Biology subjects

Ogbonna, E. C.

Publications and source records attributed to Ogbonna, E. C..

5 recordsLinked to original sources

bioRxiv2026

Phosphoarginine modulates oligomerization and repressor activity of mycobacterial ClpC2

Phosphoarginine (pArg) modifications direct proteins for proteolytic destruction by ClpC1P1P2, an essential mycobacterial protease that has emerged as a promising antibacterial drug target against Mycobacterium tuberculosis. The broader regulatory landscape surrounding pArg is poorly understood. Here, we establish a mechanistic connection between pArg binding and the activity of ClpC2, a non-proteolytic transcriptional repressor with homology to the ClpC1 N-terminal domain. Biophysical studies reveal that ClpC2 forms concentration-dependent higher-order oligomers that bind cooperatively to operator sequences in the clpC2 promoter. A high-resolution crystal structure of the Streptomyces thermoviolaceus ClpC2 C-terminal domain reveals a conserved dimerization interface mediated by a C-terminal helix, which is sterically disrupted by pArg binding. Consequently, we find that binding of pArg, as well as some ClpC1-targeting antibiotics, disrupts ClpC2 oligomerization, dissociates ClpC2 from its operator DNA, and relieves transcriptional repression in vitro. Moreover, comparative analysis of clpC2 promoters with single versus dual operator sites predicts differences in regulatory sensitivity across mycobacterial species. Together, these findings establish ClpC2 as a pArg-responsive sensor capable of mechanistically linking elevated pArg levels to downstream transcriptional regulation.

biochemistry↗

bioRxiv2026

Modeling development of tertiary lymphoid structures in pulmonary tuberculosis by 3D profiling and trajectory analysis

Tertiary lymphoid structures (TLSs) are sites of immune organization in peripheral tissues that arise from chronic inflammation. They play important roles in infection control and cancer but the mechanisms controlling their formation remain only partly understood. Here, we combine high-plex imaging, serial-section 3D reconstruction, and optimal transport trajectory modeling to reconstruct TLSs in human lungs infected with Mycobacterium tuberculosis. We find that the extended and irregular shape of TLSs is poorly captured by 2D histopathology or spatial profiling, making assessment of developmental stage (early, primary, or secondary) error prone. In contrast, modeling TLS development in 3D using optimal transport reveals two trajectories that differ in the timing and coordination of follicular dendritic cell association, germinal center consolidation, and position within the tissue. These findings highlight the value of volumetric analysis in understanding immune organization and provide new insights into TLS biology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/725201v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@11b4daorg.highwire.dtl.DTLVardef@7871feorg.highwire.dtl.DTLVardef@1840c2dorg.highwire.dtl.DTLVardef@3b6028_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI3D reconstruction of TB-infected lung reveals TLSs to be extended, heterogeneous structures that are frequently misclassified in 2D C_LIO_LITLS maturation follows continuous trajectories rather than discrete histological stages C_LIO_LIOptimal transport modeling identifies distinct maturation paths with divergent follicular dynamics C_LIO_LIGerminal center organization and Tfh-FDC interactions emerge along maturation trajectories C_LIO_LITLS maturation states are shaped by spatially localized microenvironmental niches. C_LI

immunology↗

bioRxiv2026

Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders

Light microscopy of tissue sections stained with hematoxylin and eosin (H&E) has been the foundation of histopathology for over 150 years and remains essential for diagnosis and research. The development of high-plex spatial profiling approaches able to measure protein and RNA expression at single-cell resolution augments but does not replace H&E imaging, even in research. Computational pathology (CPath) models based on deep learning promise to further increase the value of H&E imaging but interpreting these models in biological terms remains challenging. As a result, they are not widely used in spatial profiling studies. Here we describe a human-in-the-loop computational framework that leverages CPath foundation models (FMs) and sparse autoencoders (SAEs) to decompose FM embeddings and automatically identify diverse, human-interpretable histopathology features in H&E images. When FM-SAE modeling was applied to pulmonary diseases such as tuberculosis and lung cancer, human-machine interaction augmented and accelerated expert interpretation. Moreover, the resulting annotations provide a morphology-aware approach to integrating 2D and 3D mesoscale tissue architectures with molecular spatial profiling.

bioinformatics↗

bioRxiv2022

Interactome analysis identifies MSMEI_3879 as a substrate of Mycolicibacterium smegmatis ClpC1

The prevalence of drug resistant Mycobacterium tuberculosis infections has prompted extensive efforts to exploit new mycobacterial drug targets. ClpC1, the unfoldase component of the essential ClpC1P1P2 protease, has emerged as one particularly promising antibacterial target. However, efforts to identify and characterize ClpC1-targeting compounds are constrained by our limited knowledge of Clp protease function and regulation. To expand our understanding of ClpC1 physiology, we employed a co-immunoprecipitation and mass spectrometry workflow to identify proteins that interact with ClpC1 in Mycolicibacterium smegmatis, a relative of M. tuberculosis. We identify a diverse panel of interaction partners, many of which make co-immunoprecipitate with both the regulatory N-terminal domain and the ATPase core of ClpC1. Notably, our interactome analysis identifies MSMEI_3879, a truncated gene product unique to M. smegmatis, as a novel proteolytic substrate. Degradation of MSMEI_3879 by ClpC1P1P2 in vitro requires an exposed N-terminal sequence, reinforcing the idea that ClpC1 selectively recognizes disordered motifs. Fluorescent substrates incorporating MSMEI_3879 may be useful in screening for novel ClpC1-targeting antibiotics, to help address the challenge of M. tuberculosis drug resistance.

biochemistry↗

bioRxiv2021

Identification of diverse targets of arginine phosphorylation in Mycolicibacterium smegmatis by shotgun proteomics

Tuberculosis is a leading cause of worldwide infectious mortality. The prevalence of multidrug-resistant Mycobacterium tuberculosis (Mtb) infections drives an urgent need to exploit new drug targets. One such target is the ATP-dependent protease ClpC1P1P2, which is strictly essential for viability. However, few proteolytic substrates of mycobacterial ClpC1P1P2 have been identified to date. Recent studies in Bacillus subtilis have shown that the orthologous ClpCP protease recognizes proteolytic substrates bearing post-translational arginine phosphorylation. While several lines of evidence suggest that ClpC1P1P2 is similarly capable of recognizing phosphoarginine-bearing proteins, the existence of phosphoarginine modifications in mycobacteria has remained in question. Here, we confirm the presence of post-translational phosphoarginine modifications in Mycolicibacterium smegmatis (Msm), a nonpathogenic surrogate of Mtb. Using a phosphopeptide enrichment workflow coupled with shotgun phosphoproteomics, we identify arginine phosphosites on several functionally diverse targets within the Msm proteome. Interestingly, phosphoarginine modifications are not upregulated by heat stress, suggesting divergent roles in mycobacteria and Bacillus. Our findings provide new evidence supporting the existence of phosphoarginine-mediated proteolysis by ClpC1P1P2 in mycobacteria and other actinobacterial species.

microbiology↗