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PubMed2026

Dual-tasking reveals severity-dependent reorganization of cortical beta energy landscapes in Parkinson's disease.

Dual-task impairment is a hallmark of Parkinson's disease (PD), yet the large-scale neural mechanisms underlying postural-motor interference remain poorly understood. In particular, it is unclear how cortical network dynamics reorganize across disease severity when postural control competes with concurrent task demands. This study investigated EEG-derived beta-band cortical energy landscapes in healthy older adults, early-stage PD, and mid-stage PD during single- and dual-task conditions. Dual-task behavioral cost increased with disease severity for concurrent manual performance (p < 0.001), whereas a quadratic pattern was observed for postural performance. Energy landscape analysis revealed severity-dependent reconfiguration of cortical beta dynamics. Dual-task-related landscape changes in effective network flexibility (ΔNeff), landscape geometry (ΔEvar and ΔGmag), and dominant low-energy attractor organization (ΔLow mass and ΔLow area) showed significant monotonic trends (p < 0.05), reflecting progressive constrained cortical network dynamics with advancing PD severity. In addition, dual-task-related landscape alterations were associated with clinical severity, as indexed by Hoehn and Yahr stage (|r| = 0.353-0.423, p = 0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r| = 0.333-0.455, p = 0.009-0.063). These findings demonstrate that dual-task demands induce severity-dependent reconfiguration of cortical beta energy landscapes in PD. Energy landscape geometry may capture systems-level neural constraints associated with dual-task susceptibility in PD, providing a physiologically grounded framework to characterize disease-related functional vulnerability.

Humans↗

PubMed2024

The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes.

Protein evolution is guided by structural, functional, and dynamical constraints ensuring organismal viability. Pseudogenes are genomic sequences identified in many eukaryotes that lack translational activity due to sequence degradation and thus over time have undergone "devolution." Previously pseudogenized genes sometimes regain their protein-coding function, suggesting they may still encode robust folding energy landscapes despite multiple mutations. We study both the physical folding landscapes of protein sequences corresponding to human pseudogenes using the Associative Memory, Water Mediated, Structure and Energy Model, and the evolutionary energy landscapes obtained using direct coupling analysis (DCA) on their parent protein families. We found that generally mutations that have occurred in pseudogene sequences have disrupted their native global network of stabilizing residue interactions, making it harder for them to fold if they were translated. In some cases, however, energetic frustration has apparently decreased when the functional constraints were removed. We analyzed this unexpected situation for Cyclophilin A, Profilin-1, and Small Ubiquitin-like Modifier 2 Protein. Our analysis reveals that when such mutations in the pseudogene ultimately stabilize folding, at the same time, they likely alter the pseudogenes' former biological activity, as estimated by DCA. We localize most of these stabilizing mutations generally to normally frustrated regions required for binding to other partners.

Cyclophilin A↗

PubMed2025

Insights into the Catalytic Activity of a Metagenome-Derived Urethanase.

The discovery of urethanases shows an opportunity to access the biotechnological recycling of polyurethane-based plastics (PURs), widely used in the manufacture of everyday materials. However, the mechanistic understanding of these enzymes remains under debate. In this work, we report a QM/MM-based mechanistic study of the metagenome-derived urethanase UMG-SP2 catalyzing the degradation of a urethane-like model compound, 4-nitrophenyl benzylcarbamate (pNC). A high-quality structural model generated with AlphaFold2, prior to the availability of the crystal structure, accurately captured the Ser-Ser-Lys catalytic triad characteristic of amidase signature enzymes. Highly accurate constant-pH nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) simulations provided the full titration curve of active site Lys, explaining the need for alkaline media for the enzyme to be active. The generation of the free energy landscape, obtained by means of free energy perturbation methods with the M06-2X DFT functional describing the QM region of the full system, reveals an esterase-like three-step mechanism of UMG-SP2, i.e., acylation, hydrolysis, and decarboxylation, with all steps being kinetically feasible. Our computational results show very good agreement with experimental kinetic data, with a calculated free energy barrier of 21.2 kcal·mol-1 for the rate-determining step compared to 22.9 kcal·mol-1 derived from the experimentally measured turnover frequency (TOF). The present results also open the door for the final decarboxylation occurring in the solution after the release of the product of the hydrolysis step or within the active site. These findings provide an atomistic insight into the urethanase function and establish a robust framework for the future design of biocatalysts targeting polyurethane degradation.

