bioRxiv Science⌕ Search

Biology subjects

Buchser, W.

Publications and source records attributed to Buchser, W..

4 recordsLinked to original sources

Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes

Cellular phenotypes emerge from a hierarchy of molecular interactions: proteins interact to form complexes, pathways, and phenotypes. We show that hierarchical networks of protein interactions can be extracted from the statistical pattern of proteome variation as measured across thousands of bacteria and that these hierarchies reflect the emergence of complex bacterial phenotypes. We describe the mathematics underlying our statistical approach and validate our results through gene-set enrichment analysis and comparison to existing experimentally-derived hierarchical databases. We demonstrate the biological utility of our unbiased hierarchical models by creating a model of motility in Pseudomonas aeruginosa and using it to discover a previously unappreciated genetic effector of twitch-based motility. Overall, our approach, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), predicts hierarchies of protein interaction networks describing emergent biological function using only the statistical pattern of bacterial proteome variation.

systems biology↗

Weakly activated core inflammation pathways were identified as a central signaling mechanism contributing to the chronic neurodegeneration in Alzheimer's disease

Neuro-inflammation signaling has been identified as an important hallmark of Alzheimers disease (AD) in addition to amyloid {beta} plaques (A{beta}) and neurofibrillary tangles (NFTs). However, our knowledge of neuro-inflammation is very limited; and the core signaling pathways associated with neuro-inflammation are missing. From a novel perspective, i.e., investigating weakly activated molecular signals (rather than the strongly activated molecular signals), in this study, we uncovered the core neuro-inflammation signaling pathways in AD. Our novel hypothesis is that weakly activated neuro-inflammation signaling pathways can cause neuro-degeneration in a chronic process; whereas, strongly activated neuro-inflammation often cause acute disease progression like in COVID-19. Using the two large-scale genomics datasets, i.e., Mayo Clinic (77 control and 81 AD samples) and RosMap (97 control and 260 AD samples), our analysis identified 7 categories of signaling pathways implicated on AD and related to virus infection: immune response, x-core signaling, apoptosis, lipid dysfunctional, biosynthesis and metabolism, and mineral absorption signaling pathways. More interestingly, most of genes in the virus infection, immune response and x-core signaling pathways, are associated with inflammation molecular functions. Specifically, the x-core signaling pathways were defined as a group of 9 signaling proteins: MAPK, Rap1, NF-kappa B, HIF-1, PI3K-Akt, Wnt, TGF-beta, Hippo and TNF, which indicated the core neuro-inflammation signaling pathways responding to the low-level and weakly activated inflammation and hypoxia, and leading to the chronic neuro-degeneration. The core neuro-inflammation signaling pathways can be used as novel therapeutic targets for effective AD treatment and prevention.

neuroscience↗

VCP protects neurons from proteopathic seeding

Uptake and spread of proteopathic seeds, such as S, Tau, and TDP-43, contribute to neurodegeneration. The cellular machinery necessary for this process is poorly understood. Using a genome-wide CRISPR-Cas9 screen, we identified Valosin Containing Protein (VCP) as a suppressor of S seeding. Dominant mutations in VCP cause multisystem proteinopathy (MSP) with muscle and neuronal degeneration. VCP inhibition or disease mutations increase S seeding in cells and neurons. This is not associated with an increase in seed uptake and is similar to treatment with the lysosomal damaging agent, LLoME. Intrastriatal injection of S seeds into VCP disease mice enhances seeding efficiency compared with controls. This is not specific to S since VCP inhibition or disease mutations increased TDP-43 seeding in neurons. These data support that VCP protects against proteopathic spread of pathogenic aggregates. The spread of distinct aggregate species may dictate pleiotropic phenotypes and pathologies in VCP associated MSP.

neuroscience↗

Integrative omics data analysis uncovers biomarker genes and potential candidate drugs for G3 medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in infants and children. Four molecular subtypes of MB are recognized: WNT, SHH, Group 3 (G3), and Group 4 (G4). Compared with WNT and SHH subtypes, G3 MBs exhibit significantly worse outcomes and higher metastatic rates, and there is no effective treatment yet. Moreover, G3 and G4 MBs are much more common in boys than girls, i.e., sex bias, which also plays important roles in cancer prognosis and drug response. However, the molecular mechanism of G3 remains unclear, and there are no well-identified biomarker genes associated with these phenotypes, i.e., worse survival rate, higher metastasis rate, and sex bias. In this exploratory study, we aim to identify potential biomarkers associated with the three phenotypes using integrative analysis of gene expression, methylation and copy number variation datasets. In the results, we identified a set of biomarker genes and linked them into a network signature. The network signature showed better performance in the separation of G3 MB patients into subtypes with a significant difference in terms of the three phenotypes. To identify potentially effective drugs for G3 MBs, a set of drugs with diverse targets were prioritized, which can potentially inhibit the network signature. These drugs or combinations thereof might be effective for G3 treatment.

bioinformatics↗