protein folding

Evolutionary origins of protein novelty across an entire yeast subphylum

Genes encoding novel protein sequences are a ubiquitous feature of genomes. They fuel molecular and cellular evolutionary innovations and frequently contribute to species-specific characteristics. We are now unravelling the processes by which they originate, including de novo from noncoding sequences and through extreme divergence, yet how much and what types of novel proteins evolve through each process is still unclear Does the mechanism of origination shape the structural and functional potential of the resulting proteins? Here, we conducted a broad computational investigation of genetic and protein novelty at the scale of the entire subphylum of Saccharomycotina yeasts. We detected more than 5,000 robust de novo genes across 332 species and compared them to more than 10,000 novel genes resulting from extreme sequence divergence, revealing two distinct modes of evolution of novelty. A remarkable 40% of de novo proteins are predicted to localize to mitochondria compared to only 15% of divergent, with the latter also being substantially longer and more disordered. A detailed analysis of conservatively predicted tertiary structures of novel proteins shows that "invention" of novel folds can happen through both processes but is more likely to occur de novo. We also illustrate cases of evolutionary "re-invention" of existing protein folds from non-coding sequences. Our work deepens our understanding of the origins and importance of novel proteins opening new directions for further structural and functional characterization.

Multicomplex Integrative Structural Modeling of a Human Histone Deacetylase Interactome

Histone Deacetylase (HDAC) 1 and 2 are key enzymatic components in multiple large chromatin remodeling complexes including NuRD, SIN3, and CoREST. In addition, both HDAC 1 and 2 contain a large intrinsically disordered region (IDR) within their C-terminal domain (CTD). How HDAC1/2 assemble into these complexes and the structure of the CTD IDR remains poorly understood. Here, we used HDAC1/2 to isolate their protein interaction networks from cells and used crosslinking mass spectrometry (XL-MS) coupled with the Integrative Modeling Platform to build structural models of the NuRD, SIN3A, and CoREST complexes. Next, we implemented an AlphaFold-enabled XL-MS constrained modeling approach to investigate how HDAC1 could assemble into these complexes. We show that the CTD IDR of HDAC1 folds into alpha helices in these complexes. Finally, we built a complete integrative structural model of a NuRD subcomplex including the abundant HDAC1:MBD3:MTA1:GATAD2B:RBBP4 subunits, which included 6 IDRs. The approaches used herein are broadly applicable for the study of protein complexes and protein interaction networks that can provide important insights into IDRs.

Funneliformismosseae symbiosis and TiO2 nanoparticles under drought in Melissa officinalis L.: a machine learning modeling approach

Plant-mycorrhizal symbiosis under combined abiotic stress and nanoparticle exposure remains underexplored. The complexity of such multifactorial systems, combined with the labor-intensive nature of physiology study, challenges conventional analytical approaches. Machine learning can contribute to further elucidating relations among physiological variables that traditional methods may miss. This offers new avenues for predicting plant responses under multifactorial stress. The symbiotic interaction of Melissa officinalis with arbuscular mycorrhizal fungus (AMF) under TiO 2 nanoparticle (NP) exposure and drought was assessed. Drought-stressed plants were treated with TiO 2 NP (0, 250, 500 ppm) with or without Funneliformis mosseae inoculation. Twenty machine learning algorithms were applied alongside conventional analyses. SMOGN augmentation was applied to address the limited sample size of the parameters, and imbalance in shoot fresh weight data distribution. Under drought, AMF + 250 ppm TiO 2 NP was most effective, increasing total fresh weight by 21.7%, total chlorophyll by 10.0%, shoot length by 30.2%, and protein content by 14.7%, while reducing malondialdehyde (MDA) by 39.1% compared to the control. The non-AMF plants treated with 250 ppm TiO 2 NP under well-watered conditions showed the highest ascorbate peroxidase activity (∼2-fold). Peroxidase activity increased by 53.0-210.0%, superoxide dismutase (SOD) by 7.6-159.4%, chlorophyll b by up to 37.9%, and the chlorophyll b/a ratio by 14–46% across treatments compared to the control. Bayesian Ridge regression achieved high predictive accuracy for shoot fresh weight (R² = 0.9194), identifying chlorophyll a and b as the most influential predictors. TiO 2 nanoparticles enhanced antioxidant defense, while mycorrhizal symbiosis promoted growth. It is suggested that their synergy contributed to mitigating oxidative stress and sustaining growth under drought. The machine learning approach applied demonstrated the potential utility of the algorithms for plant physiology studies.