Metagenome↗

PubMed2025

Pioneer in Molecular Biology: Conformational Ensembles in Molecular Recognition, Allostery, and Cell Function.

In 1978, for my PhD, I developed the efficient O(n3) dynamic programming algorithm for the-then open problem of RNA secondary structure prediction. This algorithm, now dubbed the "Nussinov algorithm", "Nussinov plots", and "Nussinov diagrams", is still taught across Europe and the U.S. As sequences started coming out in the 1980s, I started seeking genome-encoded functional signals, later becoming a bioinformatics trend. In the early 1990s I transited to proteins, co-developing a powerful computer vision-based docking algorithm. In the late 1990s, I proposed the foundational role of conformational ensembles in molecular recognition and allostery. At the time, conformational ensembles and free energy landscapes were viewed as physical properties of proteins but were not associated with function. The classical view of molecular recognition and binding was based on only two conformations captured by crystallography: open and closed. I proposed that all conformational states preexist. Proteins always have not one folded form-nor two-but many folded forms. Thus, rather than inducing fit, binding can work by shifting the ensembles between states, and this shifting, or redistributing the ensembles to maintain equilibrium, is the origin of the allosteric effect and protein, thus cell, function. This transformative paradigm impacted community views in allosteric drug design, catalysis, and regulation. Dynamic conformational ensemble shifts are now acknowledged as the origin of recognition, allostery, and signaling, underscoring that conformational ensembles-not proteins-are the workhorses of the cell, pioneering the fundamental idea that dynamic ensembles are the driving force behind cellular processes. Nussinov was recognized as pioneer in molecular biology by JMB.

Molecular Biology↗

PubMed2026

Quantifying the peripheral surface information entropy from conformational ensembles of globular protein-peptide complexes.

Predicting favorable protein-peptide binding events remains a central challenge in biophysics, with continued uncertainty surrounding how nonlocal effects shape the global energy landscape. Here, we introduce peripheral surface information entropy, SΨ, a quantitative measure of the statistical variability in apolar and charged non-interacting surface (NIS) proportions across conformational ensembles. Within the Gibbs free-energy relation ΔG = ΔH - TΔS, SΨ is proposed as a computationally tractable entropic proxy rather than a direct thermodynamic observable or stand-alone estimator of binding affinity. Using energy-directed molecular docking via HADDOCK3 and explicit-solvent molecular dynamics simulations, it is demonstrated that favorable binding partners exhibit emergent, low-entropy N-states (discrete macrostates in NIS state space) indicative of preferential apolar/charged surface configurations. Across dozens of peptides and multiple receptor systems (WW, PDZ, and MDM2 domains), dominant N-states persisted under varied docking parameters and initial conditions. A meta-ensemble of 657 complexes from 36 experiments over 15 years confirmed the presence of dominant NIS modes independent of in silico methodology, suggesting an evolutionary selection pressure toward specific NIS fingerprints. These findings establish SΨ as a thermoinformatic descriptor that encodes favorable binding constraints into unique statistical signatures of the NIS.

Entropy↗

PubMed2026

Molecular dynamics simulations of positively selected codons in FcγRI reveal novel biochemical binding properties.

