bluuebunny/crossref_metadata_2025_split huggingface dataset:
ER protein quality control and lipid droplets: Unexpected functional connections
Authors: Olzmann James A 
Published: November 2023

Endoplasmic reticulum‐associated degradation (ERAD) mediates the recognition and destruction of proteins from the early secretory pathway. Substrates of the ERAD pathway include terminally misfolded proteins, unoligomerized subunits of multimeric complexes, and ER‐resident enzymes. Determining how substrates are recognized and targeted for degradation is paramount to combating the over 70 diseases associated with disrupted ER protein folding (e.g. Cystic fibrosis). Integrating proteomic and functional genomic platforms we recently constructed the first ERAD interaction network in mammalian cells. This systems‐level analysis led to our discovery that the p97/VCP‐recruitment factor UBXD8 relocalizes from the ER to lipid droplets (LDs) in response to excess fatty acids. UBXD8 recruitment of p97/VCP to the LD surface stabilized LDs by inhibiting the rate‐limiting enzyme in lipolysis, ATGL. In the current study we employed the acyl‐CoA synthetase inhibitor triacsin c to explore a potential role for LDs or lipid biosynthetic pathways in ERAD. Our analyses indicate that treatment with triacsin c impaired ERAD substrate glycan trimming, dislocation, and degradation. However, disruption of LD biogenesis by inhibiting the conversion of diacylglycerol to triacylglycerol had no effect on ERAD kinetics, arguing against a direct role for LDs in ERAD. Acyl‐CoA synthetases are also required for fatty acid modifications such as palmitoylation. Exploiting a click chemistry approach we identified multiple ERAD components that are palmitoylated, and treatment with the palmitoylation inhibitor 2‐bromopalmitate impaired ERAD substrate degradation. Our data support a model in which a subset of ERAD components traffic to LDs and participate in a LD regulatory complex. Although we find that LDs are dispensable for ERAD, our data reveal an unexpected role for fatty acid modifications in the regulation of ERAD machinery.Support or Funding InformationThis work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (R00DK095921) and the National Institute of General Medical Sciences (R01GM112948).
Test‐driven development improves GRNsight: a web application for visualizing models of gene regulatory networks
Authors: Varshneya Anindita , Anguiano Nicole A. , Samdarshi Mihir , Dionisio John David N. , Fitzpatrick Ben G. , Dahlquist Kam D. 
Published: November 2023

GRNsight is a web application and service for visualizing models of gene regulatory networks (GRNs). A gene regulatory network consists of genes, transcription factors, and the regulatory connections between them which govern the level of expression of mRNA and protein from genes. GRNmap, a MATLAB program that performs parameter estimation and forward simulation of a differential equations model of a GRN, can mathematically model the dynamics of GRNs. GRNsight automatically lays out the network graph based on GRNmap output spreadsheets. GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (activation or repression) and magnitude of the GRNmap weight parameter. Visualizations can be modified through manual node dragging and sliders that adjust the force graph parameters. We have now implemented an exhaustive unit testing framework using Mocha and the Chai assertion library to perform test‐driven development where unit tests are written before new functionality is coded. This framework consists of over 135 automated unit tests that examine about 450 test files to ensure that the program is running as expected. Error and warning messages have a three‐part framework that informs the user what happened, the source of the problem, and possible solutions. For example, GRNsight returns an error when the spreadsheet is formatted incorrectly or the maximum number of nodes or edges is exceeded. The completion of the testing framework marks the close of development for version 1 (the current release stands at version 1.12). In version 2.0 of GRNsight, a new feature will be implemented that colors the nodes (genes) based on the expression data. The user will have the choice to display the experimental data or the data produced by the forward simulation feature in GRNmap. GRNsight is available at http://dondi.github.io/GRNsight/.Support or Funding InformationThis work was partially supported by NSF award 0921038 (B.G.F., K.D.D.), a Kadner‐Pitts Research Grant (K.D.D.), the Loyola Marymount University Summer Undergraduate Research Program (A.V.) and the Loyola Marymount University Rains Research Assistant Program (N.A.A.).
Information extraction from native mass spectra
Authors: Guan Shenheng 
Published: November 2023

