Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Protein quality control”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Genome and time-of-day transcriptome of Wolffia australiana link morphological minimization with gene loss and less growth control

Rootless plants in the genus Wolffia are some of the fastest growing known plants on Earth. Wolffia have a reduced body plan, primarily multiplying through a budding type of asexual reproduction. Here, we generated draft reference genomes for Wolffia australiana (Benth.) Hartog & Plas, which has the smallest genome size in the genus at 357 Mb and has a reduced set of predicted protein-coding genes at about 15,000. Comparison between multiple high-quality draft genome sequences from W. australiana clones confirmed loss of several hundred genes that are highly conserved among flowering plants, including genes involved in root developmental and light signaling pathways. Wolffia has also lost most of the conserved nucleotide-binding leucine-rich repeat (NLR) genes that are known to be involved in innate immunity, as well as those involved in terpene biosynthesis, while having a significant overrepresentation of genes in the sphingolipid pathways that may signify an alternative defense system. Diurnal expression analysis revealed that only 13% of Wolffia genes are expressed in a time-of-day (TOD) fashion, which is less than the typical ~40% found in several model plants under the same condition. In contrast to the model plants Arabidopsis and rice, many of the pathways associated with multicellular and developmental processes are not under TOD control in W. australiana, where genes that cycle the conditions tested predominantly have carbon processing and chloroplast-related functions. The Wolffia genome and TOD expression data set thus provide insight into the interplay between a streamlined plant body plan and optimized growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

MEMOTE for standardized genome-scale metabolic model testing

Reconstructing metabolic reaction networks enables the development of testable hypotheses of an organism’s metabolism under different conditions. State-of-the-art genome-scale metabolic models (GEMs) can include thousands of metabolites and reactions that are assigned to subcellular locations. Gene–protein–reaction (GPR) rules and annotations using database information can add meta-information to GEMs. GEMs with metadata can be built using standard reconstruction protocols, and guidelines have been put in place for tracking provenance and enabling interoperability, but a standardized means of quality control for GEMs is lacking. Here we report a community effort to develop a test suite named MEMOTE (for metabolic model tests) to assess GEM quality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effect of different organic acid additives on the fermentation quality and bacterial community of paper mulberry (Broussonetia papyrifera) silage

To investigate the effects of different organic acid additives and their concentrations on the fermentation quality and bacterial community of paper mulberry silage, paper mulberry was left untreated (control) or was treated with ethylenediaminetetraacetic acid (EDTA), propionic acid (PA) or citric acid (CA), the amount of each additive was 2 g.kg −1 FM, 5 g.kg −1 FM and g.kg −1 FM. All groups were ensiled for 3, 7, 15, 30 and 60 days. Compared to the control, adding EDTA reduced protein breakdown, preserved more water-soluble carbohydrates of the silages (WSCs, 24.74 g.kg −1 DM), and high concentrations of EDTA inhibited the activity of undesirable microorganisms. Adding PA increased the abundance of Lactiplantibacillus and decreased the abundance of Enterococcus , and it caused a rapid decrease in the pH of the silage at an early stage (from 6.50 to 5.31) while altering the microbiota, and low concentrations of PA resulted in high LA (66.22 g.kg −1 DM) concentration and low PA (9.92 g.kg −1 DM) concentration at 60 days of ensiling. Different concentrations of additives altered the microbial community of paper mulberry to different degrees. High concentrations of PA and CA can increase the abundance of Lactiplantibacillus . High concentrations of CA resulted in a rapid decrease in silage pH at an early stage and higher WSC concentration. These results suggest that EDTA, PA and CA can be used as additives to improve the quality of paper mulberry silage.

Li, Mengxin↗
NASA NTRS1993

Protein crystal growth

Proteins account for 50% or more of the dry weight of most living systems and play a crucial role in virtually all biological processes. Since the specific functions of essentially all biological molecules are determined by their three-dimensional structures, it is obvious that a detailed understanding of the structural makeup of a protein is essential to any systematic research pertaining to it. At the present time, protein crystallography has no substitute, it is the only technique available for elucidating the atomic arrangements within complicated biological molecules. Most macromolecules are extremely difficult to crystallize, and many otherwise exciting and promising projects have terminated at the crystal growth stage. There is a pressing need to better understand protein crystal growth, and to develop new techniques that can be used to enhance the size and quality of protein crystals. There are several aspects of microgravity that might be exploited to enhance protein crystal growth. The major factor that might be expected to alter crystal growth processes in space is the elimination of density-driven convective flow. Another factor that can be readily controlled in the absence of gravity is the sedimentation of growing crystal in a gravitational field. Another potential advantage of microgravity for protein crystal growth is the option of doing containerless crystal growth. One can readily understand why the microgravity environment established by Earth-orbiting vehicles is perceived to offer unique opportunities for the protein crystallographer. The near term objectives of the Protein Crystal Growth in a Microgravity Environment (PCG/ME) project is to continue to improve the techniques, procedures, and hardware systems used to grow protein crystals in Earth orbit.