FcγRI is a high-affinity receptor for IgG, associated with autoimmune disease pathology and determines clinical responses to antibody-based immunotherapies. FcγRI has a complex evolutionary history that is not fully understood, and to address this we explored signatures of positive selection in the receptor's functional gene, FCGR1A, using codon-based selection tests on aligned 1-1 orthologous sequences from placental mammals (n = 32). Signatures of positive selection have occurred at several locations within the gene, with two sites (H148 (M2a ω 0.997 & M8 ω = 0.993)) and (W149 (M2a ω = 0.999 & M8 ω = 1.000)) exhibiting highest posterior probabilities, suggesting strong evidence of positive selection; these positions are known to form one of the FcγRI-IgG binding interfaces. We employed ancestral reconstruction to statistically infer prior codon sequences at these sites and identified ancestral H148P and W149R codons at different nodes in the phylogeny. Employing molecular dynamics simulations, we determined how evolutionary changes at these sites may have influenced the binding of FcγRI-IgG of modern-day Homo sapiens. Measuring RMSD, free energy, radius of gyration, hydrogen bond formation, and analyzing free energy landscapes, we demonstrate that structural instability between mutant structures vs the WT counterpart; however, overall binding potential increases at position 148, yet decreases at 149 in potential. H148P protonation at physiological pH remains similar, yet during acidotic calculations, protonation is likely reduced, with predicted reduction in affinity for IgG. While ancestral W149R substitutions demonstrate an implication for electron conjugation. Examining key sites at this binding FcγRI-IgG interface, our data demonstrate that these two codons have evolved in humans to be relatively insensitive to shifts in pH promoting a more stable interaction with the Fc portion of IgG during diseases that promote acidosis.

Receptors, IgG↗

PubMed2026

Comparative and Subtractive Genomics Analysis of Multidrug-Resistant Klebsiella pneumoniae Strains for Novel Target Identification and Drug Repurposing Strategies.

The rapid rise of multidrug-resistant (MDR) Klebsiella pneumoniae has created a major global health challenge due to the limited availability of conserved therapeutic targets effective across diverse resistant strains. In this study, an integrative computational target-discovery and drug-repurposing framework was applied to six clinically relevant K. pneumoniae strains. Comparative genomic analysis identified 3012 conserved genes, which were subsequently filtered to nine essential, non-host homologous proteins. Among these, three conserved cytoplasmic proteins (accD, cpxR, and mraZ) were prioritized for functional analysis, with acetyl-CoA carboxylase subunit beta (accD) emerging as the most promising therapeutic target based on sequence conservation, predicted essentiality, subcellular localization, and pathway association. Structural assessment supported the reliability of the predicted accD model, whereas consensus binding-site analysis identified key residues suitable for ligand interaction. Virtual screening of FDA-approved drugs followed by molecular docking identified several compounds with favorable binding profiles toward accD. Subsequent molecular dynamics simulations, including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), hydrogen-bond occupancy, principal component analysis (PCA), and PCA-based free energy landscape (FEL) analyses, consistently identified tenapanor, micafungin, deferoxamine, and cobicistat as the most stable protein-ligand complexes, with tenapanor exhibiting the most favorable overall structural and thermodynamic stability profile. These findings identify accD as a promising therapeutic target in MDR K. pneumoniae and suggest several FDA-approved compounds as potential candidates for drug repurposing. Although experimental validation is needed to confirm their biological activity and therapeutic potential, this study demonstrates the potential of integrating comparative genomics with molecular dynamics analyses to support antimicrobial target identification and drug repurposing against MDR bacterial pathogens.

Klebsiella pneumoniae↗

PubMed2025

Free energy spectroscopy reveals the mechanistic landscape of chromatin compaction.

Eukaryotic genomic DNA is repeatedly wrapped into nucleosome spools: the basic building block of chromatin. This organization regulates the physical accessibility of the genome to gene transcription, replication, and repair regulatory factors. Chromatin compaction is controlled by multivalent weak interactions, resulting in a complicated conformational landscape that remains challenging to characterize. This work reports a method for characterizing chromatin compaction, Free Energy Spectroscopy (FES), which is based on DNA nanotechnology and transmission electron microscopy. This method experimentally determines the chromatin compaction free energy landscape in terms of end-to-end distance and nucleosome stacking interactions. By deconvolving the free energy landscapes of partially and fully compact tetranucleosomes, FES revealed three separate mechanisms by which linker histones reshape the compaction energetics to condense chromatin. This study establishes FES as a method with the potential to help answer a broad range of mechanistic questions about genome and epigenome function.