Native MS spectra of large protein assemblies are typically characterized by low signal‐to‐noise ratios and broad peak shapes. Accurate peak detection is challenging due to additional issues such as high degrees of peak overlap and highly interleaved charge envelopes. A comprehensive algorithm has been developed to address peak identification, overlapping deconvolution, and charge state assignment in native mass spectra. Our open source software provides a novel and practical tool for those problems and is capable of extracting signals of large protein assemblies from heterogeneous, complex, and noisy native mass spectra.Nonspecifical binding of ligands to large protein complexes is commonly observed in native MS spectra. Here we also present a deconvolution model to discriminate specific bindings of a ligand to a multi‐protein complex target from the nonspecific interactions. Using the deconvolution algorithms with two level modeling steps, specific binding constant(s) can be effectively separated from the nonspecific ones. The nonspecific binding can be modeled by a simple power inverse function. An additional advantage of the method is that the target concentration can be more accurately obtained.Support or Funding InformationThis work was supported by grants from the National Institutes of Health (1S10OD016229, 8P41GM103481, GM49985, GM36659, AI‐21144, NS059690, GM109896, AG021601, AG002132, and AG010770).
GRNmap and GRNsight: open source software for dynamical systems modeling and visualization of medium‐scale gene regulatory networks
Authors: Dahlquist Kam D. , Fitzpatrick Ben G. , Dionisio John David N. , Anguiano Nicole A. , Carrillo Juan S. , Hong Monica V. , Horstmann Kristen M. , Jackson Kayla C. , Johnson K. Grace , Morris Tessa A. , Roque Trixie Anne M. , Samdarshi Mihir , Varshneya Anindita , Williams Natalie E. , Wyllie Kevin W. 
Published: November 2023

A gene regulatory network (GRN) consists of genes, transcription factors, and the regulatory connections between them that govern the level of expression of mRNA and proteins from those genes. Our group has developed a MATLAB software package, called GRNmap, that uses ordinary differential equations to model the dynamics of medium‐scale GRNs. The program uses a penalized least squares approach (Dahlquist et al. 2015, DOI: 10.1007/s11538‐015‐0092‐6) to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on gene expression data, and then performs a forward simulation of the dynamics of the network. GRNmap has options for using a sigmoidal or Michaelis‐Menten production function. Parameters for a series of related networks, ranging in size from 15 to 35 genes, were optimized against DNA microarray data measuring the transcriptional response to cold shock in wild type and five strains individually deleted for the transcription factors, Cin5, Gln3, Hap4, Hmo1, Zap1, of budding yeast, Saccharomyces cerevisiae BY4741. Model predictions fit the experimental data well, within the 95% confidence interval. Open source code and a compiled executable that can run without a MATLAB license are available from <http://kdahlquist.github.io/GRNmap/>. GRNsight is an open source web application for visualizing such models of gene regulatory networks. GRNsight accepts GRNmap‐ or user‐generated spreadsheets containing an adjacency matrix representation of the GRN and automatically lays out the graph of the GRN model. The application colors the edges and adjusts their thicknesses based on the sign (activation or repression) and the strength (magnitude) of the regulatory relationship, respectively. Users can then modify the graph to define the best visual layout for the network. The GRNsight open source code and application are available from <http://dondi.github.io/GRNsight/index.html>.Support or Funding InformationThis work was partially supported by NSF award 0921038 (K.D.D., B.G.F.), the Kadner‐Pitts Research Grant (K.D.D., M.V.H., K.G.J., N.E.W.) the Loyola Marymount University Summer Undergraduate Research Program 2015 (K.W.W., A.V.), the Loyola Marymount University Rains Research Assistant Program (N.A.A., T.A.M.), and an Loyola Marymount University Honors Summer Research Fellowship (M.V.H., K.G.J., N.E.W.).
Arc fluorescence in situ hybridization in cleared whole brains utilizing hybridization chain reaction amplification
Authors: Nguyen Minhkhoi , Chawla Monica K , Barnes Carol A 
Published: November 2023