Sodium butyrate improves growth, antioxidant capacity and intestinal health in juvenile common carp fed high-plant-protein diets

ENGINEERING 3'-UTR HAIRPIN STRUCTURES TO MODULATE MRNA STABILITY AND RECOMBINANT PROTEIN PRODUCTION IN ESCHERICHIA COLI.

Engineering mRNA stability is a promising yet underexplored approach for improving recombinant protein production in bacterial systems. In this study, we evaluated the effect of synthetic 3'-UTR hairpin structures on mRNA stability and protein yield in Escherichia coli using two SUMO-fusion expression systems. Hairpin elements with defined structural features were introduced downstream of the coding sequence. In all constructs, 3'-UTR hairpins increased mRNA half-life, with stabilization ranging from approximately 2-fold to 3-fold (n = 3 biological replicates). In the SUMO-SARS-CoV-2-derived peptide system, enhanced transcript stability was accompanied by a marked increase in specific cellular fusion-protein content, reaching up to 6.8-fold relative to the control (n = 3). In the SUMO-liraglutide-derived peptide system, mRNA stabilization was also pronounced, and the increase in specific cellular fusion-protein content reached approximately 3-fold (p < 0.001, n = 6). These findings show that 3'-UTR engineering is an effective strategy for modulating mRNA stability in *E. coli*, but the quantitative relationship between transcript persistence and protein accumulation is context-dependent and likely influenced by additional factors, including translation efficiency. Overall, engineering of 3'-terminal RNA structures provides a practical tool for post-transcriptional tuning of recombinant expression systems.

Principles of Co-Transcriptional Ribosome Assembly Nucleation and Quality Control

The ribosome is a universally conserved macromolecular machine responsible for protein synthesis across all domains of life. It is composed of two subunits, the small ribosomal subunit (SSU) and the large ribosomal subunit (LSU), which come together during translation to form the functional ribosome. In Saccharomyces cerevisiae, the mature SSU consists of the 18𝑆 ribosomal RNA (rRNA) and 33 ribosomal proteins, while the LSU contains the 5𝑆, 5.8𝑆, and 25𝑆 rRNAs alongside 46 different ribosomal proteins. Crucially, the key functional centers of the ribosome are composed of rRNA and are distributed throughout both subunits. This mechanistic dependence on the rRNA structure emphasizes the importance of its correct folding during biogenesis. Ribosome assembly is a highly regulated, hierarchical process that begins with the transcription of the precursor rRNA (pre-rRNA) in the nucleolus before transitioning through the nucleoplasm and cytoplasm, where mature ribosomes enter the translation pool. The process requires the coordinated action of over 200 assembly factors that cleave, modify, and remodel the pre-rRNA transcript, guiding its folding. While the last decade has seen significant advances in our understanding of the post- transcriptional maturation of the LSU, the molecular transitions governing its co-transcriptional biogenesis remain poorly defined. The research presented in my doctoral work elucidates the earliest stages of co-transcriptional LSU assembly, beginning with the stabilization of the 5′ end of the pre-rRNA transcript. Through a combination of biochemical and structural biology methods, I isolated and structurally characterized a series of novel co-transcriptional LSU assembly intermediates that reveal the stepwise maturation of the pre-ribosomal particle. Characterization of the Pwp1 RNP, the smallest known LSU assembly intermediate, reveals the function of Pwp1 as a structural scaffold that autonomously nucleates the assembly of the 5′ end of the LSU pre-rRNA (Chapter 2). This particle subsequently undergoes modular expansion through the installation of the Internal Transcribed Spacer 2 (ITS2) and the Nop12-mediated docking of premature 5.8𝑆 rRNA (Chapter 3). The following intermediate, the Noc1–Noc2 RNP, characterized by Zahra A. Sanghai, captures the independent folding of another major rRNA module (Domain II) (Chapter 4). The molecular logic underpinning these transitions is further examined through rRNA engineering and biochemical experiments described in Chapter 5, leading to a revised model of co-transcriptional LSU assembly (Chapter 6). Together, these findings offer unprecedented insight into the molecular logic of early co- transcriptional LSU assembly, describing a series of molecular checkpoints used to interrogate the correct folding of pre-rRNA modules. The intermediates and regulatory principles characterized in this work establish a foundation for future structural and functional studies of the early co- transcriptional LSU assembly pathway.