Bugg, Charles E.↗
NASA NTRS1971

Mechanisms and kinetics of cellulose fermentation for protein production

The development of a process (and ancillary processing and analytical techniques) to produce bacterial single-cell protein of good nutritional quality from waste cellulose is discussed. A fermentation pilot plant and laboratory were developed and have been in operation for about two years. Single-cell protein (SCP) can be produced from sugarcane bagasse--a typical agricultural cellulosic waste. The optimization and understanding of this process and its controlling variables are examined. Both batch and continuous fermentation runs have been made under controlled conditions in the 535 liter pilot plant vessel and in the laboratory 14-liter fermenters.

Dunlap, C. A.↗
DOE OSTI2021

Soil metabolome response to whole-ecosystem warming at the Spruce and Peatland Responses under Changing Environments experiment

In this study, a suite of complementary environmental geochemical analyses, including NMR and gas chromatography-mass spectrometry (GC-MS) analyses of central metabolites, Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) of secondary metabolites, and lipidomics, was used to investigate the influence of organic matter (OM) quality on the heterotrophic microbial mechanisms controlling peatland CO2, CH4, and CO2:CH4 porewater production ratios in response to climate warming. Our investigations leverage the Spruce and Peatland Responses under Changing Environments (SPRUCE) experiment, where air and peat warming were combined in a whole-ecosystem warming treatment. We hypothesized that warming would enhance the production of plant-derived metabolites, resulting in increased labile OM inputs to the surface peat, thereby enhancing microbial activity and greenhouse gas production. Because shallow peat is most susceptible to enhanced warming, increases in labile OM inputs to the surface, in particular, are likely to result in significant changes to CO2 and CH4 dynamics and methanogenic pathways. In support of this hypothesis, significant correlations were observed between metabolites and temperature consistent with increased availability of labile substrates, which may stimulate more rapid turnover of microbial proteins. An increase in the abundance of methanogenic genes in response to the increase in the abundance of labile substrates was accompanied by a shift toward acetoclastic and methylotrophic methanogenesis. Our results suggest that as peatland vegetation trends toward increasing vascular plant cover with warming, we can expect a concomitant shift toward increasingly methanogenic conditions and amplified climate–peatland feedbacks.

Wilson, Rachel M.↗
DOE OSTI2022

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Inhibition of HSP70 and a Collagen-Specific Molecular Chaperone (HSP47) Expression in Rat Osteoblasts by Microgravity

Rat osteoblasts were cultured aboard a space shuttle for 4 or 5 days. Cells were exposed to 1alpha, 25 dihydroxyvitamin D(3) during the last 20 h and then solubilized by guanidine solution. The mRNA levels for molecular chaperones were analyzed by semi-quantitative RT-PCR. ELISA was used to quantify TGF-beta1 in the conditioned medium. The HSP70 mRNA levels in the flight cultures were almost completely suppressed, as compared to the ground (1 x g) controls. The inducible HSP70 is known as the major heat shock protein that prevents stress-induced apoptosis. The mean mRNA levels for the constitutive HSC73 in the flight cultures were reduced to 69%, approximately 60% of the ground controls. HSC73 is reported to prevent the pathological state that is induced by disruption of microtubule network. The mean HSP47 mRNA levels in the flight cultures were decreased to 50% and 19% of the ground controls on the 4th and 5th days. Concomitantly, the concentration of TGF-beta1 in the conditioned medium of the flight cultures was reduced to 37% and 19% of the ground controls on the 4th and 5th days. HSP47 is the collagen-specific molecular chaperone that controls collagen processing and quality and is regulated by TGF-beta1. Microgravity differentially modulated the expression of molecular chaperones in osteoblasts, which might be involved in induction and/or prevention of osteopenia in space.

Animals↗
NASA NTRS1989

Space manufacturing in an automated crystal growth facility

An account is given of a Space Station Freedom-based robotic laboratory system for crystal growth experiments; the robot must interface with both the experimental apparatus and such human input as may be required for control and display. The goal of the system is the simultaneous growth of several hundred protein crystals in microgravity. The robot possesses six degrees-of-freedom, allowing it to efficiently manipulate the cultured crystals as well as their respective growth cells; the crystals produced are expected to be of sufficiently high quality for complete structural determination on the basis of XRD.

