Biology subjects

Rigor, P.

Publications and source records attributed to Rigor, P..

3 recordsLinked to original sources

bioRxiv2026

Cyanophage CP12 Rewires Host Carbon Regulation through Interface Remodeling and Redox Buffering

Picocyanobacteria drive ocean carbon fixation, and cyanophages reshape host metabolism during infection. In cyanobacteria, the intrinsically disorder Calvin cycle protein 12 (CP12) assembles glyceraldehyde-3-phosphate dehydrogenase (GAP2) and phosphoribulokinase (PRK) into the inhibitory dark complex, yet how phage CP12 homologs modulate redox-sensitive partners remains unclear. Here, we examined viral CP12 across sequence, structure, and post-translational modification (PTM) complexities to resolve the mechanistic remodeling of dark-complex assembly and regulation. Protein-family analysis of CP12 homologs across diverse lineages showed that viral CP12 preserves interface-dominated positions while shifting partner-facing chemistry toward charged and geometry-modulating features. Matched molecular dynamics simulations (MD) of Prochlorococcus MED4 and cyanophage P-HM2 showed that phage CP12 preserves assembly while strengthening PRK-facing contacts and reducing GAP2-facing interface burial. MED4 redox proteomics identified coordinated cysteine oxidation across CP12 and GAP2 under light disturbance, guiding MD to explore thiol-PTM states. Conformational divergence increased with PTM load and localized mainly to GAP2 modifications. Thiol PTM at GAP2 imposed the largest CP12 binding-energy cost, which P-HM2 CP12 buffered, yielding smaller comparative binding-energy penalties than host CP12. These findings link sequence-driven chemistry to interface dynamics and redox PTM responsiveness to light, defining phage CP12 as a regulatory mimetic that may retune host carbon regulation during infection.

microbiology↗

bioRxiv2026

ChatGEM: An Agentic Architecture Enabling Interactive Simulation of Genome-Scale Metabolic Models

Genome-scale metabolic models (GEMs) are powerful tools for predicting cellular phenotypes and guiding microbial strain engineering, yet broad adoption remains challenging due to the computational expertise required. To overcome that, we present ChatGEM, an agentic platform that enables interactive GEM simulation through natural language. Built on the multi-agent ADEPT framework, ChatGEM integrates COBRApy within a retrieval-augmented generation (RAG) architecture that coordinates code generation and execution through specialized agents. Benchmarking across three tasks of increasing complexity showed that RAG-enabled code generation improved the mean overall performance score from 2.63 to 4.20 while reducing the execution time significantly starting from routine to complex tasks. Application of ChatGEM using an enzyme-constrained GEM (ecGEM) for four engineered Pseudomonas putida KT2440 strains identified the constitutive strain as the optimal chassis for succinate overproduction using a succinate leakage index - a prediction observed experimentally. Therefore, ChatGEM democratizes metabolic modeling by enabling researchers without computational expertise to perform sophisticated GEM-based analyses through natural language, and, hence, accelerating scientific discovery.

systems biology↗

bioRxiv2026

An LLM-driven pipeline for proteomics-based detection and structural modeling of post-translational modifications

Post-translational modifications (PTMs) on proteins dynamically regulate their functions and subsequently cellular physiology. Significant advances have been made in their detection and modeling: mass spectrometry-based proteomics has become the cornerstone for PTM detection in complex samples, while emerging structure-prediction frameworks enable modeling of PTM-dependent conformational changes. However, the biological significance of many PTMs remains largely unexplored, in part because integrated pipelines that bridge PTM detection with structural modeling remain limited. We present a generative AI-driven pipeline that integrates PTM detection with structural modeling of their effects on protein dynamics and interactions. The pipeline comprises two complementary tools: PTMdiscoverer and PTM-Psi. First, PTMdiscoverer leverages large language models to identify, annotate, and interpret candidate PTMs from open-search proteomics results, addressing limitations of conventional proteomics tools. Next, PTM-Psi models the structural, functional, and dynamic consequences of these spatially aware modifications on protein dynamics. These two components bridge PTM discovery with mechanistic interpretation at the structural level. We demonstrate our pipeline by using cyanobacterial proteomics data to study potential molecular mechanisms of redox-regulated "dark complex" formation in carbon metabolism, advancing our ability to interpret PTM-mediated regulation in microbial systems.

bioinformatics↗