DNA nanotechnology↗

PubMed2025

Cooperative contribution of multiple energy substrate pathways to floral thermogenesis in sacred lotus.

Floral thermogenesis in lotus (Nelumbo nucifera) is a highly energy-intensive process, requiring substantial metabolic reconfiguration and substrate input. However, the mechanisms coordinating energy substrate supply during this process remain unclear. Here, we integrated microscale proteomics, time-series transcriptomics, and mitochondrial feeding assays to elucidate the substrate provisioning strategies supporting thermogenesis in lotus receptacles. Proteomic analysis revealed a concerted upregulation of major energy metabolism pathways at the thermogenic initiation stage, accompanied by enhanced expression of energy dissipation-related proteins (alternative oxidase and uncoupling proteins), indicative of a metabolic shift favoring heat production over ATP synthesis. Our results highlight the cooperative contribution of multiple pyruvate sources to mitochondrial respiration. Both the mitochondrial pyruvate carrier (MPC)-mediated cytosolic pyruvate import and the NAD-dependent malic enzyme (NAD-ME)-derived intramitochondrial pyruvate flux were significantly elevated at the thermogenic stage. Notably, isotopic feeding experiments revealed that NAD-ME-derived pyruvate may contribute more substantially than MPC-derived pyruvate under thermogenic conditions, reflecting a highly flexible substrate utilization strategy. In addition, increased expression of alanine aminotransferase (AlaAT) and β-oxidation-related genes suggested that alanine transamination and fatty acid degradation may further expand the respiratory substrate pool. Collectively, this study uncovers a diverse and dynamic landscape of energy substrate supply that underpins heat production in thermogenic lotus tissues. These findings offer insights into how plants coordinate metabolic flexibility to meet the high energetic demands of floral thermogenesis.

Flowers↗

PubMed2025

NumSimEX: A method using EXX hydrogen exchange mass spectrometry to map the energetics of protein folding landscapes.

Hydrogen exchange mass spectrometry (HXMS) is a powerful tool to understand protein folding pathways and energetics. However, HXMS experiments to date have used exchange conditions termed EX1 or EX2 which limit the information that can be gained compared to the more general EXX exchange regime. If EXX behavior could be understood and analyzed, a single HXMS timecourse on an intact protein could fully map its folding landscape without requiring denaturation. To address this challenge, we developed a numerical simulation method called NumSimEX that models EXX exchange for arbitrarily complex folding pathways. NumSimEx fits protein folding dynamics to experimental HXMS data by iteratively comparing the simulated and experimental timecourses, allowing for determination of both kinetic and thermodynamic protein folding parameters. After analytically verifying NumSimEX's accuracy, we demonstrated its power on HXMS data from beta-2 microglobulin (β2M), a protein involved in dialysis-related amyloidosis. In particular, using NumSimEX, we identified three-state kinetics that near-perfectly matched experimental observation. This proof-of-principle application of NumSimEX sets the stage for harnessing HXMS to expand our understanding of proteins currently excluded from traditional protein folding methods. NumSimEX is freely available at https://github.com/JaswalLab/NumSimEX_Public.

Protein Folding↗

PubMed2026

Stepwise DNA-unwinding gates TnpB genome-editing activity.

TnpB is a compact RNA-guided endonuclease and an evolutionary ancestor of CRISPR-Cas12 that offers a promising platform for genome engineering. However, the genome-editing activity of TnpBs remains limited, and its underlying determinants are poorly understood. Here, we used biochemical and single-molecule assays to examine the DNA-unwinding mechanism of Youngiibacter multivorans TnpB (Ymu1 TnpB). DNA unwinding proceeds through a discrete, long-lived, partially unwound intermediate state before reaching a fully unwound open state. The open state forms inefficiently and collapses readily in the absence of negative supercoiling. An optimized variant, H4W-L304F-V305R (Ymu1-WFR), stabilizes formation of both the intermediate and open states, resulting in enhanced DNA cleavage in vitro and increased genome editing in plants. These findings identify the physical basis for the observed minimal activities of natural TnpBs, revealing how stabilizing specific unwinding states enables efficient DNA targeting.