Quinn, Alberta W.↗
NASA NTRS2000

Preparation and Analysis of RNA Crystals

The crystallization of RiboNucleic Acids (RNA) was studied from the standpoint of mechanisms of crystal growth in three tasks: (1) preparation of high-quality crystals of oligonuclotides for X-ray diffraction, (2) finding pathways to the growth of high-quality crystals for X-ray diffraction and (3) investigation of mechanisms of action of inertial acceleration on crystal growth. In these tasks: (1) RNA crystals were prepared and studied by X-ray diffraction; (2) a pathway to high-quality crystals was discovered and characterized; a combination of kinetic and equilibrium factors could be optimized as described below; and (3) an interplay between purity and gravity was found in a combination of space and ground experiments with nucleic acids and proteins. Most significantly, the rate of concentration of precipitant and RNA can be controlled by membrane-based methods of water removal or by diffusion of multivalent cations across an interface stabilized by a membrane. Oligonucleotide solutions are electrokinetically stabilized colloids, and crystals can form by the controlled addition of multivalent cations.

Todd, Paul↗
DOE OSTI2022

Effects of antibacterial peptide-producing Bacillus subtilis, gallic acid, and cellulase on fermentation quality and bacterial community of whole-plant corn silage

In the current study, we assessed the effects of antibacterial peptide-producing Bacillus subtilis (BS), gallic acid (GA) and cellulase (CL) on the fermentation quality and bacterial community of various varieties of whole-plant corn silage. Three different varieties of whole-plant corn (Yuqing386, Enxiai298, and Nonghe35) were treated with 0.02% BS (fresh material basis), 0.2% GA (fresh material basis) and 0.02% CL (fresh material basis), after which 45 days of anaerobic fermentation were conducted. With the exception of its low dry matter content, the results showed that Yuqing386’s crude protein, water-soluble carbohydrate, and lactic acid contents were significantly higher than those of the other two corn varieties. However, its acid detergent fiber and cellulose contents were significantly lower than those of the other two corn varieties. Among the three corn variety silages, Yuqing386 had the highest relative abundance of Lactobacillus at the genus level and the biggest relative abundance of Firmicutes at the phylum level. In addition, the three additives markedly enhanced the quantity of dry matter and crude protein as compared to the control group. The application of GA considerably decreased the level of neutral detergent fiber while significantly increasing the content of lactic acid and water-soluble carbohydrates. Even though all additives enhanced the structure of the bacterial community following silage, the GA group experienced the greatest enhancement. On a phylum and genus level, the GA group contains the highest relative abundance of Firmicutes and Lactobacillus , respectively. Overall, of the three corn varieties, Yuqing386 provides the best silage qualities. GA has the biggest impact among the additions employed in this experiment to enhance the nutritional preservation and fermentation quality of whole-plant corn silage.

Zhang, Zhiheng↗
NASA NTRS1987

Quality control of murine monoclonal antibodies using isoelectric focusing affinity immunoblot analysis

The quality control of murine hybridoma secretory products has been performed using two approaches for isoelectric focusing affinity immunoblot analysis: (1) a method in which antigen-coated nitrocellulose is placed on top of an acrylamide gel containing isoelectrically focused ascites to bind the antigen specific monoclonal antibody; and (2) a method in which focused ascite proteins were passively blotted onto nitrocellulose and specific monoclonal antibodies were detected with enzyme-conjugated antigen. Analysis by both methods of batches of ascites containing antihuman IgG antibodies that were produced by six hybridomas permitted effective monitoring of immunoreactive antibodies for pI microheterogeneity.

Hamilton, Robert G.↗
DOE OSTI2022

Cryo-electron Microscopy of Adeno-associated Virus

Adeno-associated virus (AAV) has a single-stranded DNA genome encapsidated in a small icosahedrally symmetric protein shell with 60 subunits. AAV is the leading delivery vector in emerging gene therapy treatments for inherited disorders, so its structure and molecular interactions with human hosts are of intense interest. A wide array of electron microscopic approaches have been used to visualize the virus and its complexes, depending on the scientific question, technology available, and amenability of the sample. Approaches range from subvolume tomographic analyses of complexes with large and flexible host proteins to detailed analysis of atomic interactions within the virus and with small ligands at resolutions as high as 1.6 Å. Analyses have led to the reclassification of glycan receptors as attachment factors, to structures with a new-found receptor protein, to identification of the epitopes of antibodies, and a new understanding of possible neutralization mechanisms. AAV is now well-enough characterized that it has also become a model system for EM methods development. Heralding a new era, cryo-EM is now also being deployed as an analytic tool in the process development and production quality control of high value pharmaceutical biologics, namely AAV vectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effect of High-Protein Diets on Integrated Myofibrillar Protein Synthesis before Anterior Cruciate Ligament Reconstruction: A Randomized Controlled Pilot Study