Fluorescence in situ hybridization (FISH) has been used to track the localization of Arc transcripts as a molecular method for quantifying behavior‐driven activity in the hippocampus (Guzowski et al., 1999). But with the development of several tissue clearing techniques like CUBIC (Susaki et al., 2014), CLARITY (Chung et al., 2013), and passive‐CLARITY (Tomer et al., 2014) the opportunity to use Arc FISH on transparent brains to map out intact neural networks is now feasible. Convention has been to use the full length Arc riboprobe (~3.1 kb; Lyford et al., 1995) for FISH in 20 micron thick slices. However, in whole cleared brains, the full length Arc cRNA probe cannot easily penetrate the brain due to its thickness. We sought a solution to the issue of penetration with hybridization chain reaction (HCR) (Choi et al., 2014). HCR is a technique that utilizes DNA probes instead of RNA riboprobes. Since DNA probes are inherently more stable, and HCR probes are less than 150 bases in length, this should drastically improve penetration. In addition, HCR fluorescence hairpins self‐polymerize off of the DNA probe and thus, amplify the fluorescence signal. F344 rats were given maximal electroconvulsive seizure (MECS) to induce transcription, anesthetized, and decapitated with a rodent guillotine. The brains were extracted, fixed in paraformaldehyde, and cleared using the CUBIC reagent (containing aminoalcohols) for 2–3 weeks. Using HCR amplified fluorescence in situ hybridization, we expect to visualize Arc positive cells in rat hippocampus using an advanced intravital multi‐photon microscope.Support or Funding InformationMcKnight Brain Research Foundation; NIH Grant AG048907
Easier elution of urinary proteins preserved on nitrocellulose membrane with heating
Authors: QIN WEIWEI 
Published: November 2023

Biomarker is measurable changes associated with the disease. Urine collects changes of the body and it is a better source for biomarker research than blood which is kept almost constant by homeostatic mechanisms of the body. Urimem, adsorbing urinary proteins on a piece of membrane which can be dried and stored in a vacuum bag, was proposed in the lab. In general, this approach is simple, economical, environmentally friendly and space‐saving, which enables comprehensive and systematic collection of urine from all people. It can potentially be an important part of the medical record. The preservation of urinary proteins on a membrane plays a vital role in searching biomarker in urine, and the efficient elution of proteins preserved on the membrane help to lower the barrier for more applications. The original elution procedure relied mainly on vortexing for complete dissolve of nitrocellulose in organic solvent. In current procedure, we raised the temperature for easier nitrocellulose dissolve, and then we precipitated proteins with gentle rotating to keep nitrocellulose dissolved during the procedure. SDS‐PAGE and LC‐MS/MS analysis showed there was no degradation of proteins prepared by heat‐and‐elute procedure. Its overlapping rate of the proteins prepared in separate experiments was 92.6%. By semi‐quantitative spectral counting the quantities of 85.2% of identified proteins’ CV values were within 20%. And the heating elution procedure was much simpler and more efficient than the previous one. It helps more researchers to adopt the membrane preservation of urinary proteins.Support or Funding InformationNational Basic Research Program of China (973 Program)(Nos. 2012CB517605, 2013CB530805); 111 Project (No. B08007).
A Metabolomics Investigation of the Physiological Component of the Innate Immune Response in RAW264.7 Macrophages Treated with Nitric Oxide Inhibitors
Authors: May Amanda , Wepy James , Marnett Lawrence 
Published: November 2023