Gene Editing↗

PubMed1979

Bootstrapping on the adaptive landscape.

Different versions of a gene or of a multigenic system may be essentially equivalent so far as the specific function of the structures which they code for or control is concerned, but very different with respect to their amenability to evolution. The structural features which increase evolutionary amenability are a disadvantage to the organism in terms of energy. Nevertheless, they accumulate in the course of evolution as a consequence of hitchhiking along with the desirable traits whose evolution they make possible. This is the bootstrap principle of evolutionary adaptability. In terms of the adaptive landscape bootstrapping corresponds to populations evolving in such a way that they occupy regions of the landscape which are more amenable to evolutionary hill climbing. The bootstrapping idea has implications for structure-function relations in a number of complex biological information processing systems, including biochemical systems, the immune system, and the brain. Bootstrapping is also discussed in connection with the origin of information processing (the origin of life) and in connection with possible designs for macromolecular computing systems.

Adaptation, Biological↗

PubMed2024

Integrated multi-omics approaches reveal the neurotoxicity of triclocarban in mouse brain.

Triclocarban (TCC) is an antimicrobial ingredient that commonly incorporated in many household and personal care products, raising public concerns about its potential health risks. Previous research has showed that TCC could cross the blood-brain barrier, but to date our understanding of its potential neurotoxicity at human-relevant concentrations remains lacking. In this study, we observed anxiety-like behaviors in mice with continuous percutaneous exposure to TCC. Subsequently, we combined lipidomic, proteomic, and metabolic landscapes to investigate the underlying mechanisms of TCC-related neurotoxicity. The results showed that TCC exposure dysregulated the proteins involved in endocytosis and neurodegenerative disorders in mouse cerebrum. Brain energy homeostasis was also altered, as evidenced by the perturbation of pyruvate metabolism, TCA cycle, and oxidative phosphorylation, which in turn caused mitochondrial dysfunction. Meanwhile, the changing trends of sphingolipid signaling pathway and overproduction of mitochondrial reactive oxygen species (mROS) could enhance the neural apoptosis. The in vitro approach further demonstrated that TCC exposure promoted apoptosis, accompanied by the overproduction of mROS and alteration in the mitochondrial membrane potential in N2A cells. Together, dysregulated endocytosis, mROS-related mitochondrial dysfunction and neural cell apoptosis are considered to be crucial factors for TCC-induced neurotoxicity, which may contribute to the occurrence and development of neurodegenerative disorders. Our findings provide novel perspectives for the mechanisms of TCC-triggered neurotoxicity.

Animals↗

PubMed2026

Integrated exome and mitochondrial genome sequencing reveals the genetic landscape of primary mitochondrial diseases: findings from a large Tunisian cohort.

Primary mitochondrial diseases are a heterogeneous group of neurometabolic disorders recognized as the most common metabolic genetic diseases. They manifest at any age, affecting any tissue or organ, especially those with high energy demands, and are caused by pathogenic variants in both mitochondrial and nuclear genomes. Here, we aimed to describe the genetic spectrum of a Tunisian pediatric cohort with suspected mitochondrial diseases. We recruited 47 unrelated families who underwent exome sequencing as a first-tier test followed by whole mitochondrial genome sequencing for unsolved cases. Dedicated bioinformatic pipelines and prediction tools were used to determine the potential disease-causing variants. Sanger sequencing confirmed the presence and segregation within parents. For the newly identified variants, structural modeling was conducted to study the impact of these variants on protein structure and motions. Dual genome sequencing yielded a molecular diagnosis in 33/47 families (70%) and 18/47 (38%) showed disease-causing variants in genes encoding mitochondrial proteins. Among them, four families disclosed novel variants in FASTKD2, SERAC1 and GATB, which were supported by in-depth in silico and structural analyses demonstrating their deleterious effect. The remaining families (32%, 15/47) disclosed other metabolic and neurological disorders. An exome-first strategy delivers a high diagnostic yield in Tunisia, where consanguinity remains high and simultaneously captures mitochondrial and non-mitochondrial etiologies. Mitochondrial sequencing remains indispensable in the case of an inconclusive exome. Thus, our data expand the clinical and genetic spectrum of primary mitochondrial diseases in Tunisia, an underrepresented and admixed population.

