By generating high-resolution electron density maps from atomic structures, this research presents an approach for predicting solution X-ray scattering profiles accurately at wide angles. To account for the excluded volume of bulk solvent, our method uses the atomic coordinates to calculate unique adjusted atomic volumes. The implemented approach eliminates the dependence on a free-fitting parameter often present in existing algorithms, thus improving the accuracy of the calculated small-angle X-ray scattering (SWAXS) profile. An implicit model of the hydration shell is constructed, which leverages the form factor of water. The bulk solvent density and the mean hydration shell contrast, two parameters, are adjusted to optimally align with the data. High-quality fits to the data were observed in the results derived from eight publicly accessible SWAXS profiles. The optimized parameter values exhibit slight modifications, suggesting the default values are quite close to the optimal solution. The act of disabling parameter optimization produces a substantial advancement in the calculated scattering profiles, resulting in superior output over prevailing software. In terms of computational efficiency, the algorithm shows a greater than tenfold reduction in execution time, significantly outpacing the top software. The algorithm is coded directly into the command-line script, designated as denss.pdb2mrc.py. Part of the DENSS v17.0 software suite, this open-source component is accessible via the GitHub repository: https://github.com/tdgrant1/denss. Further enhancements in the capacity to match atomic models against experimental SWAXS data also facilitate the creation of more accurate modeling algorithms built on SWAXS data, minimizing the chance of overfitting.
Atomic models of biological macromolecules in solution can be used to generate accurate small-angle and wide-angle X-ray scattering (SAXS/WAXS) profiles, which are helpful for understanding their solution state and conformational changes. High-resolution real-space density maps are employed in a novel approach to calculating SWAXS profiles from atomic models, which we present here. In this approach, novel calculations regarding solvent contributions eliminate a substantial fitting parameter. To validate the algorithm, multiple high-quality experimental SWAXS datasets were examined, showcasing improved accuracy over prevailing leading software. Leveraging experimental SWAXS data, the algorithm, computationally efficient and resistant to overfitting, boosts the accuracy and resolution of modeling algorithms.
To gain insight into the solution state and conformational dynamics of biological macromolecules, accurate small- and wide-angle scattering (SWAXS) profile calculations from atomic models are essential. From atomic models, and utilizing high-resolution real-space density maps, we introduce a new approach to calculating SWAXS profiles. This approach features novel solvent contribution calculations that eliminate a significant fitting parameter. High-quality experimental SWAXS datasets served as the testing ground for the algorithm, showcasing superior accuracy compared to leading software packages. The algorithm's computational efficiency and resistance to overfitting contribute to improved accuracy and resolution in modeling algorithms which employ experimental SWAXS data.
In an endeavor to comprehend the mutational landscape of the coding genome, a multitude of tumor samples have undergone large-scale sequencing. However, the overwhelming majority of inherited and acquired genetic variations are found outside the protein-coding sections of the genome. Non-cross-linked biological mesh While these genomic regions lack direct protein-encoding capabilities, they can crucially influence cancer's advancement, such as by disrupting the regulation of gene expression. Our integrative computational and experimental platform was constructed to pinpoint recurrently mutated non-coding regulatory regions driving tumor progression. Employing this strategy on whole-genome sequencing (WGS) data from a substantial group of metastatic castration-resistant prostate cancer (mCRPC) patients, a large quantity of recurrently mutated regions was identified. Through in silico prioritization of functional non-coding mutations, coupled with massively parallel reporter assays and in vivo CRISPR-interference (CRISPRi) screens in xenografted mice, we methodically recognized and authenticated driver regulatory regions that cause mCRPC. We determined that enhancer region GH22I030351 affects a bidirectional promoter, resulting in a synchronized modulation of the U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. We observed that both SF3A1 and CCDC157 are tumor growth promoters in xenograft models of prostate cancer. The elevated expression of SF3A1 and CCDC157 was attributed to a set of transcription factors, including SOX6. Apamin datasheet The combined computational and experimental approach we have developed and validated allows for the systematic identification of non-coding regulatory regions that drive the development trajectory of human cancers.
