Publications by authors named "Brian D Halligan"

Background & Aims: Steatotic liver disease (SLD), characterized by elevated liver fat content (LFC), is influenced by genetics and diet. However, whether diet has a differential effect based on genetic risk is not well-characterized. We aimed to determine how genetic factors interact with diet to affect SLD in a large national biobank.

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Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank.

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Article Synopsis
  • Nonalcoholic fatty liver disease (NAFLD) is widespread, partly genetic, and currently lacks effective treatment options.
  • A genome-wide association study (GWAS) identified several genetic variants linked to NAFLD, focusing on genes related to metabolism and liver function.
  • Genetic risk factors can help classify NAFLD into subtypes and significantly increase the risk of severe liver complications, potentially aiding in the development of targeted therapies.
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Article Synopsis
  • Human studies found genetic variations near the LYPLAL1 gene that influence fat distribution and metabolic traits differently in males and females.
  • Researchers created a mouse model lacking the LYPLAL1 gene and observed that female mice on a high-fat diet gained less weight and fat compared to male mice and showed different metabolic markers.
  • The findings suggest that LYPLAL1 has a significant and conserved role in regulating obesity and metabolism based on sex, providing a new model to explore its potential effects in humans.
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Non-alcoholic fatty liver disease (NAFLD) is caused by excess lipid accumulation in hepatocytes. Genome-wide association studies have identified a strong association of NAFLD with non-synonymous E167K amino acid mutation in the transmembrane 6 superfamily member 2 (TM6SF2) protein. The E167K mutation reduces TM6SF2 stability, and its carriers display increased hepatic lipids and lower serum triglycerides.

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Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics.

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The JHK virus (JHKV) was previously described as a type C retrovirus that has some distinctive ultrastructural features and replicates constitutively in a human B-lymphoblastoid cell line, JHK-3. In order to facilitate the cloning of sequences from JHKV, a series of partially degenerate consensus retroviral PCR primers were created by a data-driven design approach based on an alignment of 14 diverse gammaretroviral genomes. These primers were used in the PCR amplification of purified JHK virion cDNA, and ana lysis of the resulting amplified sequence indicates that the JHKV is in the murine leukemia virus (MLV) family.

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During infection by human cytomegalovirus (HCMV), the tumor suppressor protein p53, which promotes efficient viral gene expression, is stabilized. However, the expression of numerous p53-responsive cellular genes is not upregulated. The molecular mechanism used to manipulate the transcriptional activity of p53 during infection remains unclear.

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The renal medullary thick ascending limb (mTAL) of the Dahl salt-sensitive (SS) rat is the site of enhanced NaCl reabsorption and excess superoxide production. In the present studies we isolated mitochondria from mTAL of SS and salt-resistant control strain SS.13(BN) rats on 0.

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A major challenge in the field of high-throughput proteomics is the conversion of the large volume of experimental data that is generated into biological knowledge. Typically, proteomics experiments involve the combination and comparison of multiple data sets and the analysis and annotation of these combined results. Although there are some commercial applications that provide some of these functions, there is a need for a free, open source, multifunction tool for advanced proteomics data analysis.

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Infection with the β-herpesvirus human cytomegalovirus (HCMV) is lifelong, causing limited disease in healthy adults, but life threatening in immunocompromised individuals. The viral kinase pUL97, a functional ortholog of cellular cyclin-dependent kinases (CDKs), is critical for HCMV replication and a target for antiviral drug development. Upon kinase inhibition, drug-resistant strains emerge with mutations in UL27, an HCMV gene of unknown function.

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Obligately aerobic ammonia-oxidizing bacteria (AOB) like Nitrosomonas europaea play a pivotal role in the global nitrogen cycle. Although starvation tolerance is a key environmental adaptation, little is known about this response in AOB. The goal of these studies was to compare the composition of the N.

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Purpose: Ureteropelvic junction obstruction may either worsen and require surgery, improve or remain stable. It may take upward of 3 years for the natural history to unfold. Urinary proteome analysis using capillary electrophoresis mass spectrometry has been shown to differentiate between normal infants and those with ureteropelvic junction obstruction.

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We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.

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Victims of nuclear accidents or radiological terrorism are likely to receive varying doses of ionizing radiation inhomogeneously distributed over the body. Early biomarkers may be useful in determining organ-specific doses due to total body irradiation (TBI) or partial body irradiation. The authors used liquid chromatography and mass spectrometry to compare the effect of TBI and local kidney irradiation (LKI) on the rat urine proteome using a single 10-Gy dose of x-rays.

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One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run.

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Protein modifications such as phosphorylation are often studied by two-dimensional gel electrophoresis, since the perturbation in the protein's pI value is readily detected by this method. It is important to be able to calculate the changes in the pI values that specific post-translational modifications cause and to visualize how these changes will effect protein migration on 2D gels. To address this need, we have developed ProMoST.

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Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model.

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Membrane-bound and membrane-associated proteins are difficult to analyze by mass spectrometry, since the association with lipids impedes the isolation and solubilization of the proteins in buffers suitable for mass spectrometry and the efficient generation of positively charged peptide ions by electrospray ionization. Current methods mostly utilize detergents for the isolation of proteins from membranes. In this study, we present an improved detergent-free method for the isolation and mass spectrometric identification of membrane-bound and membrane-associated proteins.

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One of the core activities of high-throughput proteomics is the identification of peptides from mass spectra. Some peptides can be identified using spectral matching programs like Sequest or Mascot, but many spectra do not produce high quality database matches. De novo peptide sequencing is an approach to determine partial peptide sequences for some of the unidentified spectra.

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Stable isotope labeling with (18)O is a promising technique for obtaining both qualitative and quantitative information from a single differential protein expression experiment. The small 4 Da mass shift produced by incorporation of two molecules of (18)O, and the lack of available methods for automated quantification of large data sets has limited the use of this approach with electrospray ionization-ion trap (ESI-IT) mass spectrometers. In this paper, we describe a method of acquiring ESI-IT mass spectrometric data that provides accurate calculation of relative ratios of peptides that have been differentially labeled using(18)O.

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The main goal of comparative proteomics is the quantitation of the differences in abundance of many proteins between two different biological samples in a single experiment. By differentially labeling the peptides from the two samples and combining them in a single analysis, relative ratios of protein abundance can be accurately determined. Protease catalyzed (18)O exchange is a simple method to differentially label peptides, but the lack of robust software tools to analyze the data from mass spectra of (18)O labeled peptides generated by common ion trap mass spectrometers has been a limitation.

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We describe the theoretical basis for a peptide identification method wherein peptides are represented as vectors based on their amino acid composition and grouped into clusters. Unknown peptides are identified by finding the database cluster and peptide entries with the shortest Euclidian distance. We demonstrate that the amino acid composition of peptides is virtually as informative as the sequence and allows rapid peptide identification more accurately than peptide mass alone.

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ProMoST is a flexible web tool that calculates the effect of single or multiple posttranslational modifications (PTMs) on protein isoelectric point (pI) and molecular weight and displays the calculated patterns as two-dimensional (2D) gel images. PTMs of proteins control many biological regulatory and signaling mechanisms and 2D gel electrophoresis is able to resolve many PTM-induced isoforms, such as those due to phosphorylation, acetylation, deamination, alkylation, cysteine oxidation or tyrosine nitration. These modifications cause changes in the pI of the protein by adding, removing or changing titratable groups.

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