Biology subjects

Bishof, I.

Publications and source records attributed to Bishof, I..

4 recordsLinked to original sources

bioRxiv2025

Multiomic clocks to predict phenotypic age in mice

Biological age refers to a persons overall health in aging, as distinct from their chronological age. Diverse measures of biological age, referred to as "clocks", have been developed in recent years and enable risk assessments, and an estimation of the efficacy of longevity interventions in animals and humans. While most clocks are trained to predict chronological age, clocks have been developed to predict more complex composite biological age outcomes, at least in humans. These composite outcomes can be made up of a combination of phenotypic data, chronological age, and disease or mortality risk. Here, we develop the first such composite biological age measure for mice: the mouse phenotypic age model (Mouse PhenoAge). This outcome is based on frailty measures, complete blood counts, and mortality risk in a longitudinally assessed cohort of male and female C57BL/6 mice. We then develop clocks to predict Mouse PhenoAge, based on multi-omic models using metabolomic and DNA methylation data. Our models accurately predict Mouse PhenoAge, and residuals of the models are associated with remaining lifespan, even for mice of the same chronological age. These methods offer novel ways to accurately predict mortality in laboratory mice thus reducing the need for lengthy and costly survival studies.

systems biology↗

bioRxiv2023

Measuring technical variability in Illumina DNA methylation microarrays

DNA methylation microarrays have become a widely used tool for investigating epigenetic modifications in various aspects of biomedical research. However, technical variability in methylation data poses challenges for downstream applications such as predictive modeling of health and disease. In this study, we measure the impact of common sources of technical variability in Illumina DNA methylation microarray data, with a specific focus on positional biases inherent within the microarray technology. By utilizing a dataset comprised of multiple, highly similar technical replicates, we identified a chamber number bias, with different chambers of the microarray exhibiting systematic differences in fluorescence intensities and their derived methylation beta values, which are only partially corrected for by existing preprocessing methods, and demonstrate that this positional bias can lead to false positive results during differential methylation testing. Additionally, our investigation identified outliers in low-level fluorescence data which might play a role in contributing to predictive error in computational models of health-relevant traits such as age.

bioinformatics↗

bioRxiv2019

Middle-down proteomics reveals dense sites of methylation and phosphorylation in arginine-rich RNA-binding proteins

Arginine (Arg)-rich RNA-binding proteins play an integral role in RNA metabolism. Post-translational modifications (PTMs) within Arg-rich domains, such as phosphorylation and methylation, regulate multiple steps in RNA metabolism. However, the identification of PTMs within Arg-rich domains with complete trypsin digestion is extremely challenging due to the high density of Arg residues within these proteins. Here, we report a middle-down proteomic approach coupled with electron transfer dissociation (ETD) mass spectrometry to map previously unknown sites of phosphorylation and methylation within the Arg-rich domains of U1-70K and structurally similar RNA-binding proteins from nuclear extracts of HEK293 cells. Remarkably, the Arg-rich domains in RNA-binding proteins are densely modified by methylation and phosphorylation compared with the remainder of the proteome, with di-methylation and phosphorylation favoring RSRS motifs. Although they favor a common motif, analysis of combinatorial PTMs within RSRS motifs indicate that phosphorylation and methylation do not often co-occur, suggesting they may functionally oppose one another. Collectively, these findings suggest that the level of PTMs within Arg-rich domains may be among the highest in the proteome, and a possible unexplored regulator of RNA metabolism. These data also serve as a resource to facilitate future mechanistic studies of the role of PTMs in RNA-binding protein structure and function.\n\nBriefsMiddle-down proteomics reveals arginine-rich RNA-binding proteins contain many sites of methylation and phosphorylation.

biochemistry↗

bioRxiv2018

RNA-binding proteins with mixed charge domains self-assemble and aggregate in Alzheimer’s Disease

U1 small nuclear ribonucleoprotein 70 kDa (U1-70K) and other RNA binding proteins (RBPs) are mislocalized to cytoplasmic neurofibrillary Tau aggregates in Alzheimers disease (AD), yet understanding of the mechanisms that cause their aggregation is limited. Many RBPs that aggregate in neurodegenerative diseases self-assemble into RNA granules through intrinsically disordered low complexity (LC) domains. We report here that a LC domain within U1-70K of mixed charge, containing highly repetitive complementary repeats of basic (R/K) and acidic (D/E) residues, shares many of the same properties of the Q/N-rich LC domains found in the RBPs TDP-43 and FUS. These properties include the ability to self-assemble into oligomers, and to form nuclear granules. To analyze the functional roles of the U1-70K LC domains, we performed co-immunoprecipitation and quantitative mass spectrometry analysis of recombinant U1-70K and deletions lacking the C-terminal LC domain(s). A network-driven approach resolved functional classes of U1-70K interacting proteins that showed dependency on the U1-70K LC domain(s) for their interaction. This included structurally similar RBPs, such as LUC7L3 and RBM25, which require their respective mixed charge domains for reciprocal interactions with U1-70K and for participation in nuclear RNA granules. Strikingly, a significant proportion of RBPs with mixed charge domains have elevated insolubility in AD brain proteome compared to controls. Furthermore, we show that the mixed charge LC domain of U1-70K can interact with Tau from AD brain. These findings highlight mechanisms for mixed charge domains in stabilizing RBP interactions and in potentially mediating co-aggregation with pathological Tau isoforms in AD.

biochemistry↗