Protein O-GlcNAcylation, a post-translational modification (PTM) of proteins by O-linked – N -acetyl-D-glucosamine, is present across the entire proteome of all multicellular organisms across their entire lifespan. While nearly all functional studies have examined individual protein modifications, they have overlooked the significant number of simultaneous O-GlcNAcylation events that cooperate in regulating cellular functions. We introduce NISE, a novel and comprehensive systems-level approach to rapidly monitor O-GlcNAcylation throughout the proteome, emphasizing the networking of interacting proteins and substrates. Our methodology combines affinity purification-mass spectrometry (AP-MS) and site-specific chemoproteomic technologies with network generation and unsupervised clustering to connect upstream regulatory elements with O-GlcNAcylation targets downstream. This data-laden network reveals a framework encompassing both universal O-GlcNAcylation activities, including epigenetic modification, and tissue-specific functions, such as synaptic morphology. This systems-level approach, encompassing O-GlcNAc and beyond, provides a widely applicable framework for investigating post-translational modifications and unearthing their diverse functions in particular cell types and biological situations.
To effectively investigate the processes of injury and repair in pulmonary fibrosis, one must recognize the diverse spatial characteristics of the disease. In preclinical animal model studies, the modified Ashcroft score, a semi-quantitative rubric evaluating macroscopic resolution, is employed to assess fibrotic remodeling. The inherent limitations of manual pathohistological grading clearly underscore the need for a reliable, repeatable method to assess fibroproliferative tissue burden. By employing computer vision methods on immunofluorescent images of the extracellular matrix protein laminin, we created a repeatable and robust quantitative remodeling scorer (QRS). The modified Ashcroft score and QRS readings showed a substantial agreement (Spearman correlation coefficient r = 0.768) in the bleomycin lung injury model. Multiplex immunofluorescent experiments easily accommodate this antibody-based approach, enabling us to investigate the spatial arrangement of tertiary lymphoid structures (TLS) adjacent to fibroproliferative tissue. Without programming experience, the application outlined in this manuscript can be readily used.
The relentless emergence of new COVID-19 variants, stemming from the ongoing pandemic, suggests a persistent presence and circulation of the virus within the human population, contributing to the millions of deaths. The current availability of vaccines and the innovative development of antibody-based therapies brings forth significant questions regarding the durability of immunity and the extent of protection conferred over prolonged periods. Protective antibody identification in individuals often necessitates specialized functional neutralizing assays, which are not typically part of clinical laboratory procedures. Consequently, a crucial requirement exists for the creation of swift, readily applicable diagnostic tools that align with neutralizing antibody assessments to pinpoint individuals potentially benefiting from supplementary vaccinations or tailored COVID-19 treatments. A novel semi-quantitative lateral flow assay (sqLFA) is introduced in this report, assessing its performance in detecting functional neutralizing antibodies from the serum of COVID-19 convalescent individuals. genetic enhancer elements The sqLFA correlated positively and substantially with neutralizing antibody levels. When assay cutoffs are lower, the sqLFA assay becomes highly sensitive in the identification of varying neutralizing antibody levels. Elevated cutoff levels are crucial for detecting higher concentrations of neutralizing antibodies, ensuring high specificity. The sqLFA, capable of identifying any level of neutralizing antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), serves as a versatile tool for identifying individuals with high levels of neutralizing antibodies who potentially do not need antibody-based therapies or additional vaccinations.
We previously investigated the process of transmitophagy, where mitochondria shed by the axons of retinal ganglion cells (RGCs) are transferred to and broken down by neighboring astrocytes in the optic nerve head of mice. Considering the prominent role of Optineurin (OPTN), a mitophagy receptor and a significant glaucoma gene, and the axonal damage prevalent at the optic nerve head in glaucoma, this study explores the potential effect of OPTN mutations on transmitophagy. A live-imaging study of Xenopus laevis optic nerves showcased that while human mutant OPTN, but not wild-type OPTN, exhibited increased stationary mitochondria and mitophagy machinery colocalization within RGC axons, glaucoma-associated OPTN mutations further prompted their colocalization outside the axons as well. The degradation of extra-axonal mitochondria is carried out by astrocytes. RGC axon studies reveal low mitophagy levels under normal conditions, but glaucoma-related OPTN impairments trigger heightened axonal mitophagy, characterized by mitochondrial release and subsequent astrocytic breakdown.