Increasing dietary protein intake during periods of muscle disuse may mitigate the resulting decline in muscle protein synthesis (MPS). The purpose of this randomized pilot study was to determine the effect of increased protein intake during periods of disuse before anterior cruciate ligament (ACL) reconstruction on myofibrillar protein synthesis (MyoPS), and proteolytic and myogenic gene expression. Six healthy, young males (30 ± 9 y) were randomized to consume a high-quality, optimal protein diet (OP; 1.9 g·kg−1·d−1) or adequate protein diet (AP; 1.2 g·kg−1·d−1) for two weeks before ACL reconstruction. Muscle biopsies collected during surgery were used to measure integrated MyoPS during the intervention (via daily deuterium oxide ingestion) and gene expression at the time of surgery. MyoPS tended to be higher, with a large effect size in OP compared to AP (0.71 ± 0.1 and 0.54 ± 0.1%·d−1; p = 0.076; g = 1.56). Markers of proteolysis and myogenesis were not different between groups (p > 0.05); however, participants with greater MyoPS exhibited lower levels of MuRF1 gene expression compared to those with lower MyoPS (r = −0.82, p = 0.047). The data from this pilot study reveal a potential stimulatory effect of increased daily protein intake on MyoPS during injury-mediated disuse conditions that warrants further investigation.

Howard, Emily E. (ORCID:0000000179791236)↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
DOE OSTI2022

TULIP: An RNA-seq-based Primary Tumor Type Prediction Tool Using Convolutional Neural Networks

Background: With cancer as one of the leading causes of death worldwide, accurate primary tumor type prediction is critical in identifying genetic factors that can inhibit or slow tumor progression. There have been efforts to categorize primary tumor types with gene expression data using machine learning, and more recently with deep learning, in the last several years. Methods In this paper, we developed four 1-dimensional (1D) Convolutional Neural Network (CNN) models to classify RNA-seq count data as one of 17 highly represented primary tumor types or 32 primary tumor types regardless of imbalanced representation. Additionally, we adapted the models to take as input either all Ensembl genes (60,483) or protein coding genes only (19,758). Unlike previous work, we avoided selection bias by not filtering genes based on expression values. RNA-seq count data expressed as FPKM-UQ of 9,025 and 10,940 samples from The Cancer Genome Atlas (TCGA) were downloaded from the Genomic Data Commons (GDC) corresponding to 17 and 32 primary tumor types respectively for training and validating the models. Results: All 4 1D-CNN models had an overall accuracy of 94.7% to 97.6% on the test dataset. Further evaluation indicates that the models with protein coding genes only as features performed with better accuracy compared to the models with all Ensembl genes for both 17 and 32 primary tumor types. For all models, the accuracy by primary tumor type was above 80% for most primary tumor types. Conclusions: We packaged all 4 models as a Python-based deep learning classification tool called TULIP (TUmor CLassIfication Predictor) for performing quality control on primary tumor samples and characterizing cancer samples of unknown tumor type. Further optimization of the models is needed to improve the accuracy of certain primary tumor types.

Jones, Sara↗
NASA NTRS1986

Utilization of non-conventional systems for conversion of biomass to food components: Recovery optimization and characterizations of algal proteins and lipids

Protein isolate obtained from green algae (Scenedesmus obliquus) cultivated under controlled conditions was characterized. Molecular weight determination of fractionated algal proteins using SDS-polyacrylamide gel electrophoresis revealed a wide spectrum of molecular weights ranging from 15,000 to 220,000. Isoelectric points of dissociated proteins were in the range of 3.95 to 6.20. Amino acid composition of protein isolate compared favorably with FAO standards. High content of essential amino acids leucine, valine, phenylalanine and lysine makes algal protein isolate a high quality component of closed environment life support system (CELSS) diets. To optimize the removal of algal lipids and pigments supercritical carbon dioxide extraction (with and without ethanol as a co-solvent) was used. Addition of ethanol to supercritical CO2 resulted in more efficient removal of algal lipids and produced protein isolate with a good yield and protein recovery. The protein isolate extracted by the above mixture had an improved water solubility.

Karel, M.↗