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At least 73 records · Page 4

Integrated lipidomic and proteomic profiling reveals metabolic network disruption by SARS-CoV-2 variants

The rapid evolution of SARS-CoV-2 has produced myriad viral strains with increasing transmissibility and capacity for immune evasion. While effective vaccination campaigns have reduced the fatalities associated with SARS-CoV-2, infections continue, and a detailed understanding of how this virus manipulates host biochemical pathways remains elusive. We asked both whether the patterns of host lipid rewiring remained consistent across variants and whether the changes in the abundance of lipid classes are related to changes in the expression of the enzymes involved in their biosynthesis. We compared global nontargeted lipidomics on A549-ACE2 cells infected with the delta variant (B.1.617.2), or the omicron (B.1.1.529) variant to our previous results of global nontargeted lipidomics on A549-ACE2 cells infected with the original WA1 strain and further performed quantitative proteomics to assess changes in the host proteome. We found that metabolic rewiring, both on the lipid and the enzymatic level, is remarkably consistent across all three variants. We further mapped changes in the expression of host metabolic enzymes, linking enzyme expression to alterations in the abundance of specific lipids during infection. This analysis identified key proteins related to virus-mediated changes in lipid abundance, including fatty acid synthase (FASN), lysosomal acid lipase (LIPA), and ORMDL, a regulator of sphingolipid biosynthesis. These integrated lipidomic and proteomic experiments shed light on the importance of the complex network of host metabolism networks that support SARS-CoV-2 infection and suggest that lipid metabolism may be a promising avenue for uncovering conserved therapeutic targets.

SARS-CoV-2↗

An ascomycete H4 variant with an unknown function

Histone variants leading to altered nucleosome structure, dynamics and DNA accessibility occur frequently, albeit rarely for H4. We carried out a comprehensive in silico scrutiny of fungal genomes, which revealed the presence of a novel H4 variant (H4E) in the ascomycetes, throughout the Pezizomycotina, in basal species of the Taphrinomycotina and also in the Glomeromycota. The coding cognate genes show a specific intron/exon organization, different from H4 canonical genes. H4Es diverge from canonical H4s mainly in the N- and C-terminal extensions, showing marked differences in the distribution and number of Lys and Arg residues, which may result in novel post-translational modifications. In Aspergillus nidulans (Pezizomycotina, Eurotiomycetes) the H4E variant protein level is low in mycelia. However, the encoding gene is well expressed at 37°C under nitrogen starvation. H4E localizes to the nucleus and interacts with H3, but its absence or overexpression does not result in any detectable phenotype. Deletion of only one of the of the two canonical H4 genes results in a strikingly impaired growth phenotype, which indicates that H4E cannot replace this canonical histone. Thus, an H4 variant is present throughout a whole subphylum of the ascomycetes, but with hitherto no experimentally detectable function.

59 BASIC BIOLOGICAL SCIENCES↗

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

60 APPLIED LIFE SCIENCES↗

Engineering highly stable variants of Corynactis californica green fluorescent proteins

Fluorescent proteins (FPs) are versatile biomarkers that facilitate effective detection and tracking of macromolecules of interest in real time. Engineered FPs such as superfolder green fluorescent protein (sfGFP) and superfolder Cherry (sfCherry) have exceptional refolding capability capable of delivering fluorescent readout in harsh environments where most proteins lose their native functions. Our recent work on the development of a split FP from a species of strawberry anemone, Corynactis californica, delivered pairs of fragments with up to threefold faster complementation than split GFP. We present the biophysical, biochemical, and structural characteristics of five full-length variants derived from these split C. californica GFP (ccGFP). These ccGFP variants are more tolerant under chemical denaturation with up to 8 kcal/mol lower unfolding free energy than that of the sfGFP. It is likely that some of these ccGFP variants could be suitable as biomarkers under more adverse environments where sfGFP fails to survive. A structural analysis suggests explanations of the variations in stabilities among the ccGFP variants.