Humans↗

PubMed2026

Landscape Genomics Reveals Divergent Adaptation Modes and Predicts Climate Vulnerability in Xinjiang Indigenous Sheep.

Climate change increasingly endangers precious indigenous sheep germplasm resources distributed across diverse Chinese landscapes, and systematically decoding their polygenic climate-adaptive genetic mechanisms is essential for targeted breed conservation and long-term sustainable pastoral production. Whole-genome resequencing data from 93 individuals covering six representative local sheep breeds were analyzed in this work. After filtering highly collinear climate variables, three mature landscape genomic approaches were jointly applied to identify environment-linked gene variants, while two predictive metrics across ten CMIP6 future climate scenarios quantified each breed's long-term adaptive risks. Six temperature- and water-related environmental factors jointly drove sheep population genetic differentiation, with temperature fluctuation indices showing markedly stronger explanatory power. Detected adaptive genes were significantly enriched in ion transport, energy metabolism and cellular stress response pathways. Future projections indicated western breeds (Bayinbuluke, Cele Black, Xiahe) face severe maladaptation risks under high-emission SSP370 scenarios by 2100, whereas central and eastern breeds possess much broader climate tolerance. This study systematically reveals the core genomic basis of ovine climate adaptation and quantifies distinct breed-specific climate vulnerability, providing solid reliable theoretical support for precision germplasm conservation and selective breeding of climate-resilient sheep varieties.

adaptive loci↗

PubMed2026

Dual functional genomics reveals a broad and convergent landscape of asciminib resistance in BCR::ABL1.

BACKGROUND: Drug resistance is a constantly evolving challenge. The allosteric inhibitor asciminib is a novel therapy for chronic myelogenous leukemia (CML) that targets the myristoyl pocket of the BCR::ABL1 kinase. While it can overcome resistance to active-site inhibitors like imatinib, new resistance mutations to asciminib are emerging. The complete landscape of these mutations, particularly those outside the kinase domain or those arising from epistatic interactions between mutations, are not well understood. METHODS: This study employed a dual functional genomics approach in CML cell line models. A high-throughput adenosine base editing (ABE) screen was used to identify broad hotspots of asciminib resistance across the entire BCR::ABL1 protein. Deep mutational scanning (DMS) was then used to create a high-resolution map of all possible amino acid changes within these hotspots. An "edit-on-edit" screen was performed to investigate epistasis by introducing a library of mutations into a cell line that was pre-edited to incorporate the common imatinib-resistance mutation, Y253H. Finally, a novel Förster resonance energy transfer (FRET) biosensor was developed to measure the conformational state of BCR::ABL1 in live cells and link it to drug sensitivity. RESULTS: The screens identified 279 asciminib resistance mutations and revealed resistance hotspots distributed across the SH3, SH2, and kinase domains, in contrast to imatinib resistance, which is largely confined to the kinase domain. The study uncovered a potent epistatic interaction between a mutation in the SH3 domain (V73A) and a mutation in the kinase domain P-loop (Y253H), which synergistically conferred high-level resistance. The FRET biosensor demonstrated that asciminib resistance mutations tend to destabilize the "closed" inactive conformation of the ABL1 kinase. CONCLUSIONS: The landscape of asciminib resistance is broader and more complex than previously appreciated, involving mutations across multiple domains that disrupt ABL1 autoinhibition. Epistasis between mutations acquired during sequential therapies can create unexpected and potent resistance. However, these diverse genetic resistance mechanisms converge on a single biophysical measurement of the openness of the active ABL1 conformation. This provides a unified framework for understanding asciminib resistance and underscores the need for routine clinical resistance monitoring to include the SH3 and SH2 domains in first line and later line therapy.

