Biology subjects

Mahmoud, S.

Publications and source records attributed to Mahmoud, S..

6 recordsLinked to original sources

bioRxiv2025

Identification and characterization of a SARS-CoV-2 Mpro G23 deletion ensitrelvir-resistant mutant

Ensitrelvir is an antiviral drug that specifically targets the main protease (Mpro) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been approved for the treatment of coronavirus disease 2019 (COVID-19) due to the conservation of its target protein which is essential in the viral lifecycle. However, SARS-CoV-2 could introduce mutations in the viral proteins to confer resistance to antivirals. Thus, screening for drug-resistant SARS-CoV-2 mutants and elucidating their resistant mechanisms are critical for guiding the selection of effective antiviral therapies. Here, we utilized a luminescent attenuated SARS-CoV-2 ({Delta}3a7b-Nluc WT) to safely identify ensitrelvir drug-resistant mutants (DRM-E) without the need of using virulent forms of SARS-CoV-2. We isolated a DRM-E containing a G23 deletion (G23del) in Mpro with high resistance (>1,000 fold) to ensitrelvir, but not to the other Mpro inhibitor (nirmatrelvir) or to the RNA-dependent RNA polymerase (RdRp) inhibitor remdesivir. The contribution of G23del was confirmed by generating a recombinant luminescent attenuated SARS-CoV-2 containing G23del in the non-structural protein 5 (NSP5) gene ({Delta}3a7b-Nluc G23del). {Delta}3a7b-Nluc G23del exhibited significant resistance to ensitrelvir in both cultured cells an in K18 hACE2 transgenic mice. Binding affinity revealed that G23del mutation substantially altered Mpro binding affinity for ensitrelvir but not nirmatrelvir. In conclusion, our results demonstrate that G23del in Mpro can confer high resistance to ensitrelvir. Positively, G23del in Mpro does not render SARS-CoV-2 resistant to nirmatrelvir or remdesivir, suggesting the feasibility of treating infections with SARS-CoV-2 containing G23del with these other approved antivirals. SIGNIFICANCEThe clinical use of SARS-CoV-2 antiviral drugs is increasingly challenged by the emergence of drug-resistant mutants. Thus, there is a pressing need to identify and characterize antiviral escape SARS-CoV-2 variants, particularly for FDA-approved antivirals. Our study addresses this by employing a luminescent attenuated virus platform ({Delta}3a7b-Nluc WT) to safely identify and characterize resistance mutations without the concern of using virulent forms of SARS-CoV-2. Using this safe approach, we have identified a G23 deletion (G23del) in SARS-CoV-2 Mpro, which mediates resistance to ensitrelvir in vitro and in vivo. Importantly, while G23del was able to confer more than 1,000-fold increased resistance to ensitrelvir, SARS-CoV-2 containing G23del remained sensitive to other Mpro (nirmatrelvir) and RdRp (remdesivir) inhibitors. Altogether, this study demonstrates the feasibility of using {Delta}3a7b-Nluc to safely identify and characterize drug resistant viruses without the biosafety concern of using virulent SARS-CoV-2 and advance the design of next-generation antiviral drugs.

microbiology↗

bioRxiv2023

Tenascin-C activation of lung fibroblasts in a 3D synthetic lung extracellular matrix mimic

The lung extracellular matrix (ECM) maintains the structural integrity of the tissue and regulates the phenotype and functions of resident fibroblasts. Lung-metastatic breast cancer alters these cell-ECM interactions, promoting fibroblast activation. There is a need for bio-instructive ECM models that contain the ECM composition and biomechanics of the lung to study these cell-matrix interactions in vitro. Here, we developed a synthetic, bioactive hydrogel that mimics the native lung modulus, and includes a representative distribution of the most abundant ECM peptide motifs responsible for integrin binding and matrix metalloproteinase (MMP)-mediated degradation in the lung, which promotes quiescence of human lung fibroblasts (HLFs). Stimulation with transforming growth factor {beta}1 (TGF-{beta}1), metastatic breast cancer conditioned media (CM), or tenascin-C activated these hydrogel-encapsulated HLFs in a manner reflective of their native in vivo responses. We propose this lung hydrogel platform as a tunable, synthetic approach to study the independent and combinatorial effects of ECM in regulating fibroblast quiescence and activation.

bioengineering↗

bioRxiv2022

Using Transfer Learning for Automated Microbleed Segmentation

IntroductionCerebral microbleeds are small perivascular haemorrhages that can occur in both grey and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology, and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to inter- and intra-rater variabiltiy. Automated techniques so far have shown high accuracy at a neighborhood ("patch") level at the expense of a high number of false positives voxel-wise lesions. We aimed to develop an automated, more precise microbleeds segmentation tool able to use standardizable MRI contrasts. MethodsWe first trained a ResNet50 network on another MRI segmentations task (cerberospinal fluid versus background segmentation) using T1-weighted, T2-weighted, and T2* MRI. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentations of microbleeds from 78 participants were used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, as well as data augmentation on the performance of the Microbleed ResNet50 network. ResultsThe proposed method achieved a high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57%, 99.16%, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1%, 20.1%, and 0.28 for cortical GM; 100%, 100%, and 1.0 for deep GM; and 91.1%, 44.3%, and 0.58 for WM, respectively. DiscussionThe proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity.

