Biology subjects

Petr, J.

Publications and source records attributed to Petr, J..

4 recordsLinked to original sources

bioRxiv2026

Modular Assembly of an Infectious Clone of the Akata strain of EBV using Synthetic Genomics Methods in Yeast

We have used synthetic biology recombination methods in yeast to build herpes simplex virus type-1 (HSV-1) and human cytomegalovirus (HCMV) genomes from multiple fragments. The genomes were built using transformation-associated recombination (TAR) in yeast, by virtue of overlapping sequences between the different fragments. This study demonstrates the successful assembly of the Epstein-Barr virus (EBV) genome. We used as the model genome, the Akata Burkitts lymphoma genome, specifically the BX1 genome which encodes a neomycin selectable marker and a GFP expression cassette in the BXLF1 region. The 171.3 kb genome was first deconstructed into 11 fragments in silico, each having 80 bp overlapping sequence between the fragments. The 11 fragments (TAR 1 to TAR 11) were cloned using TAR in yeast, analyzed by restriction enzyme analyses and Nanopore sequencing to validate the cloned fragment. The EBV genome was built in two stages: TAR fragments 1 to 6 and TAR fragments 7 to 11 were assembled to generate two half-genomes. The whole genome (TAR 1-11) was then assembled by joining TAR 1-6 with TAR 7-11. Complete EBV genomes were examined by PCR assays and restriction enzyme analyses and then transfected into HEK-293 cells to generate virus producer cell lines. The HEK-293 cell clones were tested for virus production following lytic induction using baculovirus transduction of Zta, Rta and glycoprotein B (BALF4). The supernatants from these induced cells were harvested and used to infect Raji cells. This analysis revealed a significant number of cells displaying strong GFP fluorescence indicative of infectious virus. We used this supernatant virus to infect primary B cells and were able to derive lymphoblastoid cell lines (LCL) indicative of the ability of this virus to transform B cells. We tested this method for engineering different mutations. Two mutations were made, one in Zta and the other in the small capsid protein (BFRF3). Mutations were engineered in the TAR plasmid in which the genes reside and after sequence validation, assembled into the TAR 1-6 half genome and then the TAR 1-11 genome, which was used to generate HEK-293 cell clones. For the {Delta}Zta cell lines, we could detect virus in the supernatants only if baculovirus expressing Zta in trans was included, this {Delta}Zta EBV virus could transform B cells. The small capsid protein (BFRF3) decorates the capsid shell and is required for capsid assembly in a self-assembly system. When the HEK-293 cell clones were induced using co-expression of Zta, Rta and gB, no virus was detected in the culture supernatants. However, if we provided BFRF3 in trans using baculovirus expressing this protein, virus was detected in the supernatants. This provides the first report of the essential role of the small capsid protein in EBV-infected cells.