Fusion Proteins, bcr-abl↗

PubMed2026

Lactylome Reprogramming Mediates Therapeutic Response and Adaptation to Neoadjuvant Chemotherapy in Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) exhibits high prevalence in China and poor prognosis despite neoadjuvant chemotherapy (NACT), with significant chemoresistance development. Tumor-associated metabolic reprogramming and NACT-induced cellular stress promote lactate accumulation, which serves as a precursor for lysine lactylation (Kla), a post-translational modification potentially regulating cancer progression. We hypothesized that systematic characterization of the lactylome in response to NACT could reveal critical molecular mechanisms underlying treatment and identify new therapeutic vulnerabilities in ESCC. Herein, through comprehensive proteomic and lactylome profiling of tumor and adjacent normal adjacent tissues from 31 ESCC patients (with or without NACT treatment), we identified 8281 proteins and 1836 Kla sites across 62 samples. NACT induced substantial lactylome alterations with 307 differentially expressed Kla sites predominantly in nonhistone proteins involved in DNA damage response and metabolic pathways. Our data revealed that while NACT-induced suppression of energy metabolism, coupled with upregulated 3-hydroxy-3-methylglutaryl reductase degradation 1 complex expression, may exert potential proapoptotic effects, the activation of ribosome biogenesis and increased nucleoprotein lactylation triggered tumor-protective mechanisms. Mechanistically, we demonstrated that DNA damage and elevated lactate levels induced poly(ADP-ribose) polymerase 1 K654 lactylation, enhancing its enzymatic activity and augmenting poly(ADP-ribosyl)ation of downstream targets, potentially playing a pivotal role in chemotherapy resistance-associated pathways. This comprehensive tissue-level landscape of Kla dynamics in ESCC response to chemotherapy establishes Kla as a critical regulatory mechanism in treatment response, potentially offering novel therapeutic targets and predictive biomarkers for personalized treatment strategies.

Humans↗

PubMed2026

Integrated transcriptomic analysis of mRNA and miRNA in Brown adipose tissue of the greater horseshoe bats during hibernation.

Hibernation enables animals survive harsh environments by conserving energy through reduced metabolism and body temperature. Brown adipose tissue (BAT) plays a critical role in non-shivering thermogenesis, crucial for warming up during arousal phase. The greater horseshoe bats (Rhinolophus nippon) are typical hibernators and non-shivering thermogenesis in BAT tissue may persist throughout the arousal process in bats. This study examines gene expression and regulatory changes in BAT of these bats across active, hibernation, and arousal phases using transcriptome and miRNA sequencing. A total of 2721 differentially expressed mRNAs and 268 differentially expressed miRNAs were identified. The results reveal that the BAT transcriptome undergoes state-dependent remodeling throughout the hibernation process. The most pronounced divergence occurs between the active phase and torpor, involving cell cycle arrest, immunosuppression, thermogenic signal desensitization, and upregulation of lipid metabolism and autophagy pathways, reflecting the coordinated adaptation of energy conservation and thermogenic reserve. In contrast, transcriptional alterations between torpor and arousal are extremely limited, indicating that torpid BAT is already pre-primed for thermogenesis and requires only modest transcriptional adjustments to activate heat production. Notably, although body temperature recovers to active-phase levels during arousal, the molecular signature of BAT remains highly similar to that of the torpid state. Furthermore, the core thermogenic gene UCP1 showed no significant expression differences across the three groups. In conclusion, this study systematically delineates the miRNA-mRNA regulatory landscape of bat BAT across the hibernation process, and deepens our understanding of the thermoregulatory mechanisms underlying mammalian hibernation.

BAT↗