can exist in at least some near-surface regions of present-day Mars. Atmospheric pressure data further suggest that liquid water may be stable for short periods of time in the mid-latitudes of the Martian surface. [4] Measurements of the global distribution of hydrogen in the Martian regolith offer tantalizing indirect evidence that water may at least exist in near-surface soils. [5] Evidently, any water to be found is likely to exist as soil mixtures at levels ranging between approx.0.5% and approx.5 %.

Seshadri, S.↗

Satellite-To-Satellite Imaging in Support of LEO Optical Navigation, Using the ASTERIA Cubesat

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was a 6-unit CubeSat technology demonstration mission that was built at NASA’s Jet Propulsion Laboratory (JPL) and deployed from the International Space Station (ISS) on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations alongside science until end of mission in December 2019. At the end of its lifetime it was being used as a demonstration platform for several experiments, including low earth orbit (LEO) optical navigation operations. With its visible light astrometric camera and stable attitude control system, the ASTERIA spacecraft showed itself to be a capable platform for the imaging of geosynchronous satellites from LEO. This paper will describe the imagery attained in flight and also the image processing algorithms that were developed to render that imagery into navigation quality data. These algorithms dealt with hot pixel filtering, noise modeling, attitude registration, star signal rejection and satellite signal identification. Brightness prediction algorithms used for target selection will also be discussed.

Fesq, Lorraine↗

Shape Memory Alloy Material Maturation (SMA)

The Shape Memory Alloy (SMA) project will evaluate, process, and refine 3 SMA materials that have the potential to provide the properties needed to enable various technologies for human exploration missions on the Moon and Mars. The work will focus on the development and identification of a new SMA alloy targeted at enabling compliant rover tires capable of the extreme demands (high loads, faster drive speeds, extreme cold temperatures and exceedingly long mission durations). The necessary work will include the development of key material testing capabilities that will enable material properties development from 40K – 400K for all properties needed to qualify space flight hardware (Tensile, Fatigue/Durability, etc.). The SMA wire properties will be input into a database and model, ultimately to disseminate material property design data (for 1 alloy only) as parameters for finite element modeling of a tire structure.

Andrea Marchica↗

Metabolite, Protein, and Lipid Extraction (MPLEx): a method that simultaneously inactivates Middle East respiratory syndrome coronavirus and allows analysis of multiple host cell components following infection

Mass spectrometry (MS)-based, integrated proteomics, metabolomics, and lipidomics (collectively, multi-omics) studies provide a very detailed snap shot of virus-induced changes to the host following infection and can lead to the identification of novel prophylactic and therapeutic targets for preventing or lessening disease severity. Multi-omics studies with Middle East respiratory syndrome coronavirus (MERS-CoV) are challenging as the requirements of Biosafety Level 3 containment limit the numbers of samples that can be safely managed. To address these issues, the multi-omics sample preparation technique MPLEx (metabolite, protein, and lipid extraction) was developed to partition a single sample into three distinct parts (metabolites, proteins and lipids) for multi-omics analysis, while simultaneously inactivating MERS-CoV by solubilizing and disrupting the viral envelope and denaturing viral proteins. Here we describe the MPLEx protocol, highlight the step of inactivation, and describe the details of downstream processing, instrumental analysis of studies with Middle East respiratory syndrome coronavirus (MERS-CoV) are challenging as the requirements of Biosafety Level 3 containment limit the numbers of samples that can be safely managed. To address these issues, the multi-omics sample preparation technique MPLEx (metabolite, protein, and lipid extraction) was developed to partition a single sample into three distinct parts (metabolites, proteins and lipids) for multi-omics analysis, while simultaneously inactivating MERS-CoV by solubilizing and disrupting the viral envelope and denaturing viral proteins. Here we describe the MPLEx protocol, highlight the step of inactivation, and describe the details of downstream processing, instrumental analysis of the three separate analytes and their subsequent informatics pipelines.

