Biology subjects

Souza, R.

Publications and source records attributed to Souza, R..

8 recordsLinked to original sources

bioRxiv2026

Mitochondrion-IMC contact sites are critical for cofactor biosynthesis and egress signaling in Toxoplasma gondii

Toxoplasma gondii is a single-celled parasite belonging to the Apicomplexa phylum. Toxoplasmas single mitochondrion is highly dynamic, changing its morphology as the parasite undergoes egress and invasion. Recently, we have demonstrated that mitochondrial morphology is driven by a protein named Lasso Maintenance Factor 1 (LMF1). This protein interacts with IMC10, a protein present at the parasites inner membrane complex (IMC), mediating a unique membrane contact site between the IMC and mitochondrion. Interestingly, parasites lacking either LMF1 or IMC10 have abnormal mitochondrial morphology, cell division defects, and delayed propagation in tissue culture. Although both components of the tether were identified, the functions of this contact site remain unknown. In this work, we show that {Delta}lmf1 parasites exhibit upregulation of egress signaling and downregulation in folate metabolism and pantothenate biosynthesis. {Delta}lmf1 parasites exhibit increased intracellular calcium levels, leading to greater sensitivity to ionophore-induced egress and microneme secretion. We have confirmed that parasites have decreased levels of tetrahydrofolate and coenzyme A, showing a limitation in cofactor production. Interestingly, the {Delta}lmf1 parasites prefer glutamine instead of glucose as a catabolic substrate. Accordingly, we demonstrate for the first time that proper mitochondrial positioning is crucial for folate and Coenzyme A metabolism as well as egress signaling. IMPORTANCEToxoplasma gondii is the causative agent of Toxoplasmosis, a disease that affects a third of the worlds population. This parasite has a single, highly dynamic mitochondrion. The parasites mitochondrion changes shape depending on environmental conditions (inside or outside the host cell) or on stressors, such as drugs. Our laboratory characterized the proteins involved in regulating mitochondrial dynamics in the parasite, but the functional importance of these mitochondrial changes has not yet been described. Here, we show that the shape of Toxoplasmas mitochondrion is important for the synthesis of key cofactors, such as folates and coenzyme A. We show that mitochondrial shape in this parasite is important for signaling the parasites exit from the host cell, a critical process in its life cycle. These findings review a previously unknown function of a parasite-specific organelle contact site, providing new insights into the importance of mitochondria for these parasites.

microbiology↗

bioRxiv2025

GABA-Edited Magnetic Resonance Spectroscopy Deep Learning Quality Assessment Framework

PurposeMotivated by the need to improve GABA-edited magnetic resonance spectroscopy (MRS) quality, we developed a three-module framework to improve transient averaging based on quality. We hypothesized that training a deep learning (DL) to differentiate spectrum quality could improve transient averaging compared to traditional averaging. MethodsThe transient averaging framework was approached through three modules: (1) a continuous-valued automated quality labeling algorithm using both traditional and recently developed MRS quality metrics, (2) a dual-domain (time and frequency) DL model that learns from these quality labels to assess quality scores for new data, and (3) a transient weighting algorithm informed by DL quality scores. The labeling algorithm was used to produce quality labels focused on retaining GABA peak shape in difference spectra (1) to train the DL model (2). The DL model quality scores were used to assign weights (3) for transient pairs within the final average difference spectrum. Results were compared to an existing software weighting algorithm for transient averaging and traditional transient averaging. ResultsRetaining only GABA-edited transient pairs with quality labels above zero, defined by metrics evaluating peak shapes, resulted in overall better traditional and recently developed mean metric values as well as better visual assessment of GABA and Glx peaks. Applying the trained DL model to in vivo scans, the average difference spectra calculated from the DL quality scores and weighting algorithm resulted in lower fit errors than averaging all transients with equal weights. ConclusionThe proposed framework can optimize transient averaging based on quality for edited-MRS.

bioengineering↗

bioRxiv2024

Placentas from SARS-CoV-2 infection during pregnancy exhibit foci of oxidative stress and DNA damage