neuroscience↗

bioRxiv2021

White Matter Hyperintensity Distribution Differences in Aging and Neurodegenerative Disease Cohorts

IntroductionWhite matter hyperintensities (WMHs) are common magnetic resonance imaging (MRI) findings in the aging population in general, as well as in patients with neurodegenerative diseases. They are known to exacerbate the cognitive deficits and worsen the clinical outcomes in the patients. However, it is not well-understood whether there are disease-specific differences in prevalence and distribution of WMHs in different neurodegenerative disorders. MethodsData included 976 participants with cross-sectional T1-weighted and fluid attenuated inversion recovery (FLAIR) MRIs from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort of the Canadian Consortium on Neurodegeneration in Aging (CCNA) with eleven distinct diagnostic groups: cognitively intact elderly (CIE), subjective cognitive impairment (SCI), mild cognitive impairment (MCI), vascular MCI (V-MCI), Alzheimers dementia (AD), vascular AD (V-AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), cognitively intact elderly with Parkinsons disease (PD-CIE), cognitively impaired Parkinsons disease (PD-CI), and mixed dementias. WMHs were segmented using a previously validated automated technique. WMH volumes in each lobe and hemisphere were compared against matched CIE individuals, as well as each other, and between men and women. ResultsAll cognitively impaired diagnostic groups had significantly greater overall WMH volumes than the CIE group. Vascular groups (i.e. V-MCI, V-AD, and mixed dementia) had significantly greater WMH volumes than all other groups, except for FTD, which also had significantly greater WMH volumes than all non-vascular groups. Women tended to have lower WMH burden than men in most groups and regions, controlling for age. The left frontal lobe tended to have a lower WMH burden than the right in all groups. In contrast, the right occipital lobe tended to have greater WMH loads than the left. ConclusionsThere were distinct differences in WMH prevalence and distribution across diagnostic groups, sexes, and in terms of asymmetry. WMH burden was significantly greater in all neurodegenerative dementia groups, likely encompassing areas exclusively impacted by neurodegeneration as well as areas related to cerebrovascular disease pathology.

neuroscience↗

bioRxiv2021

Diffusely abnormal white matter converts to T2 lesion volume in the absence of acute inflammation

Diffusely abnormal white matter (DAWM), characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive MS (SPMS). However, little is known about changes of DAWM over time and their relation to focal white matter lesions (FWML). The objectives of this work were: 1) To characterize the longitudinal evolution of FWML, DAWM, and DAWM that transforms into FWML, and 2) To determine whether gadolinium enhancement, known to be associated with the development of new FWML, is also related to DAWM voxels that transform into FWML. Our data included 4220 MRI scans of 689 SPMS participants, followed for 156 weeks and 2677 scans of 686 RRMS participants, followed for 96 weeks. FWML and DAWM were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, DAWM voxels at each visit that transformed into FWML on the last MRI scan as well as their overlap with gadolinium enhancing lesion masks were identified. Our results showed that the average yearly rate of conversion of DAWM-to-FWML was 1.27cc for SPMS and 0.80cc for RRMS. FWML in SPMS participants significantly increased (t=3.9; p=0.0001) while DAWM significantly decreased (t=-4.3 p<0.0001) and the ratio FWML:DAWM increased (t=12.7; p<0.00001). RRMS participants also showed an increase in the FWML:DAWM Ratio (t=6.9; p<0.00001) but without a significant change of the individual volumes. Gadolinium enhancement was associated with 7.3% and 18.7% of focal New T2 lesion formation in the infrequent scans of the RRMS and SPMS cohorts, respectively. In comparison, only 0.1% and 0.0% of DAWM-to-FWML voxels overlapped with gadolinium enhancement. We conclude that DAWM transforms into FWML over time, in both RRMS and SPMS. DAWM appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

neuroscience↗

bioRxiv2020

PhyloBrain atlas: a cortical brain MRI atlas following a phylogenetic approach

Cortical atlases constitute a consistent division of the human cortex into areas that have common structural as well as meaningful and distinctive functional characteristics. The most widely used atlases follow the cytoarchitectonic and myeloarchitectonic characteristics of the cortex and have been combined to the standard anatomical nomenclature of gyri and sulci. More recently, common functional features depicted by resting state functional MRI have also guided the division of the cortical brain in functional regions of interest. However, to date, there are no atlases that divide the cortex considering the common evolutionary changes experienced by the mammalian cortex. Hence, the present study proposes the division of cortical areas into five main regions of interest (ROIs) following a phylogenetic approach: 1- archicortex, 2- paleocortex, 3- peri-archicortex, 4- proisocortex, 5-neocortex, and twelve neocortical sub-ROIs: 5.1.temporopolar, 5.2.post-central, 5.3.pre-central, 5.4.pericalcarine, 5.5.superior temporal, 5.6.middle temporal, 5.7.precuneus, 5.8.insular, 5.9.inferior parietal, 5.10.caudal anterior, 5.11.posterior cingulate, and 5.12.lingual gyrus. The segmentations were done using the T1-weighted MNI-ICBM152 non-linear 6th generation symmetric average brain MRI model.

neuroscience↗