Nicora, Carrie D.↗

Enumeration and Fluorescence In Situ Hybridization of Microbial Bioburden on Cleanroom Surfaces

Introduction: Microorganisms are everywhere on Earth, even in the cleanest of places. Spacecraft assembly cleanrooms can harbor low levels of living and dead microbial cells (e.g., [1,2]), and cleanroom bioburden can also include organic molecules from industrial sources and in situ biomass. Life detection missions require careful attention to avoid contaminants that can be easily convoluted with analytical targets. We are evaluating epifluorescent microscopy and fluorescence in situ hybridization (FISH) as methods to complement organic contamination detection techniques. Epifluorescent cell counting offers an accurate and cost-effective way to quantify low levels of surface biomass. FISH could allow for the identification of residual organisms, and can be targeted to detect active populations of specific organisms such as bacteria known to resist cleaning procedures. This effort is part of a larger study that is concentrated on characterizing the surface and airborne molecular organic contamination background in Johnson Space Center (JSC) Astromaterials curation laboratories and Goddard Space Flight Center (GSFC) spacecraft assembly rooms, and understanding contaminants in the context of cleaning procedures and residual bioburden. Methods: Samples were collected by swabbing surfaces in ISO 5 and ISO 7 equivalent cleanrooms at JSC. Swabs for FISH were fixed in 4% paraformaldehyde (PFA) for 3 hours and then stored in 1:1 ethanol:PBS, while swabs for cell counting were stored in 4% PFA until analysis to avoid any cell loss during centrifugation that could impact quantification of very low biomass samples. Cell counting was performed with SYBR Gold as in [3], but adapted for very low biomass. FISH was performed as in [4], using DAPI as a counterstain for all DNA-containing cells. Negative controls included wells with no probe applied, to test for natural fluorescence, as well as the nonsense probe NONEUB (reverse complement of EUB338) to evaluate non-specific probe binding. Results and Discussion: Cleanroom surfaces had 102-103 cells cm-2. The extremely low biomass of these samples was challenging for enumeration, and required careful and routine use of “field” and laboratory blanks. FISH was performed with the general archaeal and bacterial probes ARCH915 and EUB338 (EUBMIX, [4]), probe GAMBET ([4]), and PSE227, which targets the genus Pseudomonas [5]). The latter two probes were selected because Pseudomonas spp. and other Gammaproteobacteria have not been isolated from cleanroom surfaces but do appear frequently in rRNA gene libraries from these surfaces. While some active bacteria were identified (Fig. 1c), most cells detectable by DAPI did not have a strong or any fluorescent signal (e.g., Fig. 1d), indicating that the vast majority of cells are dead or inactive. This suggests that cleaning protocols are effective at inactivating microbial contaminants, but that dead or inactive cells can remain on surfaces. Cells were often clumped in a weakly autofluorescent matrix, possibly biofilm material (Fig. 1c,d). We also observed other particulate material that was collected by the swabs, including apparent textile fibers (Fig. 1b). Our results are consistent with other studies that show that the bioburden present in clean rooms includes active, dormant, and dead cells. We will discuss how FISH and epifluorescent cell counting could be applied in planetary protection protocols, including the advantages and disadvantages of FISH and cell counting for routine use, as well as different possible applications for more specialized FISH procedures. References: [1] Moissl-Eichinger et al. (2015) Sci Rep, 5, 9156 [2] Hendrickson et al. (2021) Microbiome, 9, 238 [3] Jones et al. (2017) Appl Environ Microbiol, 83, e00909-17 [4] Jones et al. (2015) Appl Environ Microbiol, 81, 1242-1250. [5] Watt et al. (2006) Environ Microbiol, 8, 871-884

