Biology subjects

Wang, M.

Publications and source records attributed to Wang, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

LDSC regression-based heritability estimates can be biased when summary statistics are obtained from meta-analysis or imputed variants

MotivationLinkage disequilibrium score (LDSC) regression is a popular method to estimate heritability for complex traits using summary statistics and linkage disequilibrium (LD) reference panels, offering a practical alternative to methods requiring individual-level data. Despite its widespread use, LDSC regression can produce biased heritability estimates. The properties of LDSC regression were investigated using summary statistics from several large-scale Alzheimers disease (AD) studies and a variety of LD reference panels. These heritability estimates were compared with those obtained from individual-level data. ResultsWhen LDSC regression was applied to summary statistics obtained from meta-analysis, it led to an underestimation of heritability. This can occur if meta-analysis is used to combine studies of different ancestries leading to the caveat of the lack of an appropriate LD reference panel. Additionally meta-analyses often include studies with different phenotype definitions, that not only impacts heritability estimates but also makes them uninterpretable. Summary statistics generated from imputed variants, even those with high imputation accuracy, can lead to underestimation of heritability. For example, the heritability estimates for AD were reduced from 0.265 (se 0.148) to 0.160 (se 0.041) when imputed variants (INFO>0.9) were included compared to analyzing only genotype array variants. A decrease in heritability estimates was also observed when individual-level imputed variant data were analyzed using GCTA-GREML. Our findings highlight the caveats of estimating heritability using meta-analysis summary statistics or imputed data instead of genotyped or sequence data.

genetics↗

bioRxiv2026

A vascular chip for disease-relevant flow shear stress topology

Vascular chips have advanced endothelial mechanobiology by enabling controlled responses to hemodynamic cues, yet disease-relevant wall shear stress (WSS) modeling remains limited. Simplified one-dimensional flow shear systems, designed mainly for physiological mechanobiology, miss the topological organization of pathological flow, whereas patient-specific vascular models capture complex hemodynamics but sacrifice generality and imaging compatibility. Here we develop a programmable vascular chip that converts disease-associated WSS topology into a physiologically parameterized experimental input. The device reconstructs a representative pathological shear-topology field on endothelial layer, supports stationary and physiologically paced oscillatory flow modes, and integrates matched unidirectional-shear references within the same chip. Using this system, we show that oscillatory WSS topology destabilizes endothelial monolayers, drives asymmetric collective emergent behaviors, impairs actin-nuclear mechanotransduction, accompanied by nuclear softening and enhanced perinuclear nanoparticle uptake. Integrated live-cell imaging, fluorescence analysis, Brillouin microscopy, and transport assays enable multimodal phenotyping across collective, subcellular mechanical and functional scales. By making disease-relevant WSS topology experimentally controllable, this vascular-chip framework bridges computational hemodynamics and experimental mechanomedicine, supporting standardized vascular disease modeling and functional screening.

bioengineering↗

bioRxiv2026

EEG biomarkers of reinforcement learning and motivation: A multi-task battery

Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components, yet we lack neural biomarkers capable of detecting their differential effects. Here, we report the development of a five-task EEG battery designed to probe these dissociable RL mechanisms. Using a model-free analytical approach in healthy volunteers, we identify distinct neural markers across probabilistic instrumental learning, motivational vigour, Pavlovian-instrumental transfer, reversal learning, and a working memory-RL task. A centroparietal P300 tracked incremental learning across three paradigms and showed cross-task convergent validity. Readiness potentials and beta suppression indexed value-based motor preparation, while frontal theta captured Pavlovian-instrumental conflict. The largely independent pattern across markers supports the batterys capacity to detect selective pharmacological effects on distinct neural systems.

neuroscience↗

bioRxiv2026

NLR from soybean Rsv1 locus confers broad-spectrum resistance to soybean mosaic virus G1-G7 strains by recognizing viral P3 protein

Nucleotide-binding leucine-rich repeat (NLR) immune receptor genes are of significant value in disease resistance breeding and the control of viral diseases. Soybean mosaic virus (SMV) poses a serious threat to soybean production and the Rsv1 locus in soybean cultivar Suweon 97 confers broad-spectrum resistance against SMV strains G1 to G7; however, this locus harbors no fewer than 18 NLR genes, and thus the broad-spectrum antiviral mechanisms underlying the Rsv1 locus remain poorly understood to date. Here, we established a rapid and highly efficient screening system for cloning NLR genes from soybean Rsv1 locus and identified a broad-spectrum antiviral NLR gene 13g184900 from this highly complicated locus. The NLR encoded by 13g184900 can recognize viral P3 protein from all SMV strains (G1-G7) and another potyvirus Bean common mosaic virus (BCMV). The coiled-coil (CC) domain of this NLR directly interacts with viral P3 protein. Additionally, we showed that this NLR originated from wild soybean accession in East China and has been introduced into several soybean cultivars during domestication. Collectively, we developed a high-throughput screening system for identifying NLR genes in soybean and our study provides new mechanistic perspective on how the Rsv1 locus mediates the broad-spectrum resistance to all SMV G1-G7 strains.