Identification of genetic determinants that promote biofilm growth under heterotrophic conditions in Cupriavidus necator using transposon enrichment

: Cupriavidus necator is a metabolically versatile β-proteobacterium of growing interest for auto- and heterotrophic bioprocesses, yet the genetic determinants governing its biofilm formation remain largely uncharacterized, particularly under process-relevant heterotrophic conditions. Here, we applied a forward-genetics transposon-enrichment approach to identify loci which promote surface-associated growth. A high-density mini-Tn 5 mutant library (26,185 insertion clones, exceeding the >17,000 required for genome-wide coverage) was cultivated as a biofilm in a microfluidic flow-cell system on fructose for 168 h, and the surface-associated community was characterized by deep sequencing. Twelve genes showed significantly elevated insertion frequencies, several with documented links to biofilm formation in other bacteria, including the ferrous-iron uptake system ( feoA / feoB ), galU , and a GSDEF/EAL dual-domain protein. The gene B2043 (E6A55_RS29530), encoding this c-di-GMP-metabolizing protein, was selected for validation by markerless deletion. Under static conditions, the ΔB2043 mutant showed a 1.69 ± 0.06-fold increase in biofilm-associated biomass (p = 5.16 × 10 -15 ). Under flow-through conditions, the mutant attached faster, entered exponential growth ∼10 h earlier, reached its biovolume plateau ∼16 h earlier than the wild-type, and formed distinct tower-like structures. These results identify B2043 as a negative regulator of biofilm formation acting predominantly during attachment, provide the first experimental evidence for c-di-GMP-dependent biofilm regulation in C. necator H16, and establish a functional-genomics framework — together with eleven further candidate loci — for engineering productive biofilms in this organism.

Fractal Compact Manifold Theory Core Mechanics: Multifractal Unification of Quantum Mechanics, Gravity, and Consciousness

Abstract This sub-paper, "Fractal Compact Manifold Theory Core Mechanics" serves as a concise, standalone distillation of FCMT's foundational elements, emphasizing the atemporal symmetry breaking, field emergence, Lagrangian formulation, projection operator, and foliation map. By focusing solely on these core mechanics—without delving into the full theory's extensions like general relativity recovery, timeless quantum applications, gauge structures, or empirical predictions—it aims to provide a more accessible entry point, reducing the reading commitment from the comprehensive 200-page main document to a targeted exploration of the theory's essence. Fractal Compact Manifold Theory (FCMT) is a unified framework for quantum mechanics, gravity, electromagnetism, and consciousness, built from atemporal symmetry breaking in a multifractal configuration space. The theory begins in a pre-perturbation state: a stable unified field on a compact manifold whose maximum multifractal dimension is *d*_max ≈ 4.01–4.02. That slight excess over four is required both to recover ordinary four-dimensional physics in the infrared and to supply the scale-dependent measure that keeps loop integrals finite. The field is governed by the quadratic potential V(φ_unified) = ½ m² φ_unified² with m² > 0. An atemporal quantum fluctuation then triggers symmetry breaking and differentiates the unified field into four fields: the informational field φ_info, which encodes self-similar structure; the consciousness field ψ_c, which carries the primordial awareness substrate; the entanglement field φ_e, which supplies non-local correlations; and the Higgs field φ_H, which generates mass. There is one variational structure. It is the action. Inside that action already sits the Shannon term *S*_info = −∑ *p*_ij log *p*_ij. Consciousness-Modulated Informational Entropy Minimization is that term, not a second principle standing beside the action. Isolating ψ_c as the field that weights the Shannon term produces the control Hamiltonian H = λ · f(p, ψ_c) − *S*_info[p]. Pontryagin’s necessary conditions are the Euler–Lagrange equation of the same action written so that the role of the control is explicit. When multifractal spectra rather than a single Shannon functional are required, the same construction applies to the Rényi family *H*_q. The principle does not change. A renormalized projection operator Proj_d^R then foliates the atemporal configuration space into ordinary four-dimensional Lorentzian hypersurfaces. Relational time emerges from the renormalization-group flow that accompanies the projection. Gravity arises as the geometric response to ψ_c-orchestrated clustering of the stress-energy; in the low-consciousness limit the multifractal corrections vanish and the classical Einstein equations are recovered exactly. The same residual symmetry of the entanglement field that produces its transverse-traceless two-point function also yields a massless vector mode whose projected dynamics reproduce Maxwell’s equations, so electromagnetism appears as a controlled consequence of the identical breaking that generates φ_e. In the high-energy sector the multifractal measure and the running intermittency γ(k) generate a Gaussian hard form factor that renders the spectrum finite. There is no infinite linear Regge trajectory. The effective cutoff Λ_R is restricted by three matching conditions, all built from functions already present in the architecture, to a window of roughly 3–30 TeV: the form factor is anchored to the same intermediate dimensionality already used for the consciousness-field length; suppression is required once γ(k) falls below 10⁻³; and suppression is required once the running projection kernel has narrowed enough that non-local comparison ceases to be effective. Those three conditions share the architecture. They are not three independent theories of the cutoff. The projection framework also generates the principal structural features of the Standard Model — three fermion generations from discrete scale bands, hierarchical Yukawa couplings from the running kernel, and the gauge group from residual transformations of the entanglement field — rather than inserting them by hand. Three faces of the same Lagrangian, plus one empirical lock, return one characteristic length for the consciousness field. The effective mass of ψ_c on the infrared slice *d*_i ≈ 3.3, the running width of the projection kernel on that slice, and the feedback coupling κ_c / *v*_IR² ≈ 0.06 share those two anchors and give the Compton length λ_ψc ≈ 1.5 μm (window 1.1–1.9 μm). A fourth contact is empirical rather than calculational: the optical and near-infrared member of the microtubule resonance hierarchy, and the Fröhlich condensate it supports, already sit at that length. That is a lock, not a fourth independent derivation. The length coincides with the characteristic size of large protein complexes, cytoskeletal bundles, and dendritic spines — the regime in which living systems must maintain order against thermal noise. FCMT therefore treats consciousness as a fundamental field that participates in the generation of spacetime, the emergence of electromagnetism, the finiteness of the high-energy spectrum, and the selection of low-informational-entropy configurations. Ordinary quantum phenomena and classical gravity appear as controlled projections of one atemporal stationarity condition. The framework yields sharp, testable signatures: a Higgs-consciousness Yukawa coupling |*y*_h| = 0.0153 ± 0.0022, consistent with public LHC limits as of November 2025; essentially null running of the CMB spectral index α_s ≈ 0; neural coherence times of order τ_d = 10⁻⁴ s; and a size-scanned search for enhanced order-maintenance or coherence in the window 0.5–3 μm, with the predicted peak at 1.5 μm. Consciousness is not emergent. It is the field that folds the universe.

