Biology subjects

Foo, H.

Publications and source records attributed to Foo, H..

4 recordsLinked to original sources

bioRxiv2026

Structure-Guided Biochemical Design of DNA Tweezers As A Dual Target of the Primary Glioblastoma Biomarkers S100A4 and Midkine

Glioblastoma multiforme (GBM) is among the most aggressive malignant brain tumors originating from glial cells and characterized by severe infiltration into surrounding brain tissue, rendering early detection difficult with current diagnostic imaging methods. S100A4 has been identified as a biomarker protein associated with glioblastoma invasiveness due to its role in cell motility and tumor metastasis. Similarly, midkine (MDK) poses an optimal biomedical target for identifying GBM invasive phenotypes because of its connection to the tumor microenvironment and infiltrative proliferation. Both proteins notably possess a positive charge that interacts electrostatically with the negatively charged phosphate backbone of DNA. It has been established that early molecular detection remains a critical unmet need. This study investigates a promising strategy for GBM diagnosis based on how S100A4 and MDK can selectively bind with DNA tweezer nanostructures. Computationally predicting eight distinct nucleotide sequences yielded three-stranded, hinge-scaffolded tweezer conformations for each candidate. The target protein and DNA structures, derived from AlphaFold, were paired together by molecular docking simulations conducted with HDOCK. Docking analyses evaluated binding affinity, structural complementarity, and conformational stability of the complexes formed. Among the evaluated candidates, DT3_8 computationally established the most biochemically robust interaction with both biomarker proteins. Selectivity is especially important because many S100 proteins share similar electrostatic profiles, yet DT3_8 indicates stronger selectivity for S100A4 and MDK over other S100 family proteins. These findings establish a biomechanical basis for the development of nanoscale DNA biosensors, which suggests the potential for detecting invasive GBM phenotypes, preceding radiographic manifestation and pending experimental validation.

bioinformatics↗

bioRxiv2021

Protist.guru: a comparative transcriptomics database for the protist kingdom

SummaryDuring the last few decades, the study of microbial ecology has been enabled by molecular and genomic data. DNA sequencing has revealed the surprising extent of microbial diversity and how microbial processes run global ecosystems. However, significant gaps in our understanding of the microbial world remain, and one example is that microbial eukaryotes, or protists, are still neglected. To address this gap, we used gene expression data from 15 distinct protist species to create protist.guru: an online database equipped with tools for identifying functional co-expression networks, gene families, and enriched gene clusters. Here, we show how our database can be used to reveal genes involved in essential pathways, such as the synthesis of secondary carotenoids in Haematococcus lacustris. We expect protist.guru to serve as a valuable resource for protistologists, as well as a catalyst for discoveries and new insights into the biological processes of microbial eukaryotes. AvailabilityThe database and co-expression networks are freely available from http://protist.guru/. The expression matrices and sample annotations are found in the supplementary data.

evolutionary biology↗

bioRxiv2021

Age- and sex-related topological organisation of human brain functional networks and their relationship to cognition

BACKGROUNDAge and sex associated with changes in functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 UK Biobank participants (mean=62.83{+/-}7.41 years). METHODSBrain connectivity toolbox was used to derive the graph theory measures that assessed network integration, segregation, and strength. Multiple linear regression was performed the relationship between age, sex, cognition, and network measures. Subsequently, multivariate analysis was done to further examine the joint effect of the network measures on cognitive functions. RESULTSAge was associated with an overall decrease in the effectiveness of network communication (i.e. integration) and loss of functional specialisation (i.e. segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks which were less segregated than in men (FDR adjusted p<.05). Age-related changes were also more apparent in men than women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p[≤].002). This may imply that individual measures may be inadequate to capture much of the variance in neural activity or its output and need further refinement. CONCLUSIONThe complexity of the functional brain organisation may be shaped by an individuals age and sex, which ultimately may influence cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.

neuroscience↗

bioRxiv2020

Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank

This is the first study investigating the genetics of weighted functional brain network graph theory measures from 18,445 participants of the UK Biobank (44-80 years). The eighteen measures studied showed low heritability (mean h2SNP =0.12) and were highly genetically correlated. Genome-wide association studies for these measures observed 14 significant variants associated with strength of somatomotor and limbic networks. These intergenic variants were located near the PAX8 gene on chromosome 2. Gene-based analyses identified five significantly associated genes for five of the network measures, which have been implicated in sleep duration, neuronal differentiation/development, cancer, and susceptibility to neurodegenerative diseases. Genetic correlations with other traits were examined and significant correlations were observed with sleep measures and psychiatric symptoms. Further analysis found that somatomotor network strength was phenotypically associated with sleep duration and insomnia. Single nucleotide polymorphism (SNP) and gene level associations with functional network measures were identified, which may help uncover novel biological pathways relevant to human brain functional network integrity and diseases that affect it.

neuroscience↗