2,642 research outputs found
Exploring missing heritability in neurodevelopmental disorders:Learning from regulatory elements
In this thesis, I aimed to solve part of the missing heritability in neurodevelopmental disorders, using computational approaches. Next to the investigations of a novel epilepsy syndrome and investigations aiming to elucidate the regulation of the gene involved, I investigated and prioritized genomic sequences that have implications in gene regulation during the developmental stages of human brain, with the goal to create an atlas of high confidence non-coding regulatory elements that future studies can assess for genetic variants in genetically unexplained individuals suffering from neurodevelopmental disorders that are of suspected genetic origin
Characterisation of peroxisomes in the fission Yeast Schizosaccharomyces pombe and slime mold Dictyostelium discoideum
Peroxisome is a compartment that is found in most eukaryotic organisms' cells. It has several crucial roles, such as fatty acid beta (β) oxidation and hydrogen peroxide (H2O2) detoxification. It contains many essential enzymes, including oxidase and catalase, and has several metabolic and non-metabolic pathways, depending on the environment and the organisms within its cells. This study investigates the role of peroxisomes in two organisms, S. pombe and D. discoideum.
Although S. pombe is a well-studied yeast, there is only one study of this yeast that has focused on peroxisomes. This study offers a few crucial observations, including that S. pombe contains peroxisomes, that GFP containing a well-characterized PTS1 (SKL) is efficiently imported, and that peroxisome numbers increase in cells grown on a fatty acid as the sole carbon source, suggesting a role for peroxisomes in fatty acid degradation.
The starting point in my research was initially a bioinformatics screen. This screening recognized the enzymes imported into peroxisomes based on the presence of a potential peroxisomal targeting signal. A few proteins were found. However, the low number of proteins with a classical PTS might be the result of different targeting signals that are not recognized by our bioinformatics parameters. Indeed, in other organisms, there are proteins without PTS1 that still use Pex5 for import. The first example is S. cerevisiae Acyl-CoA oxidase. In a global yeast two-hybrid screen, S. pombe Pex5 was found to bind S. pombe Str3 and Lys3. Consequently, we think that there is conserved targeting of a peroxisomal protein lacking a PTS1 and PTS2 imported into the peroxisome by Pex5. One of these is the Str3 case. Interestingly, proteins involved in peroxisomal fatty acid β -oxidation are absent from the S. pombe genome, casting doubt on the conclusions from the previous study and explaining the low number of potential peroxisomal enzymes.
In D. discoideum, this study investigates the dynamic regulation of peroxisome numbers in response to growth conditions and identifies peroxisomal import and contents through a proximity labeling approach (BioID). Overall, this study sheds light on the roles and regulation of peroxisomes in these two organisms
Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches
Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly
Analytical validation of innovative magneto-inertial outcomes: a controlled environment study.
peer reviewe
PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
Large protein language models are adept at capturing the underlying
evolutionary information in primary structures, offering significant practical
value for protein engineering. Compared to natural language models, protein
amino acid sequences have a smaller data volume and a limited combinatorial
space. Choosing an appropriate vocabulary size to optimize the pre-trained
model is a pivotal issue. Moreover, despite the wealth of benchmarks and
studies in the natural language community, there remains a lack of a
comprehensive benchmark for systematically evaluating protein language model
quality. Given these challenges, PETA trained language models with 14 different
vocabulary sizes under three tokenization methods. It conducted thousands of
tests on 33 diverse downstream datasets to assess the models' transfer learning
capabilities, incorporating two classification heads and three random seeds to
mitigate potential biases. Extensive experiments indicate that vocabulary sizes
between 50 and 200 optimize the model, whereas sizes exceeding 800
detrimentally affect the model's representational performance. Our code, model
weights and datasets are available at
https://github.com/ginnm/ProteinPretraining.Comment: 46 pages, 4figures, 9 table
Multiplexed High-Resolution Imaging Approach to Decipher the Cellular Heterogeneity of the Kidney and its Alteration in Kidney Disease and Nephrolithiasis
Indiana University-Purdue University Indianapolis (IUPUI)Kidney disease and nephrolithiasis both present a major burden on the health care system in the US and worldwide. The cellular and molecular events governing the pathogenesis of these diseases are not fully understood. We propose that defining the cellular heterogeneity and niches in human and mouse kidney tissue specimens from controls and various models of renal disease could provide unique insights into the molecular pathogenesis. For that purpose, a multiplexed fluorescence imaging approach using co-detection by Indexing (CODEX) was used, using a panel of 33 and 38 markers for mouse and human kidney tissues, respectively. A customized computational analytical pipeline was developed and applied to the imaging data using unsupervised and/or semi-supervised machine learning and statistical approaches. The goal was to identify various cell populations present within the tissues, as well as identify unique cellular niches that may be altered with disease and/or injury. In mice, we examined disease models of acute kidney injury (AKI) and in human tissues we analyzed specimens from patients with AKI, IgA nephropathy, chronic kidney disease, systemic lupus erythematosus, and nephrolithiasis. In both mice and humans, the disease and reference samples show similar broad cell populations for the main segments of the nephron, endothelium, as well as similar groups of immune cells, such as resident macrophages and neutrophils. When comparing between health and disease, however, a change in the distribution of few sub-populations occurred. For example, in human kidney tissues, the abundance and distribution of a subpopulation of proximal tubules positive for THY1 (a marker of differentiation and repair), was markedly reduced with disease. Changes observed in mouse tissues included shifts in the immune cell population types and niches with disease. We propose that our analytical workflow and the observed changes in situ will play an important role in deciphering the pathogenesis of kidney disease
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