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1. Experimental assessment of AI-based interactome mapping

   https://doi.org/10.1038/s41467-026-70942-x  

   Lambourne, Luke; Yadav, Anupama; Wang, Yang; Desbuleux, Alice; Kim, Dae-Kyum; Laval, Florent; Spirohn-Fitzgerald, Kerstin; Cafarelli, Tiziana; Pons, Carles; Kovács, István A; et al (December 2026, Nature Communications)

   Abstract Genotype-phenotype relationships are mediated through intricate networks of physical and functional interactions among macromolecules. Knowledge of the interactome is vital to understand and model genetics and cellular biology. Recent advances in accurately predicting tertiary protein structures using artificial intelligence (AI) approaches such as AlphaFold¹have revived the vision that the protein-protein interactome might be fully predictable through computational modeling of quaternary structures. Here we present a comprehensive experimental framework to systematically assess the impact of AI-driven interactome predictions for yeast²and human³. We find that the quality of high-confidence predictions is on par with established experimental approaches. However, in proteome-wide screening, the tested AI approaches underperform in the discovery of strictly novel protein-protein interactions (PPIs) compared to experimental reference interactome maps. In particular, the yeast interactome map described here identifies >40-fold more novel PPIs than its AI counterpart. Strikingly, AlphaFold provides structural models for a substantial number of experimentally identified PPIs missed by the virtual screens. Our results suggest that, at this stage, the main contribution of AI predictions is to provide quaternary structure models for experimentally identified PPIs. 

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2. CALCIUM‐DEPENDENT PROTEIN KINASE32 regulates cellulose biosynthesis through post‐translational modification of cellulose synthase

   https://doi.org/10.1111/nph.19106  

   Xin, Xiaoran; Wei, Donghui; Lei, Lei; Zheng, Haiyan; Wallace, Ian S.; Li, Shundai; Gu, Ying (September 2023, New Phytologist)

   Summary Cellulose is an essential component of plant cell walls and an economically important source of food, paper, textiles, and biofuel. Despite its economic and biological significance, the regulation of cellulose biosynthesis is poorly understood. Phosphorylation and dephosphorylation of cellulose synthases (CESAs) were shown to impact the direction and velocity of cellulose synthase complexes (CSCs). However, the protein kinases that phosphorylate CESAs are largely unknown. We conducted research inArabidopsis thalianato reveal protein kinases that phosphorylate CESAs.In this study, we used yeast two‐hybrid, protein biochemistry, genetics, and live‐cell imaging to reveal the role of calcium‐dependent protein kinase32 (CPK32) in the regulation of cellulose biosynthesis inA. thaliana.We identified CPK32 using CESA3 as a bait in a yeast two‐hybrid assay. We showed that CPK32 phosphorylates CESA3 while it interacts with both CESA1 and CESA3. Overexpressing functionally defective CPK32 variant and phospho‐dead mutation of CESA3 led to decreased motility of CSCs and reduced crystalline cellulose content in etiolated seedlings. Deregulation of CPKs impacted the stability of CSCs.We uncovered a new function of CPKs that regulates cellulose biosynthesis and a novel mechanism by which phosphorylation regulates the stability of CSCs. 

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3. Unlocking translational control of specialized metabolism in plants through 5′UTR structure

   https://doi.org/10.1126/sciadv.aeb6806  

   Lin, Makou; Shin, Doosan; Hao, Jie; Jan, Masood; Park, Minkyu; Perez, Veronica; Breuer, Benjamin; Wang, Ying; Kim, Jeongim (May 2026, Science Advances)

   Plant-specialized metabolites are essential for plant fitness and human health, with their biosynthesis pathways tightly regulated at multiple levels. However, the translational regulation of their biosynthesis remains poorly understood. Here, we reveal a 5′ untranslated region (5′UTR)–mediated translational mechanism that controls glucosinolate production inArabidopsis. A forward genetic screen exploring the metabolic interaction between auxin and glucosinolates identified two dominantArabidopsisalleles, each carrying a single-nucleotide substitution located 13–base pair apart within the 5′UTR ofMYB28, a master regulator of aliphatic glucosinolate biosynthesis. These mutations markedly increase MYB28 protein abundance without affecting transcript levels, leading to enhanced glucosinolate production. Mutational profiling of the 5′UTR revealed that alterations in RNA tertiary structure influence translation efficiency, establishing a link between RNA conformation and metabolic output. Our findings uncover a previously uncharacterized layer of posttranscriptional regulation in plant-specialized metabolism and highlight the 5′UTR as a potential target for precision breeding to enhance crop performance and nutritional quality. 

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4. Computed structures of core eukaryotic protein complexes

   https://doi.org/10.1126/science.abm4805  

   Humphreys, Ian R.; Pei, Jimin; Baek, Minkyung; Krishnakumar, Aditya; Anishchenko, Ivan; Ovchinnikov, Sergey; Zhang, Jing; Ness, Travis J.; Banjade, Sudeep; Bagde, Saket R.; et al (December 2021, Science)

   Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning–based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as five subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function. 

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5. Balancing Doses of EL222 and Light Improves Optogenetic Induction of Protein Production in Komagataella phaffii

   https://doi.org/10.1002/bit.29027  

   Hoffman, Shannon M; Espinel‐Ríos, Sebastián; Kwartler, Sarah K; Lalwani, Makoto A; Avalos, José L (May 2025, Biotechnology and Bioengineering)

   ABSTRACT Komagataella phaffii, also known asPichia pastoris, is a powerful host for recombinant protein production, in part due to its exceptionally strong and tightly controlled P_AOX1promoter. MostK. phaffiibioprocesses for recombinant protein production rely on P_AOX1to achieve dynamic control in two‐phase processes. Cells are first grown under conditions that repress P_AOX1(growth phase), followed by methanol‐induced recombinant protein expression (production phase). In this study, we propose a methanol‐free approach for dynamic metabolic control inK. phaffiiusing optogenetics, which can help enhance input tunability and flexibility in process optimization and control. The light‐responsive transcription factor EL222 fromErythrobacter litoralisis used to regulate protein production from the P_C120promoter inK. phaffiiwith blue light. We used two system designs to explore the advantages and disadvantages of coupling or decoupling EL222 integration with that of the gene of interest. We investigate the relationship between EL222 gene copy number and light dosage to improve production efficiency for intracellular and secreted proteins. Experiments in lab‐scale bioreactors demonstrate the feasibility of the outlined optogenetic systems as potential alternatives to conventional methanol‐inducible bioprocesses usingK. phaffii. 

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