59 BASIC BIOLOGICAL SCIENCES↗

Solidification texture, variant selection, and phase fraction in a spot-melt electron-beam powder bed fusion processed Ti-6Al-4V

The effect of a spot melt strategy on the solidification texture, variant selection, phase fraction, and their variations along the build height was investigated in comparison to a conventional linear melt strategy. Ti-6Al-4V alloy samples were manufactured by an electron-beam powder bed fusion process using two different melt strategies and characterized using high-energy synchrotron x-ray diffraction. The linear and spot melt cases resulted in β<100> cube and fiber textures, respectively, with the cube/fiber axis nearly parallel to the build direction. The α phase exhibited Burgers orientation relationship (BOR) with the parent β phase for both melt strategies. Although all of the key texture components and the BOR between the α and β phases were consistently observed in both cases along the build height, there were several measurable differences between the two. At the top of the build height, the β<100> build texture intensity was stronger in the linear case. However, the texture intensity in the linear case decreased gradually from the top to near the substrate, whereas the spot melt case did not show this trend. Moreover, the BOR was examined along the build height and the results showed that there is a distinct variant selection in the spot melt case, unlike the linear case. Specifically, the planar variants sharing ($\bar101$) β || (0002) α with [$\bar2\bar2\bar2$]β and [$2\bar22$]β were the most prominent in the spot melt, but no preference was identified in the directional variants. The β phase fraction was slightly lower in the spot melt case compared to the linear case. In both the cases, the β phase fraction decreased moving towards the substrate but remained significantly higher than that of the powder feedstock. Overall, the novel spot melt strategy produced a more homogeneous microstructure in terms of both the phase fraction and texture across the build height.

36 MATERIALS SCIENCE↗

Stabilization of glucose-6-phosphate dehydrogenase oligomers enhances catalytic activity and stability of clinical variants

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a genetic trait that can cause hemolytic anemia. To date, over 150 nonsynonymous mutations have been identified in G6PD, with pathogenic mutations clustering near the dimer and/or tetramer interface and the allosteric NADP + -binding site. Recently, our lab identified a small molecule that activates G6PD variants by stabilizing the allosteric NADP + and dimer complex, suggesting therapeutics that target these regions may improve structural defects. Here, we elucidated the connection between allosteric NADP + binding, oligomerization, and pathogenicity to determine whether oligomer stabilization can be used as a therapeutic strategy for G6PD deficiency (G6PD def ). We first solved the crystal structure for G6PD K403Q , a mutant that mimics the physiological acetylation of wild-type G6PD in erythrocytes and demonstrated that loss of allosteric NADP + binding induces conformational changes in the dimer. These structural changes prevent tetramerization, are unique to Class I variants (the most severe form of G6PD def ), and cause the deactivation and destabilization of G6PD. We also introduced nonnative cysteines at the oligomer interfaces and found that the tetramer complex is more catalytically active and stable than the dimer. Furthermore, stabilizing the dimer and tetramer improved protein stability in clinical variants, regardless of clinical classification, with tetramerization also improving the activity of G6PD K403Q and Class I variants. These findings were validated using enzyme activity and thermostability assays, analytical size-exclusion chromatography (SEC), and SEC coupled with small-angle X-ray scattering (SEC-SAXS). Taken together, our findings suggest a potential therapeutic strategy for G6PD def and provide a foundation for future drug discovery efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Orientation-selected micro-pillar compression of additively manufactured 316L stainless steels: Comparison of as-manufactured, annealed, and proton-irradiated variants

In this work, irradiation response and deformation mechanisms of additively manufactured (AM) 316L stainless steel were studied by atomic scale characterization and micro-pillar compression. The AM 316L stainless steels were fabricated by direct energy deposition, a laser-based additive manufacturing process. Irradiation with 2 MeV protons at 360°C was performed to create ~1.8 displacements-per-atom (dpa) damage in AM 316L. Deformation behaviors of the as-manufactured, annealed, and proton-irradiated variants were studied, focusing on the effects of manufacturing-induced pores, residual stress, and irradiation-introduced defects (dislocation loops and voids). Micro-pillars were prepared from grains of pre-selected orientation, avoiding contributions of grain boundaries and allowing determination of resolved shear stress on {111} glide planes. Transmission electron microscopy was used to characterize the pre- and post-deformation microstructure. It was found that in the as-manufactured alloy variant, moving dislocations were the major deformation carrier, with noticeable blocking by fabrication-induced pores, In the annealed variant, hardness was reduced, and deformation was also accomplished by dislocation gliding. In the proton-irradiated variant, significant twinning was observed. Comparing measured resolved shear stress and predicted critical stress for dislocation dissociation, we conclude that irradiation hardening became high enough to activate twinning. Therefore, the deformation mechanism changes from dislocation gliding to twinning. The study is important for both processing optimization and performance evaluation of AM alloys for reactor applications.

