Search bioRxiv⌕ Search

Biology subjects

Mousavian, Z.

Publications and source records attributed to Mousavian, Z..

2 recordsLinked to original sources

CD11c+ Memory B Cell Differentiation Across Blood and Tonsil Follows Origin-Specific Routes Revealed by CD24/CD27 Profiling

Atypical B cells (ABCs) are observed across infections, yet their ontogeny and differentiation remain unclear. Using high-dimensional flow cytometry, single-cell transcriptomics, V(D)J sequencing, and functional assays in human malaria and healthy donors, we identified markers of cellular origin while tracking ABC differentiation. Early ABCs express CD11c and arise predominantly from memory B cells. Two intermediate states originate from germinal center-derived and marginal zone-like B cells. Pseudotime and lineage analyses reveal trajectories marked by progressive CD24 and CD27 loss, recapitulated in vitro, defining bona fide differentiation programs. Differentiation culminates in late ABCs lacking CD24, CD27, and CD21, with high CD11c, T-bet, and NKG7, partly overlapping with double-negative 2 cells. Early- and intermediate stages show greater plasma-cell differentiation potential and cytokine production capacity, whereas later stages acquire antigen-presentation transcriptomic signatures and microbial-particle association, defining stage-dependent functions that reconcile conflicting ABC roles. Comparable ABC populations occur in healthy blood and tonsils, with tissue-associated class switching and CD86 expression consistent with recent T-cell interaction. This framework consolidates ABC definitions onto a single differentiation axis and clarifies cellular origins. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/676235v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@140364corg.highwire.dtl.DTLVardef@accbb5org.highwire.dtl.DTLVardef@720dc3org.highwire.dtl.DTLVardef@1e591f3_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

StrongestPath: a Cytoscape application for protein-protein interaction analysis

BackgroundStrongestPath is a Cytoscape 3 application that enables to look for one or more cascades of interactions connecting two single or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, it is able to process them and identify the cascade of interactions having the highest total confidence score. Given a set of proteins, StrongestPath can extract and show the network of interactions among them from the given databases, and expand the network by adding new proteins having the most interactions with highest total confidence to the current proteins. The application can also identify any activation or inhibition regulatory paths between two distinct sets of transcription factors and target genes. This application can be either used with a set of built-in human and mouse PPI or signaling databases, or any user-provided database for some organism. ResultsOur results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in the middle of the pathway by finding the strongest path(s) in the PPI or signaling network. ConclusionEasy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform and providing a user-friendly graphical interface make the StrongestPath easy to use.

systems biology↗