Biology subjects

Brito, A. D.

Publications and source records attributed to Brito, A. D..

5 recordsLinked to original sources

bioRxiv2025

ReScale4DL: Balancing Pixel and Contextual Information for Enhanced Bioimage Segmentation

Deep learning has established itself as the state-of-the-art approach for segmentation in bioimage analysis. However, these powerful algorithms present an intriguing paradox regarding image resolution: contrary to intuition, lower-resolution images can yield superior performance for specific image analysis carried out by deep learning. This phenomenon is particularly significant in microscopy imaging, where high-resolution acquisitions come with substantial costs in throughput, data storage requirements, and potential photodamage to specimens. Through systematic experimentation, we evaluate how varying image resolution impacts deep learning performance in cellular image segmentation tasks. We trained popular architectures on datasets downsampled to 6-50% of their original resolution, mimicking acquisitions at lower image magnification, and compared their performance against models trained on native-resolution images. Our results show that segmentation accuracy either improves (by up to 25% of mean Intersection over Union (IoU)) or experiences only minimal degradation (< 5% of mean IoU) when using images downsampled by up to a factor of 4 (25% of the original resolution). This downsampling proportionally increases information throughput while reducing data storage requirements and inference time. With these findings, we contribute systematic guidelines to deep learning practitioners in creating efficient experimental pipelines for image-driven discoveries. This approach improves the sustainability and cost-effectiveness of bioimaging studies by reducing data and computing needs while optimising microscopy techniques.

biophysics↗

bioRxiv2025

Chromosome segregation dynamics during the cell cycle of Staphylococcus aureus

Research on chromosome organization and cell cycle progression in spherical bacteria, particularly Staphylococcus aureus, remains limited and fragmented. In this study, we established a working model to investigate chromosome dynamics in S. aureus using a Fluorescent Repressor-Operator System (FROS), which enabled precise localization of specific chromosomal loci. This approach revealed that the S. aureus cell cycle and chromosome replication cycle are not coupled, with cells exhibiting two segregated origins of replication at the start of the cell cycle. The chromosome has a specific origin-terminus-origin conformation, with origins localizing near the membrane, towards the tip of each hemisphere, or the "cell poles". We further used this system to assess the role of various proteins with a role in S. aureus chromosome biology, focusing on the ParB-parS and SMC-ScpAB systems. Our results demonstrate that ParB binds five parS chromosomal sequences and the resulting complexes influence chromosome conformation, but play a minor role in chromosome compaction and segregation. In contrast, the SMC-ScpAB complex plays a key role in S. aureus chromosome biology, contributing to chromosome compaction, segregation and spatial organization. Additionally, we systematically assessed and compared the impact of proteins linking chromosome segregation to cell division--Noc, FtsK, SpoIIIE and XerC--on origin and terminus number and positioning. This work provides a comprehensive study of the factors governing chromosome dynamics and organization in S. aureus, contributing to our knowledge on chromosome biology of spherical bacteria.

microbiology↗

bioRxiv2023

NanoPyx: super-fast bioimage analysis powered by adaptive machine learning

To overcome the challenges posed by large and complex microscopy datasets, we have developed NanoPyx, an adaptive bioimage analysis framework designed for high-speed processing. At the core of NanoPyx is the Liquid Engine, an agent-based machine-learning system that predicts acceleration strategies for image analysis tasks. Unlike traditional single-algorithm methods, the Liquid Engine generates multiple CPU and GPU code variations using a meta-programming system, creating a competitive environment where different algorithms are benchmarked against each other to achieve optimal performance under the user"s computational environment. In initial experiments focusing on super-resolution analysis methods, the Liquid Engine demonstrated an over 10-fold computational speed improvement by accurately predicting the ideal scenarios to switch between algorithmic implementations. NanoPyx is accessible to users through a Python library, code-free Jupyter notebooks, and a napari plugin, making it suitable for individuals regardless of their coding proficiency. Furthermore, the optimisation principles embodied by the Liquid Engine have broader implications, extending their applicability to various high-performance computing fields.

bioinformatics↗

bioRxiv2023

Processive movement of Staphylococcus aureus essential septal peptidoglycan synthases is independent of FtsZ treadmilling and drives cell constriction

Bacterial cell division is mediated by the tubulin-homolog FtsZ, which recruits peptidoglycan (PG) synthesis enzymes to the division site. Septal PG synthases promote inward growth of the division septum, but the mechanisms governing the spatiotemporal regulation of these enzymes are poorly understood. Recent studies on various organisms have proposed different models for the relationship between the movement and activity of septum-specific PG synthases and FtsZ treadmilling. Here, we studied the movement dynamics of conserved cell division proteins relative to the rates of septum constriction and FtsZ treadmilling in the Gram-positive pathogen Staphylococcus aureus. The septal PG synthesis enzyme complex FtsW/PBP1 and its putative activator protein, DivIB, moved processively, around the division site, with the same velocity. Impairing FtsZ treadmilling did not affect FtsW and DivIB velocities or septum constriction rates. Contrarily, inhibition of PG synthesis slowed down or completely stopped both septum constriction and the directional movement of FtsW/PBP1 and DivIB. Our findings support a model for S. aureus in which a single population of processively moving FtsW/PBP1 remains associated with DivIB to drive cell constriction independently of treadmilling FtsZ filaments.

microbiology↗

bioRxiv2023

The role of GpsB in cell morphogenesis of Staphylococcus aureus

For decades, cells of the gram-positive bacterial pathogen Staphylococcus aureus were thought to lack a dedicated elongation machinery. However, S. aureus cells were recently shown to elongate before division, in a process that requires a SEDS (Shape Elongation Division and Sporulation) / PBP (Penicillin Binding Protein) pair for peptidoglycan synthesis, consisting of the glycosyltransferase RodA and the transpeptidase PBP3. In ovococci and rod-shaped bacteria the elongation machinery, known as elongasome, is composed of various proteins besides a dedicated SEDS/PBP pair. To identify proteins involved in the elongation of S. aureus, we screened the Nebraska Transposon Mutant Library, which contains transposon mutants in virtually all non-essential staphylococcal genes, for mutants with modified cell shape. We confirmed the roles of RodA/PBP3 in S. aureus elongation and identified GpsB, SsaA, and RodZ as additional proteins involved in this process. The gpsB mutant showed the strongest phenotype, mediated by the partial delocalization from the division septum of PBP2, the only bifunctional PBP in S. aureus, with both glycosyltransferase and transpeptidase activity, and of the PBP4 transpeptidase. Increased levels of these PBPs at the cell periphery result in higher levels of peptidoglycan insertion throughout the entire cell, overriding the RodA/PBP3-mediated peptidoglycan synthesis at the outer edge of the septum, which leads to cell elongation. As a consequence, in the absence of GpsB, S. aureus cells become more spherical.

microbiology↗