C J Huff↗

Efficient species identification for Pacific salmon genetic monitoring programs

Abstract Genetic monitoring of Pacific salmon in the Columbia River basin provides crucial information to fisheries managers that is otherwise challenging to obtain using traditional methods. Monitoring programs such as genetic stock identification (GSI) and parentage‐based tagging (PBT) involve genotyping tens of thousands of individuals annually. Although rare, these large sample collections inevitably include misidentified species, which exhibit low genotyping success on species‐specific Genotyping‐in‐Thousands by sequencing (GT‐seq) panels. For laboratories involved in large‐scale genotyping efforts, diagnosing non‐target species and reassigning them to the appropriate monitoring program can be costly and time‐consuming. To address this problem, we identified 19 primer pairs that exhibit consistent cross‐species amplification among salmonids and contain 51 species informative variants. These genetic markers reliably discriminate among 11 salmonid species and two subspecies of Cutthroat Trout and have been included in species‐specific GT‐seq panels for Chinook Salmon, Coho Salmon, Sockeye Salmon, and Rainbow Trout commonly used for Pacific salmon genetic monitoring. The majority of species‐informative amplicons (16) were newly identified from the four existing GT‐seq panels, thus demonstrating a low‐cost approach to species identification when using targeted sequencing methods. A species‐calling script was developed that is tailored for routine GT‐seq genotyping pipelines and automates the identification of non‐target species. Following extensive testing with empirical and simulated data, we demonstrated that the genetic markers and accompanying script accurately identified species and are robust to missing genotypic data and low‐frequency, shared polymorphisms among species. Finally, we used these tools to identify Coho Salmon incidentally caught in the Columbia River Chinook Salmon sport fishery and used PBT to determine their hatchery of origin. These molecular and computing resources provide a valuable tool for Pacific salmon conservation in the Columbia River basin and demonstrate a cost‐effective approach to species identification for genetic monitoring programs.

Robinson, Zachary L.↗

Interdisciplinary applications and interpretations of ERTS data within the Susquehanna River Basin; resources inventory, land use and pollution

The author has identified the following significant results. Identification and mapping of three major kinds of coal refuse targets based on spectral signatures in channels four through seven of the ERTS-1 MSS were conducted. Correlation of the placement of the coal refuse targets with an existing map of their location was accomplished. Digital processing of ERTS-1 data permitted identification of stripped areas including ones that are not discernible by visual analysis of ERTS imagery. Combined visual and digital techniques of analyzing ERTS-1 data for geologic formations have been tried on selected areas of Pennsylvania. Mapping of two major agriculture counties to show land forms, drainage patterns, water, and urban areas were made using positive transparencies of MSS data. Two frames of the same central Pennsylvania area were brought into registration by translation and then merged even though the frames were obtained 71 days apart.

Mcmurtry, G. J.↗

Small-molecule modulation of β-arrestins

β-Arrestins are multifunctional regulators of G-protein-coupled receptor (GPCR) signalling and orchestrate diverse downstream signalling events and physiological responses across the GPCR superfamily. Although GPCR pharmacology has advanced to target orthosteric and allosteric sites, as well as G proteins and GPCR kinases, direct chemical tools to modulate β-arrestin activities have remained conspicuously absent. Here we report the identification of small-molecule inhibitors that selectively target β-arrestins and delineate their mechanism of action through integrated pharmacological, biochemical, biophysical and structural analyses. These inhibitors disrupt β-arrestin engagement with agonist-activated GPCRs, impairing desensitization, internalization and β-arrestin-dependent physiological functions while sparing G protein–receptor coupling. Cryo-electron microscopy, molecular dynamics simulations and structure-guided mutagenesis reveal that one modulator, Cmpd-5, engages a pocket within the central crest of β-arrestin1 formed by the middle, C and lariat loops, a critical receptor-binding interface, stabilizing a distinct conformation that is incompatible with full β-arrestin–receptor engagement. Together, these findings establish a mechanistic framework for β-arrestin modulation, reveal a novel allosteric site for structure-based drug design, and open new avenues for transducer-targeted, pathway-specific GPCR therapeutic agents.