ProblemCOVID-19 during pregnancy is linked to increased maternal morbidity and a higher incidence of preterm births, yet the underlying mechanisms remain unclear. Cellular senescence, characterized by the irreversible cessation of cell division, is a critical process in placental function and its dysregulation has been implicated in pregnancy complications like preterm birth. Senescence can be induced by various stressors, including oxidative stress, DNA damage, and viral infections. Method of StudyIn this study, we determined whether COVID-19 had an impact on placental senescence. We examined placentas from women infected with SARS-CoV-2 (n=10 term, 4 preterm) compared to uninfected controls (n=10 term, 3 preterm). The placentas were analyzed for SARS-CoV-2 infection/replication (Spike and Nucleocapsid viral proteins), markers of DNA damage ({gamma}H2AX) and oxidative stress (ROS), and senescence (telomere length; cell cycle regulators, SASP). ResultsWhile no overall differences in cellular senescence markers were observed between the COVID-19 positive and negative groups, we found increased secreted SASP markers and confocal microscopy revealed localized areas of oxidative stress and DNA damage in the placentas from COVID-19 positive cases. ConclusionsThese findings indicate that SARS-CoV-2 infection induces localized placental damage, warranting further investigation into its impact on maternal and perinatal outcomes.

microbiology↗

bioRxiv2024

SMART MRS: A Simulated MEGA-PRESS Artifacts Toolbox for GABA-edited MRS

PurposeTo create a Python-based toolbox to simulate commonly occurring artifacts for single voxel Gamma-Aminobutyric Acid (GABA)-edited Magnetic Resonance Spectroscopy (MRS) data. MethodsThe toolbox was designed to maximize user flexibility and contains artifact, applied, input/output (I/O), and support functions. The artifact functions can produce spurious echoes, eddy currents, nuisance peaks, line broadening, baseline contamination, linear frequency drifts, and frequency and phase shift artifacts. Applied functions combine or apply specific parameter values to produce recognizable effects such as lipid peak and motion contamination. I/O and support functions provide additional functionality to accommodate different kinds of input data (MATLAB FID-A .mat files, nifti-mrs files), which vary by domain (time vs. frequency), collection type (edited vs. non-edited) and scale. ResultsUsers may provide some or all of the required artifact function parameter values which will result in artifacts of different appearances. Visual assessment confirms the resemblance of simulated compared to in vivo produced artifacts. ConclusionOur pip installable Python artifact simulated toolbox SMART_MRS is meant to enhance the diversity and quality of existing simulated edited-MRS data and is complementary to existing MRS simulation software.

bioengineering↗

bioRxiv2023

Advancing GABA-edited MRS Research through a Reconstruction Challenge

PurposeTo create a benchmark for the comparison of machine learning-based Gamma-Aminobutyric Acid (GABA)-edited Magnetic Resonance Spectroscopy (MRS) reconstruction models using one quarter of the transients typically acquired during a complete scan. MethodsThe Edited-MRS reconstruction challenge had three tracks with the purpose of evaluating machine learning models trained to reconstruct simulated (Track 1), homogeneous in vivo (Track 2), and heterogeneous in vivo (Track 3) GABA-edited MRS data. Four quantitative metrics were used to evaluate the results: mean squared error (MSE), signal-to-noise ratio (SNR), linewidth, and a shape score metric that we proposed. Challenge participants were given three months to create, train and submit their models. Challenge organizers provided open access to a baseline U-NET model for initial comparison, as well as simulated data, in vivo data, and tutorials and guides for adding synthetic noise to the simulations. ResultsThe most successful approach for Track 1 simulated data was a covariance matrix convolutional neural network model, while for Track 2 and Track 3 in vivo data, a vision transformer model operating on a spectrogram representation of the data achieved the most success. Deep learning (DL) based reconstructions with reduced transients achieved equivalent or better SNR, linewidth and fit error as conventional reconstructions with the full amount of transients. However, some DL models also showed the ability to optimize the linewidth and SNR values without actually improving overall spectral quality, pointing to the need for more robust metrics. ConclusionThe edited-MRS reconstruction challenge showed that the top performing DL based edited-MRS reconstruction pipelines can obtain with a reduced number of transients equivalent metrics to conventional reconstruction pipelines using the full amount of transients. The proposed metric shape score was positively correlated with challenge track outcome indicating that it is well-suited to evaluate spectral quality.

