Biology subjects

Sid Ahmed, S.

Publications and source records attributed to Sid Ahmed, S..

3 recordsLinked to original sources

bioRxiv2025

A genetically encoded marker for imaging membranes of Plasmodium

Fluorescence microscopy is a powerful tool to analyze subcellular architecture, and long-term live-cell imaging permits the analysis of the dynamics of intracellular structures. Applying this approach to the membranes of Plasmodium spp., the causative agent of malaria, yielded important insight. Fluorescent labelling of Plasmodiums plasma membrane via membrane-resident proteins has been described, but proteins, which broadly mark internal membranes are currently elusive. Alternatively, general membrane dyes can be employed to study membrane dynamics, however, we find that the membrane dye BODIPY TR Ceramide has adverse effects on cell viability during live-cell imaging. To overcome this limitation, we present FLUMMI (Fixed-and-Live-cell Universal Membrane Marker for Imaging), a 32-amino acid long peptide derived from P. falciparum PCNA1, which targets (fluorescent) protein tags to internal membranes for detection in live or fixed samples. Importantly, FLUMMI enables non-invasive, long-term live-cell imaging of internal membranes without affecting P. falciparum viability and is functional in blood stages of both, the human malaria parasite P. falciparum and the rodent-infecting parasite P. berghei, as well as in P. berghei mosquito stages. FLUMMI is also compatible with advanced techniques such as expansion microscopy. Together, our results establish FLUMMI as a versatile and non-toxic tool for membrane imaging in Plasmodium.

microbiology↗

bioRxiv2023

An Environmental Restriction impairs HIV-1 virion fusion and triggers innate immune recognition

In vivo, HIV-1 replicates within tissue, but how three-dimensional (3D) tissue-like environments influence viral spread and pathogenesis remains largely unknown. We previously identified an Environmental Restriction to cell-free Virus Infectivity (ERVI), imposed by collagen-rich 3D extracellular matrix (ECM), which diminishes HIV-1 particle infectivity. Here we report that ERVI is broadly implemented by various adhesive ECM components assembled into tissue-like 3D scaffolds. This restriction rapidly reduces infectivity within minutes, is saturable, and affects diverse primary HIV-1 strains and virions with distinct viral glycoproteins by impairing their ability to fuse with target cells. Importantly, particles subjected to ERVI also trigger pronounced pro-inflammatory cytokine secretion by monocyte-derived macrophages. Mechanistic analyses reveal that transient contact with collagen fibers induces conformational changes in the viral envelope glycoprotein (Env) and enhance its recognition by toll-like receptor (TLR) 2. This recognition promotes routing of viral particles into TLR8-positive endosomes, amplifying innate immune sensing of viral RNA genomes. ERVI thus acts via a dual mechanism: directly limiting the fusogenicity of cell-free virions and sensitizing them for innate immune detection. These findings highlight the biophysical properties of the ECM as a previously unrecognized, tissue-intrinsic barrier that restricts HIV-1 spread and promotes local inflammation representing a novel, broadly acting arm of antiviral innate immunity.

immunology↗

bioRxiv2022

Inferring cell motility in complex environments with incomplete tracking data

Cell motility has important influence on cell interactions and functionality for various biological aspects. Deciphering these dynamics often relies on live-cell microscopy measurements, which partly have to deal with limitations that could impair a reliable quantification of their motility. Especially given complex environments and tissue structures, limited observation periods, cells moving in and out of focus and impaired calibration of observation axes often lead to loss of cell tracks and insufficient tracking of motility within several dimensions. However, a reliable quantification of cell motility dynamics is essential when aiming at extrapolating the observed dynamics in order to understand cell population dynamics at larger temporal and spatial scales using appropriate simulation environments. To analyze how incomplete observations affect interpretation and parameterization of cell motility, we combined experimental observations with computational models. Studying individual cell dynamics within 3D collagen environments, we found that the gradual loss of cell tracks leads to an underestimation of several motility parameters with the effect dependent on the collagen density. By extending the automated fitting strategy FitMultiCell to account for cell track loss, we show that we are able to retrieve the actual cell dynamics and, thus, to reliably parameterize cell motility from such incomplete data. Applying our approach to the analysis of CD4+ T cells within 3D collagen environments that were infected with HIV-1, we could show that despite a considerable loss of cell tracks, the data still contained sufficient information to compare individual cell motilities by inferring and simulating their dynamics. Thereby, the analysis allowed us to disentangle the effect of HIV-1 infection and collagen density on individual cell motility. Our extended FitMultiCell-approach presented here provides a solution for the elimination of artifacts from cell track data analysis to robustly infer cell motility dynamics.

systems biology↗