Micro- and macro- heterogeneity of N-glycoproteome remodeling in endoplasmic reticulum stress

N-glycosylation plays essential roles in the folding, trafficking, and maturation of proteins in the secretory pathways, but how individual protein- and site- specific glycosylation rewires under endoplasmic reticulum (ER) stress is unknown. Particularly, intact glycopeptide data that retain the connectivity between glycosylation sites and the attached glycans are needed to reveal the micro- and macro- heterogeneity of N-glycosylation sites and their permutations in stressed cells. Here, we developed and optimized a magnetic polyethyleneimine boronic acid-containing scaffold (mPBA) enrichment workflow to achieve sensitive and broad enrichment of intact glycopeptides for mass spectrometry analysis, requiring only 0.1 to 0.5 mg total peptide input. With this method, we performed a large intact glycopeptide comparative study, systematically analyzing 13,759 unique protein-, site-, and glycoform combinations, termed glycopeptidoforms, in normal and stressed human cells. The data reveals a dynamic rewiring of N-glycosylation involving hundreds of proteins with complex protein-, site-, and glycan- specific granularity. The magnitude of differential glycosylation far exceeds that of protein expression changes. Individual glycoform reconfigurations can be observed that indicate likely disruptions within specific steps in protein maturation and trafficking. Mannose trimming emerges as a shared disruption across multiple proteins, suggesting a processing bottleneck of the ER stress glycoproteome. Together, these results reveal molecular details into the remodeling of protein secretory pathways upon ER stress and highlight the utility of mPBA for sensitive N-glycoproteomics studies. The data can be visualized on https://glycoproteome.info.

Effectiveness, Patient Satisfaction, and Safety of a Next-generation PLLA Collagen Biostimulator for Nasolabial Fold Augmentation: 12-month Results of a Prospective Multicenter Study.