bioengineering↗

bioRxiv2023

Frequency and Phase Correction of GABA-Edited Magnetic Resonance Spectroscopy using Complex-Valued Convolutional Neural Networks

PurposeTo determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in Convolutional Neural Networks (CNNs) for frequency and phase correction (FPC) of GABA-edited Magnetic Resonance Spectroscopy (MRS) data. MethodsAn ablation study was performed to determine the most effective input (real or complex) and convolution type (real or complex) to predict frequency and phase shifts in GABA-edited MEGA-PRESS data using CNNs. The best CNN model was subsequently compared to two recently proposed deep learning (DL) methods for FPC of GABA-edited MRS. All methods were trained using the same experimental setup and evaluated using GABAs signal-to-noise ratio and linewidth, Choline artifact, and by analyzing the reconstructed final difference spectrum. Statistical significance and effect size were assessed using the Wilcoxon signed rank test and Cohens d respectively. ResultsThe ablation study showed that using complex values for the input represented by real and imaginary channels in our model input tensor, with real (conventional) convolutions was most effective for FPC. For the comparative study, the simulated data test set showed that our CNN model that received complex-valued inputs with real convolutions outperformed models it was compared against with a lower mean absolute error (p<0.05). For the in vivo data test set, our model performed similarly to other DL FPC models. ConclusionOur results indicate that the optimal CNN configuration for GABA-edited MRS FPC uses a complex-valued input and real-valued convolutions. This model outperformed existing DL models on simulated data and performed similarly on in vivo data.

neuroscience↗

bioRxiv2022

Efficacy and Specificity of Melanopsin Reporters for Retinal Ganglion Cells

Intrinsically photosensitive retinal ganglion cells (ipRGCs) are specialized retinal output neurons that mediate behavioral, neuroendocrine, and developmental responses to environmental light. There are diverse molecular strategies for marking ipRGCs, especially in mice, making them among the best characterized retinal ganglion cells. With the development of more sensitive reporters, new subtypes of ipRGCs have emerged. We therefore tested high-sensitivity reporter systems to see whether we could reveal yet more. Substantial confusion remains about which of the available methods, if any, label all and only ipRGCs. Here, we compared many different methods for labeling of ipRGCs, including anti-melanopsin immunofluorescence, Opn4-GFP BAC transgenic mice, and Opn4cre mice crossed with three different Cre-specific reporters (Z/EG; Ai9; and Ai14) or injected with Cre-dependent (DIO) AAV2. We show that Opn4cre mice, when crossed with sensitive Cre-reporter mice, label numerous ganglion cell types that lack intrinsic photosensitivity. Though other methods label ipRGCs specifically, they do not label the entire population of ipRGCs. We conclude that no existing method labels all and only ipRGCs. We assess the appropriateness of each reporter for particular applications and integrate findings across reporters to estimate that the overall abundance of ipRGCs among mouse retinal ganglion cells may approach 11%.

neuroscience↗

bioRxiv2020

GATA4, expressed in Barrett's esophagus and esophageal adenocarcinoma, can block squamous epithelial cell gene expression in human esophageal cells

Metaplasia often involves a change from one cell type to another that was present during organogenesis. The embryonic esophagus is initially lined by columnar cells that are replaced by squamous cells, and metaplasia in Barretts esophagus (BE) involves a change from squamous to columnar cells in the setting of gastroesophageal reflux. Here, we explored the effect of ectopic expression of the essential developmental transcription factor GATA4 on squamous epithelial cell gene expression using human esophageal squamous epithelial cells. We found that GATA4 protein, although absent in mature human esophageal squamous epithelium, was present in BE and esophageal adenocarcinoma (EAC). Moreover, acid and bile induced GATA4 mRNA in esophageal squamous epithelial cells. Ectopic GATA4 expression in esophageal squamous epithelial cells generally compromised squamous cell marker gene expression, although the extent varied between cell lines studied. We observed GATA4 occupancy in the p63, KRT5, and KRT15 gene promoters, suggesting that GATA4 can directly repress expression of typical squamous epithelial cell marker genes. Overall, our data suggest a mechanism whereby GATA4 expression in abnormal esophageal cells, possibly induced by reflux, supports a columnar metaplastic cell identity by repressing expression of key genes required to program stratified squamous epithelial cell identity.

cell biology↗