Kahsai, Alem W. [Duke University, Durham, NC (Unit↗

Wideband Interferometric Sensing and Imaging Polarimetry

Wideband Interferometric Sensing and Imaging Polarimetry (WISIP) has become an important, indispensible tool in wide area military surveillance and global environmental monitoring of the terrestrial and planetary covers. It enables dynamic, real time optimal feature extraction of significant characteristics of desirable targets and/or target sections with simultaneous suppression of undesirable background clutter and propagation path speckle at hitherto unknown clarity and never before achieved quality. WISIP may be adopted to the detection, recognition, and identification (DRI) of any stationary, moving or vibrating targets or distributed scatterer segments versus arbitrary stationary, dynamical changing and/or moving geo-physical/ecological environments, provided the instantaneous 2x2 phasor and 4x4 power density matrices for forward propagation/backward scattering, respectively, can be measured with sufficient accuracy. For example, the DRI of stealthy, dynamically moving inhomogeneous volumetric scatter environments such as precipitation scatter, the ocean/sea/lake surface boundary layers, the littoral coastal surf zones, pack ice and snow or vegetative canopies, dry sands and soils, etc. can now be successfully realized. A comprehensive overview is presented on how these modern high resolution/precision, complete polarimetric co-registered signature sensing and imaging techniques, complemented by full integration of novel navigational electronic tools, such as DGPS, will advance electromagnetic vector wave sensing and imaging towards the limits of physical realization. Various examples utilizing the most recent image data take sets of airborne, space shuttle, and satellite imaging systems demonstrate the utility of WISIP.

Verdi, James Salvatore↗

RIViT-seq enables systematic identification of regulons of transcriptional machineries

Abstract Transcriptional regulation is a critical process to ensure expression of genes necessary for growth and survival in diverse environments. Transcription is mediated by multiple transcription factors including activators, repressors and sigma factors. Accurate computational prediction of the regulon of target genes for transcription factors is difficult and experimental identification is laborious and not scalable. Here, we demonstrate regulon identification by in vitro transcription-sequencing (RIViT-seq) that enables systematic identification of regulons of transcription factors by combining an in vitro transcription assay and RNA-sequencing. Using this technology, target genes of 11 sigma factors were identified in Streptomyces coelicolor A3(2). The RIViT-seq data expands the transcriptional regulatory network in this bacterium, discovering regulatory cascades and crosstalk between sigma factors. Implementation of RIViT-seq with other transcription factors and in other organisms will improve our understanding of transcriptional regulatory networks across biology.

59 BASIC BIOLOGICAL SCIENCES↗

Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems

We consider a high-dimensional nonlinear computational model of a dynamical system, parameterized by a vector-valued control parameter, in the presence of uncertainties represented by an uncontrolled parameter modeled by a vector-valued random variable, and possibly with stochastic excitation. The objective is to construct a statistical surrogate model where the input is any deterministic value of the control parameter, and the output is a vector-valued observation of the computational model, which is a random vector whose probability measure is updated using a target dataset. To construct this statistical surrogate model, the stochastic response of the computational model must be built, which is a vector-valued time-discretized stochastic process in high dimension, depending on the control parameter. It is assumed that the computational cost of a single evaluation of the deterministic model is high. For the probabilistic updating, we consider a subset of the components of the observation of the computational model, defined as the “identification observation” of the computational model, for which a small target dataset is available. Therefore, the target dataset is associated with partial observability, corresponding to an incomplete data case. Given a prior probability model of the random control and uncontrolled parameters, a training dataset is constructed, consisting of realizations of the random triplet composed of the stochastic response, the random identification observation, and the random control parameter. Since the computational cost of a single evaluation of the deterministic model is assumed to be large, the training dataset is also of small size. The main challenges in this problem are the high dimensionality, partial observability leading to incomplete data in the target dataset for the identification observation of the computational model (which is not sufficient to identify the computational stochastic responses), and the availability of a small training dataset. To address these challenges, we propose a methodology based on statistical methods for constructing necessary reduced representations, direct probabilistic learning under constraints using probabilistic learning on manifolds (PLoM) constrained by the target dataset, and the use of a weak formulation of the Fourier transform of probability measures. Statistical conditioning is also employed to explore the learned dataset. The constructed predictive statistical surrogate model can be implemented in the context of online computation. Here, we apply this approach to a problem of nonlinear stochastic dynamics in high dimensions within the framework of deformable solids mechanics.

