Biology subjects

Saadawi, A.

Publications and source records attributed to Saadawi, A..

2 recordsLinked to original sources

bioRxiv2025

Transcriptomic module fingerprint reveals heterogeneity of whole blood transcriptome in type 1 diabetic patients

BackgroundType 1 diabetes (T1D) is a complex autoimmune disease resulting from {beta}-cell destruction in the pancreas. Yet, no gene signature derived from whole blood samples has been established to differentiate T1D patients from healthy donors, likely because of the high heterogeneity of the underlying pathophysiological mechanisms. MethodsWe analysed whole blood transcriptomic profiles from 39 patients and 43 healthy donors, collected as part of our observational clinical trial, using a multi-step multivariate statistical analysis. This approach combined classical differential analysis, random forest and support vector machine classifications, gene set functional enrichment analysis to construct the most stable and reliable gene signature. ResultsClassical differential analysis did not separate clearly samples into healthy and T1D clusters, but rather spread samples into three clusters. On the contrary, we show that our approach, which combined molecular signatures independently constructed, adds robustness to the analysis without compromising the specificity. This efficiency was demonstrated by the clear separation of the samples according to their diagnosis group. Also, the functional annotation of the gene modules that we obtained was more associated with T1D-related pathways compared to the classical statistical analysis. ImpactsThese results emphasize that single differential analyses are not able to capture immune continuums involved in such a complex pathophysiological process. We hypothesize that T1D patients can have different molecular pathways involved in their pathology or/and can display unsynchronized -omics profiles. These findings call for further investigations to identify the molecular pathways involved in T1D patients, and for revising the nosology of autoimmune diseases.

bioinformatics↗

bioRxiv2024

Investigating Polyreactivity of CD4+ T Cells to the Intestinal Microbiota

The symbiotic relationship between host and microbiota plays a pivotal role in training and development of the hosts innate and adaptive immune systems. Antigen-specific recognition of microbiota by T cells enforces tolerance at homeostasis. Conversely, dysbiosis--characterized by alterations in microbiota diversity and abundance--leads to imbalanced T cell responses and triggering of inflammatory and autoimmune diseases. Despite their significance, the identities of immunogenic microbial antigens are still largely enigmatic. Here, we leveraged an in-house developed antigen screening platform, the MCR system 1, to delineate CD4+ T cell reactivity against Akkermansia muciniphila (AKK) and Bacteroides thetaiotaomicron (BT), --two prominent members of the gut microbiota. T-cell hybridomas reactive to AKK and BT bacteria showed polyreactivity to select microbiota-derived peptides in MCR co-cultures. We discovered 13 novel antigenic epitopes from AKK and 14 from BT. Steady-state T cells recognized these epitopes in an MHC-restricted fashion. Ex vivo stimulation of peptide-specific T cells revealed induction of type 1 and type 17 immune responses, albeit with non-overlapping specificities, contrary to MCR system results. Our findings further demonstrated that most identified epitopes are broadly conserved within the given phylum and originate from both membrane and intracellular proteins. Our work showcases the potential of the MCR system for identifying immunogenic microbial epitopes, providing a valuable resource. Additionally, it indicates the existence of mucosal T cells with a tropism toward broadly conserved bacterial epitopes. Overall, our study forms the basis for decoding antigen specificity in immune system-bacterial interactions, with applications in understanding both microbiome and pathogenic bacterial immunity.

immunology↗