Ultra performance liquid chromatography‐high resolution mass spectrometry (UPLC‐HRMS) based metabolomics is capable of providing a global snapshot of alterations in the intracellular small molecule content (the metabolome) that can be used to probe the temporal changes in metabolism in response to perturbations. Using untargeted UPLC‐HRMS metabolomics (Anal. Chem., 2010, 82 (8), pp 3212–3221), the metabolome of RAW264.7 macrophages treated with Kdo‐Lipid2 (KLA), a chemically defined lipopolysaccharide, was measured and compared to a control metabolome from untreated cells. Initial biochemical studies were used to supplement the metabolomics data and have shown that treatment of RAW264.7 macrophages with KLA induces nitric oxide synthase (iNOS), which leads to the production of nitric oxide (NO) through the conversion of arginine to citrulline. While arginine concentrations remained unchanged in the two populations, other amino acids involved in nitrogen metabolism (glutamine and glutamate) and oxidative stress (glutathione), show decreases in pool size when cultures are treated with KLA after 8 hours. Metabolites involved in arginine and proline metabolism, the metabolic pathway encompassing NO synthesis, also show a decrease in fold change at 8 h. These are proline, sarcosine, L‐argininosuccinate, and aspartate. Macrophages were also co‐incubated with KLA and either a broad NOS inhibitor, L‐NAME (Methods Enzymol., 1996, 268, pp 375–392), or selective iNOS inhibitor 1400W (J Biol Chem., 1997, 272, pp 4959–4963), and the metabolomes and NO production from these cells were recorded. Global alterations in metabolism were noted, and the NO concentrations were diminished at 24 hours, as NO was not detected prior to then, when incubated with either inhibitor. The iNOS activity was also indirectly monitored by measuring citrulline via liquid chromatography‐tandem mass spectrometry. This concentration of this metabolite increased between the KLA treated and untreated populations, while the addition of each inhibitor subsequently diminished the increase at 24 hours. Herein, the temporal metabolic response of RAW264.7 macrophages either treated with KLA or not over 24 hours is reported to reveal differences in metabolism for cells that are experiencing an induction of the inflammatory response via KLA.Support or Funding InformationAuthors would like to acknowledge funding of this research through the NIEHS (2T32ES007028–40).
Identification of Apoptosis Inducing Signaling Pathways and Characterization of Sclerotium rolfsii Lectin (SRL) Binding Proteins from Human Colon Epithelial Cancer HT29 cells
Authors: Guha Nilanjan , Gudihal Ravindra , Barkeer Sreekanth , Deepak SA , Padmanaban Arunkumar , Inamdar Shashikala 
Published: November 2023

Sclerotium rolfsii lectin (SRL) is isolated from fungus Sclerotium rolfsii and exhibits strong receptor mediated anti‐proliferative activity towards human colon, breast and ovarian cancer cells by inducing apoptosis. In this study, we investigated the signaling pathways that lead to apoptosis by combining transcriptomics data from gene expression and miRNA microarray analysis data and performed pathway analysis using features of GeneSpring 13.1 (GS 13.1). We also identified SRL binding membrane proteins from HT29 cells using proteomics experiments.It was found that SRL treatment results in altered expression of several hundred molecules including MAPK and c‐JUN‐associated, apoptosis‐associated, cell cycle and DNA replication‐associated signaling molecules. Pathway analysis using GS 13.1 revealed that SRL treatment induces changes of MAPK and c‐JUN associated signaling pathways as early as 2h while changes of cell cycle, DNA replication and apoptosis pathways were significantly affected after 24h. A significant change of miRNA expression was also observed after 12h SRL treatment. These changes were further validated by qRT‐PCR and immunoblotting. The study suggests that the presence of SRL affects multiple signaling pathways in cancer cells with early effects on cell proliferation pathways associated with MAPK and c‐JUN, followed by miRNA‐associated cell activity and apoptosis.Membrane proteins from HT29 cells were isolated by phase separation and purified by affinity chromatography using SRL‐Sepharose‐4B matrix. Affinity purified proteins were subjected to in‐gel and in‐solution trypsin digestion, analyzed by ESI‐Q‐TOF LC‐MS and Agilent Spectrum Mill software. Considering the specificity of SRL towards O‐glycans, the presence of O‐GalNAc sites in SRL interacting proteins were tested using NetOGlyc software. Western blotting was performed to validate the MS identified proteins. A major protein band around 25kDa following in‐gel trypsin digestion was identified as Keratin 1 by MS. In‐solution trypsin digestion followed by MS identified 25 SRL interacting proteins namely, keratins, heat shock proteins, tubulins, pyruvate kinase M2, peroxiredoxin‐1, ATP synthase subunit alpha, actin, annexin‐A2, prohibitin, ADP/ATP translocase‐2 and alpha enolase. NetOGlyc software analysis revealed 21 proteins positive for O‐glycosylation sites including keratins containing 27 to 50 O‐GalNAc sites. Keratin 1 identified and validated by western blotting as major SRL interacting protein showed 49 O‐GalNAc sites. Proteins identified in our proteomics studies contain O‐GalNAc sites and are known to be involved in cell survival, apoptosis and tumorigenesis. These findings demonstrate the signature profiles of SRL ‐induced gene expression which helps in understanding the lectin's mechanism of action.
Genomics of Gastrointestinal Disorders: a Familial Based Approach
Authors: Coble Joel L. , Sheldon Kathryn , Yue Feng , Schneper Lisa , Choi Christine , Poirier Kendra , Salameh Tarik , Harris Leonard , Deiling Sue , Ruggiero Francesca , Broach James R. , Koltun Walter A. , Gerhard Glenn S. 
Published: November 2023