BACKGROUND Poly-L-lactic acid (PLLA) dermal fillers induce neocollagenesis through a bioinductive mechanism rather than facial tissue volumization. The next-generation PLLA-LASYNPRO formulation (LASYNPRO, Lactic Acid Induced Synthesis of Collagen Protein), a biomaterial-microsphere technology developed for regenerative aesthetic biostimulation, composed of uniform, non-porous microspheres, has been proposed as an evolution of earlier PLLA products, offering a more controlled, lower-inflammatory regenerative pathway. Efficacy data for nasolabial fold (NLF) correction are emerging, but patient-reported outcomes remain underreported. OBJECTIVES To evaluate patient-reported outcomes, aesthetic self-perception, and treatment satisfaction over 12 months following JULÄINE (PLLA-LASYNPRO) treatment for NLF correction. METHODS Prospective, single-arm, multicenter post-market clinical follow-up (PMCF) investigation enrolling 60 subjects. Subjects received up to 3 bilateral NLF injections of JULÄINE™ at 2- to 4-week intervals. Patient-reported outcomes included FACE-Q Appraisal of Lines (Nasolabial Folds), FACE-Q Satisfaction with Outcome, the Global Aesthetic Improvement Scale (GAIS), and a 12-item subject satisfaction questionnaire, assessed at 6 and 12 months after the final injection. RESULTS At 12 months, the FACE-Q Appraisal of Lines score improved by a mean of 20.7 points (P<.0001; d=1.14), a large effect that continued to grow between 6 and 12 months. Subject GAIS responder rate was 83.3% at both timepoints. More than 90% of subjects reported natural-looking results; 83%-85% would repeat the treatment; 90%-94% would recommend it. Overall satisfaction was 88.9% at 6 months and 77.8% at 12 months. No serious adverse events or device deficiencies were reported. CONCLUSIONS JULÄINE produced sustained, clinically meaningful improvements in patient-perceived aesthetic outcomes with high treatment satisfaction over 12 months. The consistent perception of natural-looking results is in line with the progressive, collagen-building mechanism of PLLA-LASYNPRO.

Formation and Ecological Dynamics of Synthetic Biofilms Derived from Microbial Components of the Cladonia arbuscula Thallus

Synthetic multi-species consortia provide valuable insights into the ecological and structural dynamics of complex microbial biofilms. However, the specialized functional contributions of individual components under severe nutrient limitations remain poorly understood. This study investigated the population dynamics, matrix biogenesis and metabolic potential of a synthetic ‘protolichen biofilm’ model comprising Asterochloris microalgae, Gordonia bacteria, Thelebolus filamentous fungi and Occultifur yeast. The biofilms were cultivated under strict carbohydrate-deficient conditions for 30 days. Population changes, extracellular polymeric substance (EPS) matrix formation, and the concentrations of extracellular DNA (exDNA) and proteins (exProt), as well as potential dehydrogenase activity (via iodonitrotetrazolium reduction), were evaluated across monocultures, binary, ternary and quaternary consortia. Under carbon starvation, the photoautotrophic microalgae dominated the consortium, driving an 11-fold increase in population size in the four-component system and serving as the primary source of exDNA, which increased by up to three orders of magnitude by day 30. The Gordonia sp. exhibited a tenfold expansion by actively localizing to fungal hyphae and microalgal cell walls. This was directly correlated with a sharp increase in metabolic activity. By contrast, Thelebolus sp. initially provided the structural framework via EPS production, but exhibited limited metabolic activity over time. Meanwhile, the Occultifur sp. yeast population was severely suppressed, adopting a sit-and-wait ecological strategy. Spearman correlation analysis revealed that multi-species integration stabilized the community and triggered significant emergent effects in exDNA accumulation and metabolic potential, but only when microalgae were present. These findings demonstrate that microalgae and bacteria primarily drive metabolism and regulation within the protolichen consortia investigated, while fungi and yeast play structural or opportunistic roles. This provides a robust framework for understanding complex symbiotic interactions.

A curated benchmark for cofolding models on kinase conformational states

Protein kinases are critical drug targets, requiring therapeutics that can modulate their active and inactive conformational states. While cofolding models can generate global folds directly from kinase sequences and ligand SMILES strings, these models have not yet been tested on their ability to recover ligand-induced-fit conformational states of the kinase proteins. Here, we introduce KinConfBench, a curated benchmark of 2225 high-quality human kinase chains to evaluate the ability of four state-of-the-art cofolding models—Boltz-2, Chai-1, Protenix, and RoseTTAFold-All-Atom—to recover both canonical and rare conformational states. We show that geometric success metrics of a ligand pose in the active site do not correlate strongly with the correct kinase conformational state, motivating a new set of dynamical benchmarks for assessing cofolding models. While all four cofolding models achieve ~60–80% prediction accuracy for kinase conformational classification, they exhibit severe mode collapse when performing multiple inferences, show negligible structural diversity in sampling induced-fit motions, and display a prevalent “apo-drift” in which most cofolding models predominantly predict the kinase to be in its ligand-free state. Our results highlight that capturing ligand-induced protein conformational diversity, not just geometric fit, is critical for next-generation structure-based drug discovery.