36 MATERIALS SCIENCE↗

Effect of epitope variant co-delivery on the depth of CD8 T cell responses induced by HIV-1 conserved mosaic vaccines

To stop the HIV-1 pandemic, vaccines must induce responses capable of controlling vast HIV-1 variants circulating in the population as well as those evolved in each individual following transmission. Numerous strategies have been proposed, of which the most promising include focusing responses on the vulnerable sites of HIV-1 displaying the least entropy among global isolates and using algorithms that maximize vaccine match to circulating HIV-1 variants by vaccine cocktails of optimized complementing sequences. In this study, we investigated CD8 T cell responses induced by a bi-valent mosaic of highly conserved HIVconsvX regions delivered by a combination of simian adenovirus ChAdOx1 and poxvirus MVA. We compared partially and fully mono- and bi-valent prime-boost regimens and their ability to elicit T cells recognizing natural epitope variants using an interferon-g enzyme-linked immunospot (ELISPOT) assay. We used 11 well-defined CD8 T cell epitopes in two mouse haplotypes and, for each epitope, assessed recognition of the two vaccine forms together with the other most frequent epitope variants in the HIV-1 database. We conclude that for the magnitude and depth of epitope recognition, CD8 T cell responses benefitted in most comparisons from the combined bi-valent mosaic and envisage the main advantage of the bi-valent vaccine during its deployment to diverse populations.

59 BASIC BIOLOGICAL SCIENCES↗

Structural Insights into Low and High Recalcitrance Natural Poplar Variants Using Neutron and X-ray Scattering

Here, we used small-angle neutron scattering (SANS) and wide-angle X-ray scattering (WAXS) to study two Populus trichocarpa variants, GW-11012 and BESC-316, with lignin contents of 17.8 and 23.2%, respectively, to understand why the low lignin variant has increased sugar release during liquid hot water (LHW) pretreatment. SANS showed differences in cell wall polymer arrangement in the variants. In GW-11012, the cellulose microfibrils were similar in size to BESC-316 but were not equally spaced and lignin was aggregated rather than homogenously interspersed with other matrix co-polymers. However, after LHW pretreatments, the SANS profiles of the pretreated variants were almost indistinguishable, indicating that the nanoscale structural features could not adequately explain the increased sugar release observed in GW-11012. WAXS analysis revealed higher cellulose crystallinity and larger crystallite size in native and pretreated GW-11012. However, the most significant difference was that the crystallite orientation was approximately 2-fold higher in GW-11012. This suggests that higher crystallite orientation may be favorable for the action of processive cellulases leading to increased sugar release from GW-11012. Our study shows that there is a complex interplay between cell wall polymers during their deposition resulting in changes in lignin distribution and cellulose structure, highlighting the importance of investigating plant cell wall architecture across multiple length scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemoproteogenomic stratification of the missense variant cysteinome

Abstract Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Desai, Heta (ORCID:0000000343621707)↗

Non-coding structural variants disrupt FOXG1 transcriptional regulation in early neurodevelopment

The FOXG1 transcription factor is a crucial regulator of embryonic brain development. Pathogenic FOXG1 variants cause FOXG1 syndrome. Although structural variants in the non-coding region downstream of FOXG1 have been reported in 38 individuals with similar characteristics, the regulatory pathomechanisms remain unknown. Here, we identify two non-coding structural variants in individuals with FOXG1 syndrome-like features, allowing us to delineate a ~ 124 kb commonly affected regulatory region. Using epigenomic profiling and in vivo enhancer assays, we characterize and validate regulatory elements within the commonly affected regulatory region and wider FOXG1 TAD. We see strong activation of previously validated forebrain enhancers, and identify an enhancer cluster and progenitor-specific enhancer region that are strongly activated during forebrain-directed neural progenitor cell differentiation, a process in which FOXG1 is an important regulator. Perturbation of these elements results in varying degrees of reduced FOXG1 transcription in forebrain neural progenitor cells and in population shifts within these cells, while removal of the TAD boundary leads to aberrant expression of the neighbouring PRKD1 gene. Our findings characterize enhancer and architectural elements essential for proper FOXG1 transcription during neurodevelopment, therefore improving variant interpretation in this region.