Synthetic Biology↗

bioRxiv2025

Multi-cohort, multi-sequence harmonisation for cerebrovascular brain age

IntroductionHigher brain-predicted age gaps (BAG), based on anatomical brain scans, have been associated with cognitive decline among elderly participants. Adding a cerebrovascular component, in the form of arterial spin labelling (ASL) perfusion MRI, can improve the BAG predictions and potentially increase sensitivity to cardiovascular health, a contributor to brain ageing and cognitive decline. ASL acquisition differences are likely to influence brain age estimations, and data harmonisation becomes indispensable for multi-cohort brain age studies including ASL. In this multi-cohort, multi-sequence study, we investigate harmonisation methods to improve the generalisability of cerebrovascular brain age. MethodsA multi-study dataset of 2608 participants was used, comprising structural T1-weighted (T1w), FLAIR, and ASL 3T MRI data. The single scanner training dataset consisted of 806 healthy participants, age 50{+/-}17, 18-95 years. The testing datasets comprised four cohorts (n=1802, age 67{+/-}8, 37-90 years). Image features included grey and white matter (GM/WM) volumes (T1w), WM hyperintensity volumes and counts (FLAIR), and ASL cerebral blood flow (CBF) and its spatial coefficient of variation (sCoV). Feature harmonisation was performed using NeuroComBat, CovBat, NeuroHarmonize, OPNested ComBat, AutoComBat, and RELIEF. ASL-only and T1w+FLAIR+ASL brain age models were trained using ExtraTrees. Model performance was assessed through the mean absolute error (MAE) and mean BAG. ResultsASL feature differences between cohorts decreased after harmonisation for all methods (p<0.05), mostly for RELIEF. Negative associations between age and GM CBF (b=-0.37, R2=0.13, unharmonised) increased after harmonisation for all methods (b<-0.42, R2>0.12) but weakened for RELIEF (b=-0.28, R2=0.14). In the ASL-only model, MAE improved for all harmonisation methods from 11.1{+/-}7.5 years to less than 8.8{+/-}6.2 years (p<0.001), while BAGs changed from 0.6{+/-}13.4 years to less than -1.03{+/-}7.92 years (p<0.001). For T1w+FLAIR+ASL, MAE (5.9{+/-}4.6 years, unharmonised) increased for all harmonisation methods non-significantly to above 6.0{+/-}4.9 years (p>0.42) and significantly for RELIEF (6.4{+/-}5.2 years, p=0.02), while BAGs non-significantly differed from -1.6{+/-}7.3 years to between -1.3{+/-}4.7 and -2.0{+/-}8.0 years (p>0.82). In general, the ASL-specific parameter harmonisation method AutoComBat performed nominally best. DiscussionHarmonisation of ASL features improves feature consistency between studies and also improves brain age estimations when only ASL features are used. ASL-specific parameter harmonisation methods perform nominally better than basic mean and scale adjustment or latent-factor approaches, suggesting that ASL acquisition parameters should be considered when harmonising ASL data. Although multi-modal brain age estimations were improved less by ASL-only harmonisation, possibly due to weaker associations between age and ASL features compared to T1w features feature importance, studies investigating pathological ASL-feature distributions might still benefit from harmonisation. These findings advocate for ASL-parameter specific harmonisation to explore associations between cardiovascular risk factors, brain ageing, and cognitive decline using multi-cohort ASL and cerebrovascular brain age studies.

neuroscience↗

bioRxiv2022

MRI-based computational model generation for cerebral perfusion simulations in health and ischaemic stroke

Cerebral perfusion models were found to be promising research tools to predict the impact of acute ischaemic stroke and related treatments on cerebral blood flow (CBF) linked to patients functional outcome. To provide insights relevant to clinical trials, perfusion simulations need to become suitable for group-level investigations, but computational studies to date have been limited to a few patient-specific cases. This study set out to overcome issues related to automated parameter inference, that restrict the sample size of perfusion simulations, by integrating neuroimaging data. Seventy-five brain models were generated using measurements from a cohort of 75 healthy elderly individuals to model resting-state CBF distributions. Computational perfusion model geometries were adjusted using healthy reference subjects T1-weighted MRI. Haemodynamic model parameters were determined from CBF measurements corresponding to arterial spin labelling perfusion MRI. Thereafter, perfusion simulations were conducted for 150 acute ischaemic stroke cases by simulating an occlusion and cessation of blood flow in the left and right middle cerebral arteries. The anatomical (geometrical) fitness of the brain models was evaluated by comparing the simulated grey and white matter (GM and WM) volumes to measurements in healthy reference subjects. Statistically significant, strong positive correlations were found in both cases (GM: Pearsons r 0.74, P-value< 0.001; WM: Pearsons r 0.84, P-value< 0.001). Haemodynamic parameter tuning was verified by comparing total volumetric blood flow rate to the brain in reference subjects and simulations resulting in Pearsons r 0.89, and P-value< 0.001. In acute ischaemic stroke cases, the simulated infarct volume using a perfusion-based proxy was 197{+/-}25 ml. Computational results showed excellent agreement with anatomical and haemodynamic literature data corresponding to T1-weighted, T2-weighted, and phase-contrast MRI measurements both in healthy scenarios and in acute ischaemic stroke cases. Simulation results represented solely worst-case stroke scenarios with large infarcts because compensatory mechanisms, e.g. collaterals, were neglected. The established computational brain model generation framework provides a foundation for population-level cerebral perfusion simulations and for in silico clinical stroke trials which could assist in medical device and drug development.

bioengineering↗

bioRxiv2021

The European Prevention of Alzheimer's Dementia (EPAD) MRI Dataset and Processing Workflow

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimers Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features -- i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features -- Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) -- were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.

neuroscience↗