Biology subjects

Albergante, L.

Publications and source records attributed to Albergante, L..

4 recordsLinked to original sources

bioRxiv2022

Representation and quantification Of Module Activity from omics data with rROMA

The efficiency of analyzing high-throughput data in systems biology has been demonstrated in numerous studies, where molecular data, such as transcriptomics and proteomics, offers great opportunities for understanding the complexity of biological processes. One important aspect of data analysis in systems biology is the shift from a reductionist approach that focuses on individual components to a more integrative perspective that considers the system as a whole, where the emphasis shifted from differential expression of individual genes to determining the activity of gene sets. Here, we present the rROMA software package for fast and accurate computation of the activity of gene sets with coordinated expression. The rROMA package incorporates significant improvements in the calculation algorithm, along with the implementation of several functions for statistical analysis and visualizing results. These additions greatly expand the packages capabilities and offer valuable tools for data analysis and interpretation. It is an open-source package available on github at: www.github.com/sysbio-curie/rROMA. Based on publicly available transcriptomic datasets, we applied rROMA to cystic fibrosis, highlighting biological mechanisms potentially involved in the establishment and progression of the disease and the associated genes. Results indicate that rROMA can detect disease-related active signaling pathways using transcriptomic and proteomic data. The results notably identified a significant mechanism relevant to cystic fibrosis, raised awareness of a possible bias related to cell culture, and uncovered an intriguing gene that warrants further investigation. Contact: loredana.martignetti@curie.fr

systems biology↗

bioRxiv2018

High gene dosage changes transcriptional regulation of genetic structures and contributes to diversity and heterogeneity

Differences in gene dosages between and within species are widely observed. Nevertheless, our understanding of the impacts of gene dosages on transcriptional regulation is far from complete and it is largely ignored in many genetic studies. In this article, we showed that dynamic properties of three genetic structures became significantly different when gene dosages were high and, for self-inhibiting genes, high gene dosages could facilitate monoallelic expression at single cell level and heterogeneity of cell population. This shed lights on potential links between levels of ploidy and phenotypes. In addition, in the context of modern molecular biology, especially synthetic biology, gene dosage needs to be taken into consideration when designing or modifying genetic circuits.

systems biology↗

bioRxiv2018

STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.

genomics↗

bioRxiv2017

Faster Growth With Shorter Antigens Explains A VSG Hierarchy During African Trypanosome Infections: A Feint Attack By Parasites

The parasitic African trypanosome, Trypanosoma brucei, evades the adaptive host immune response by a process of antigenic variation that involves the clonal switching of variant surface glycoproteins (VSGs). The VSGs that periodically come to dominate in vivo display a hierarchy, but how this hierarchy arises is not well-understood. Combining publicly available genetic data with mathematical modelling, we report a VSG-length-dependent hierarchical timing of clonal VSG dominance in a mouse model, revealing an inverse correlation between VSG length and trypanosome growth-rate. Our analysis indicates that, among parasites switching to new VSGs, those expressing shorter VSGs preferentially accumulate to a detectable level that is sufficient to trigger an effective immune response. Subsequent elimination of faster-growing parasites then allows slower parasites with longer VSGs to accumulate. This interaction between the host and parasite is able by itself to explain the temporal distribution of VSGs observed in vivo. Thus, our findings reveal a length-dependent hierarchy that operates during T. brucei infection, representing a feint attack diversion tactic utilised during infection by these persistent parasites to out-maneuver the host immune system.\n\nSignificance StatementThe protozoan parasite Trypanosoma brucei causes devastating and lethal diseases in humans and livestock. This parasite continuously evades the host adaptive immune response by drawing on a library of variant surface proteins but the mechanisms determining the timing of surface protein - host interactions are not understood. We report a simple mechanism, based on differential growth of parasites with surface proteins of different lengths, which can explain the hierarchy of variants over time. This allows parasites to evade host immune responses for extended timeframes using limited cohorts of surface proteins. We liken this strategy to a military feint attack, that enhances the parasites ability to evade the host immune response. A similar mechanism may also operate in other important pathogens.

systems biology↗