Hamerlinck, Lisa↗

Unsupervised learning of ferroic variants from atomically resolved STEM images

An approach for the analysis of atomically resolved scanning transmission electron microscopy data with multiple ferroic variants in the presence of imaging non-idealities and chemical variabilities based on a rotationally invariant variational autoencoder (rVAE) is presented. We show that an optimal local descriptor for the analysis is a sub-image centered at specific atomic units, since materials and microscope distortions preclude the use of an ideal lattice as a reference point. The applicability of unsupervised clustering and dimensionality reduction methods is explored and is shown to produce clusters dominated by chemical and microscope effects, with a large number of classes required to establish the presence of rotational variants. Comparatively, the rVAE allows extraction of the angle corresponding to the orientation of ferroic variants explicitly, enabling straightforward identification of the ferroic variants as regions with constant or smoothly changing latent variables and sharp orientational changes. This approach allows further exploration of the chemical variability by separating the rotational degrees of freedom via rVAE and searching for remaining variability in the system. The code used in this article is available at https://github.com/saimani5/ferroelectric_domains_rVAE.

30 DIRECT ENERGY CONVERSION↗

Evolving dual-trait EPSP synthase variants using a synthetic yeast selection system

The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (K i of nearly 1 mM) and improved enzymatic efficiency over the starting point (~2.5 fold). Finally, we show the crystal structure of corn EPSPS and the top resulting mutants and demonstrate that certain mutants have the potential to outperform previously reported glyphosate-resistant EPSPS mutants, such as T102I and P106S (denoted as TIPS), in whole-plant testing. Altogether, this platform helps explore the trade-off between glyphosate resistance and enzymatic efficiency.

Science & Technology - Other Topics↗

Rapid assessment of SARS-CoV-2–evolved variants using virus-like particles

Efforts to determine why new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants demonstrate improved fitness have been limited to analyzing mutations in the spike (S) protein with the use of S-pseudotyped particles. In this study, we show that SARS-CoV-2 virus-like particles (SC2-VLPs) can package and deliver exogenous transcripts, enabling analysis of mutations within all structural proteins and at multiple steps in the viral life cycle. In SC2-VLPs, four nucleocapsid (N) mutations found universally in more-transmissible variants independently increased messenger RNA delivery and expression ~10-fold, and in a reverse genetics model, the serine-202→arginine (S202R) and arginine-203→methionine (R203M) mutations each produced >50 times as much virus. SC2-VLPs provide a platform for rapid testing of viral variants outside of a biosafety level 3 setting and demonstrate N mutations and particle assembly to be mechanisms that could explain the increased spread of variants, including B.1.617.2 (Delta, which contains the R203M mutation).

60 APPLIED LIFE SCIENCES↗

Domestic Sales Mix of Plug-In Electric Vehicles by Trim Variant and Vehicle Characteristics

As plug-in electric vehicles (PEVs) take up a larger share of the United States vehicle market, their variety increases as well. Since many electric vehicle manufacturers offer multiple PEV trim variants, the distribution of vehicle characteristics such as battery capacity, all-electric range, electricity consumption, and curb weight cannot be determined by sales data alone. Sales data and vehicle registration data were analyzed to quantify and map the trim variant distribution of PEV models from nine automakers. With this information, we quantify national sales-weighted characteristics of fourteen different models over ten years, including battery capacity, fuel economy, and vehicle weight. We find a positive correlation between share of all-wheel drive variants for Tesla vehicles and average annual snowfall, and general uniformity nationwide in other vehicle characteristics. The estimated trim variant distributions will be useful in informing decisions regarding materials recycling and EV impact on the energy grid, and this study found that the total installed battery capacity in PEV in the U.S. was 76 GWh through 2020.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

US National Institutes of Health Prioritization of SARS-CoV-2 Variants

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. Here, the group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

60 APPLIED LIFE SCIENCES↗

Leapfrog variants of iterative methods for linear algebra equations

Two iterative methods are considered, Richardson's method and a general second order method. For both methods, a variant of the method is derived for which only even numbered iterates are computed. The variant is called a leapfrog method. Comparisons between the conventional form of the methods and the leapfrog form are made under the assumption that the number of unknowns is large. In the case of Richardson's method, it is possible to express the final iterate in terms of only the initial approximation, a variant of the iteration called the grand-leap method. In the case of the grand-leap variant, a set of parameters is required. An algorithm is presented to compute these parameters that is related to algorithms to compute the weights and abscissas for Gaussian quadrature. General algorithms to implement the leapfrog and grand-leap methods are presented. Algorithms for the important special case of the Chebyshev method are also given.

Saylor, Paul E.↗

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

Abstract New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

59 BASIC BIOLOGICAL SCIENCES↗