Biology subjects

Korhonen, E.

Publications and source records attributed to Korhonen, E..

3 recordsLinked to original sources

bioRxiv2024

Frontotemporal dementia patient-derived iPSC neurons show cell pathological hallmarks and evidence for synaptic dysfunction and DNA damage

Frontotemporal dementia (FTD) is the second most common cause of dementia in patients under 65 years, characterized by diverse clinical symptoms, neuropathologies, and genetic background. Synaptic dysfunction is suggested to play a major role in FTD pathogenesis. Disturbances in the synaptic function can also be associated with the C9orf72 repeat expansion (C9-HRE), the most common genetic mutation causing FTD. C9-HRE leads to distinct pathological hallmarks, such as C9orf72 haploinsufficiency and development of toxic RNA foci and dipeptide repeat proteins (DPRs). FTD patient brains, including those carrying the C9-HRE, are also characterized by neuropathologies involving accumulation of TDP-43 and p62/SQSTM1 proteins. This study utilized induced pluripotent stem cell (iPSC)-derived cortical neurons from C9-HRE-carrying or sporadic FTD patients and healthy control individuals. We report that the iPSC neurons derived from C9-HRE carriers developed typical C9-HRE-associated hallmarks, including RNA foci and DPR accumulation. All FTD neurons demonstrated increased TDP-43 nucleus-to-cytosolic shuttling and p62/SQSTM1 accumulation, and changes in nuclear size and morphology. In addition, the FTD neurons displayed reduced number and altered morphologies of dendritic spines and significantly altered synaptic function indicated by a decreased response to stimulation with GABA. These structural and functional synaptic disturbances were accompanied by upregulated gene expression in the FTD neurons related to synaptic function, including synaptic signaling, glutamatergic transmission, and pre- and postsynaptic membrane, as compared to control neurons. Pathways involved in DNA repair were significantly downregulated in FTD neurons. Only one gene, NUPR2, potentially involved in DNA damage response, was differentially expressed between the sporadic and C9-HRE-carrying FTD neurons. Our results show that the iPSC neurons from FTD patients recapitulate pathological changes of the FTD brain and strongly support the hypothesis of synaptic dysfunction as a crucial contributor to disease pathogenesis in FTD.

neuroscience↗

bioRxiv2023

Breast Milk Oligosaccharides Contain Immunomodulatory Glucuronic Acid and LacdiNAc

Breast milk is abundant with functionalized milk oligosaccharides (MOs), to nourish and protect the neonate. Yet we lack a comprehensive understanding of the repertoire and evolution of MOs across Mammalia. We report [~]400 MO-species associations (>100 novel structures) from milk glycomics of nine mostly understudied species: alpaca, beluga whale, black rhinoceros, bottlenose dolphin, impala, LHoests monkey, pygmy hippopotamus, domestic sheep, and striped dolphin. This revealed the hitherto unknown existence of the LacdiNAc motif (GalNAc{beta}1-4GlcNAc) in MOs of all species except alpaca, sheep, and striped dolphin, indicating widespread occurrence of this potentially antimicrobial motif in MOs. We also characterize glucuronic acid-containing MOs in the milk of impala, dolphins, sheep, and rhinoceros, previously only reported in cows. We demonstrate that these GlcA-MOs exhibit potent immunomodulatory effects. Our study extends the number of known MOs by >15%. Combined with >1,900 curated MO-species associations, we characterize MO motif distributions, presenting an exhaustive overview of MO biodiversity.

biochemistry↗

bioRxiv2021

LectinOracle - A Generalizable Deep Learning Model for Lectin-Glycan Binding Prediction

Ranging from bacterial cell adhesion over viral cell entry to human innate immunity, glycan-binding proteins or lectins abound in nature. Widely used as staining and characterization reagents in cell biology, and crucial for understanding the interactions in biological systems, lectins are a focal point of study in glycobiology. Yet the sheer breadth and depth of specificity for diverse oligosaccharide motifs has made studying lectins a largely piecemeal approach, with few options to generalize. Here, we present LectinOracle, a model combining transformer-based representations for proteins and graph convolutional neural networks for glycans to predict their interaction. Using a curated dataset of 564,647 unique protein-glycan interactions, we show that LectinOracle predictions agree with literature-annotated specificities for a wide range of lectins. We further identify clusters of lectins with related binding specificity that are not clustered based on sequence similarity. Using a range of specialized glycan arrays, we show that LectinOracle predictions generalize to new glycans and lectins, with qualitative and quantitative agreement with experimental data. We further demonstrate that LectinOracle can analyze whole lectomes and their role in host-microbe interactions. We envision that the herein presented platform will advance both the study of lectins and their role in (glyco)biology.

bioinformatics↗