Engineering↗

Signature evaluation of natural targets using high spectral resolution techniques

The concept of 'spectral signature' identification has been applied to LANDSAT and other broad-band multi-spectral scanner data to classify various materials on the earth's surface. A large amount of the spectral information available is invisible, however, to the broad-band sensors. Although the natural targets of interest in remote sensing do not exhibit fine line features such as those associated with gaseous media, there is significant information to be extracted from smoothly varying spectral reflection functions of most natural targets. Subtle variations observed recently in the high resolution 'spectral signatures' of vegetation targets, in particular, promise to open new avenues of application using higher spectral and radiometric resolution techniques. This research was accomplished using a 500-band spectroradiometer system specially adapted to rapid airborne operations

Collins, W.↗

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization

Photonic surfaces designed with specific optical characteristics are becoming increasingly crucial for novel energy harvesting and storage systems. The design of these surfaces can be achieved by texturing materials using lasers. The optimal adjustment of laser fabrication parameters to achieve target surface optical properties is an open challenge. Thus, we develop a surrogate-based optimization approach. Our framework employs the Random Forest algorithm to model the forward relationship between the laser fabrication parameters and the resulting optical characteristics. During the optimization process, we use a greedy, prediction-based exploration strategy that iteratively selects batches of laser parameters to be used in experimentation by minimizing the predicted discrepancy between the surrogate model’s outputs and the user-defined target optical characteristics. This strategy allows for efficient identification of optimal fabrication parameters without the need to model the error landscape directly. We demonstrate the efficiency and effectiveness of our approach on two synthetic benchmarks and two specific experimental applications of photonic surface inverse design targets. By calculating the average performance of our algorithm compared to other state of the art optimization methods, we show that our algorithm performs, on average, twice as well across all benchmarks. Additionally, a warm starting inverse design technique for changed target optical characteristics enhances the performance of the introduced approach.

97 MATHEMATICS AND COMPUTING↗

A protein phosphatase 1 specific phos phatase ta rgeting p eptide (PhosTAP) to identify the PP1 phosphatome

Phosphoprotein phosphatases (PPPs) are the key serine/threonine phosphatases that regulate all essential signaling cascades. In particular, Protein Phosphatase 1 (PP1) dephosphorylates ~80% of all ser/thr phosphorylation sites. Here, we developed a phosphatase targeting peptide (PhosTAP) that binds all PP1 isoforms and does so with a stronger affinity than any other known PP1 regulator. This PhosTAP can be used as a PP1 recruitment tool for Phosphorylation Targeting Chimera (PhosTAC)-type recruitment in in vitro and cellular experiments, as well as in phosphoproteomics experiments to identify PP1-specific substrates and phosphosites. The latter is especially important to further our understanding of cellular signaling, as the identification of substrates and especially phosphosites that are targeted by specific phosphatases lags behind that of their kinase counterparts. Using PhosTAP-based proteomics, we show that, counter to our current understanding, many PP1 regulators are also substrates, that the number of residues between regulator PP1-binding and phosphosites vary significantly, and that PP1 counteracts the activities of mitotic kinases. Finally, we also found that Haspin kinase is a direct substrate of PP1 and that its PP1-dependent dephosphorylation modulates its activity during anaphase. Together, we show that PP1-specific PhosTAPs are a powerful tool for +studying PP1 activity in vitro and in cells.

Science & Technology - Other Topics↗

Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

laser hair removal↗