BackgroundInflammatory Bowel Disease (IBD) and Diverticular Disease (DD) are both gastrointestinal disorders known to have a genetic component. IBD comprises both Ulcerative Colitis (UC) and Crohn's Disease (CD). The role of genetics is suggested to be 40–53% for DD and 75% for CD. However, less than 20% of the heritability of CD is accounted for by the known genomic loci. No causative genes have yet been implicated for DD. The purpose of our study is to identify novel genetic contributors to these diseases.MethodsUsing exome sequencing and 2 DD and 1 CD affected families with strong phenotypes, we identified missense single nucleotide variants (SNVs) whose segregation matched disease presentation in the families. The SNVs lie within genes that therefore may contribute to the pathogenesis of each disease. Targeted sequencing of those genes in non‐familial but affected (sporadic) patients was performed to identify any patients with other SNVs in those genes that also have disease. To assess the functional effect of these SNVs, immunofluorescence was performed to identify changes in protein localization and abundance.ResultsWe found two rare missense variants in the genes for basement membrane proteins, LAMB4 and COL1A1, which each segregated with disease in separate DD affected families. Decreased expression of LAMB4 was observed in the myenteric plexus of patients with DD and variants in LAMB4. This decreased expression may affect the development of the enteric nervous system, which can contribute to the pathogenesis of DD. We observed increased COL1A1 protein in the submucosa of patients with DD and with variants in COL1A1. This increased expression confirms the increased collagen expression observed in DD. Altered plasticity of the submucosa may contribute to the development of DD. We identified multiple missense SNVs that matched the pattern of inheritance of the CD affected family and collectively may contribute to the development of CD. These include NOD2 interacting protein DDX58, a regulator of autophagy ATG4B, and a member of a protein family previously associated with CD, ADAMTS16.ConclusionWe have identified additional SNVs and genes that may account for some of the missing heritability in CD. Additionally, we have identified the first genes to be associated with DD, LAMB4 and COL1A1. Further research is needed to elucidate the genomic and molecular pathogenesis of these diseases.
Ramachandran outliers in ligand‐induced protein structural changes
Authors: West Korbin H.J. , Novak Walter R.P. 
Published: November 2023

Ramachandran outliers are amino acid residues that have unfavorable dihedral angles in proteins. Often found in protein structure analysis, the presence of these outliers may be simply errors in the structure; however, other times these outliers existence is supported by structural data. There has been little investigation into the role that these energetically unfavorable outliers have in protein structure. Of special interest is how ligand binding may affect protein structures with respect to Ramachandran outliers. These structural changes may drastically alter the properties of proteins: ligand affinities, protein‐protein interactions, or activity levels. In this study, we survey the Ramachandran outliers in pairs of proteins in the ligand‐bound and unliganded states available in the Protein Structural Change Database (http://idp1.force.cs.is.nagoya‐u.ac.jp/pscdb/). We also examine whether these outliers are supported by the structural data using PDB_REDO (http://xtal.nki.nl/PDB_REDO/).Support or Funding InformationThis research is supported by the Wabash College Haines Biochemistry Fund.