plant biology↗

bioRxiv2026

Agentic AI for Structural Elucidation and Discovery of Drug Metabolites from Mass Spectrometry Data

The majority of chemical signals detected in public metabolomics repositories remain structurally undefined. Large language models (LLMs) are probabilistic systems whose capacity to generate outputs beyond their training data, which can cause hallucinations, makes them also potentially suited to hypothesize structures for molecules that have never been described. We aimed to build a system that could harness this LLM generative capacity combined with domain specific tools/framework to constrain hallucination and produce validated discoveries. We developed a GNPS2 agentic AI system that interprets LC-MS/MS data by integrating spectral alignment, molecular formula inference, rule-based structural enumeration, machine learning-based spectrum prediction, and translates natural language hypotheses from domain experts into dynamically generated analytical workflows. We demonstrate the annotation of unknown drug metabolites from public data guided by chemical hypotheses. The agent predicted, and we experimentally confirmed, a phosphorylated hydroxyzine, an acetaminophen-p-coumaric acid ester, and identified two new oxidative ibuprofen-carnitine conjugates from public repositories. These results demonstrate that LLM-driven agentic reasoning, when combined with domain expertise, can indeed generate experimentally testable structural hypotheses for previously uncharacterized metabolites leveraging pan repository data.

bioinformatics↗

bioRxiv2026

Learning interpretable structural similarity from tandem mass spectra for small molecule analog discovery

Analog discovery remains a central bottleneck in mass spectrometry-based untargeted metabolomics, as conventional spectral similarity scores poorly reflect molecular structure. We introduce SIMBA, a transformer-based model that infers two interpretable graph-based distances, maximum common edge subgraph and substructure edit distance, directly from tandem mass spectra. SIMBA consistently retrieves structurally closer analogs than existing methods, enabling structure-aware small molecule identification beyond exact spectral matching.

bioinformatics↗

bioRxiv2026

MALDI Tandem Mass Spectrometry for Colony-Based Dereplication of Natural Products

Microbial libraries remain an important resource for natural product discovery; however, constructing taxonomically and chemically diverse collections remains a challenge. Advances in dereplication strategies, including molecular networking, have reduced the rediscovery of known bioactive molecules and facilitated the identification of novel chemical scaffolds, but these approaches are typically applied after library construction or to existing repositories. Furthermore, many dereplication workflows require scaled fermentation and extraction, increasing the time needed to assess a microbes metabolite profile. Here, we integrate matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) into the bioinformatics platform IDBac, enabling streamlined characterization of microbial taxonomic identity, metabolite production potential, and preliminary metabolite annotation through GNPS2 molecular networking. This miniaturized high-content workflow facilitates strain prioritization by providing metabolite annotations directly from single microbial colonies prior to scale-up and extraction. Application of this approach to marine actinomycetes enabled the annotation of lavanducyanin and multiple napyradiomycin analogs. Subsequent investigation led to the discovery of napyradiomycin B8 from marine Streptomyces sp. CNZ-289, which was confirmed by 1D and 2D NMR spectroscopy and MALDI-MS/MS. Expanding this workflow to an untargeted analysis of 25 commensal marine vertebrate-derived bacterial isolates resulted in the annotation of several known bioactive natural products, including surugamides, antimycins, desferrioxamine siderophores, and the isolation and elucidation of harmane derivatives using NMR. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/733640v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@c92cfforg.highwire.dtl.DTLVardef@1a9522borg.highwire.dtl.DTLVardef@151b309org.highwire.dtl.DTLVardef@c1531f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Nanovibrational stimulation preferentially enhances osteogenic responses in zebrafish

Mechanical cues are key regulators of bone formation, yet their potential as therapeutic stimuli remains incompletely explored in vivo. Nanovibrational stimulation, which delivers low-amplitude, high-frequency mechanical input, has been shown to promote osteogenic differentiation in vitro, and rodent studies have similarly demonstrated osteogenic effects. However, its impact on other cellular systems at the whole-organism level remains poorly understood. Here, we demonstrate that nanovibrational stimulation enhances myogenic differentiation in vitro before investigating its effects on skeletal development and tissue specificity in zebrafish. Larval zebrafish exposed to nanovibrational stimulation exhibited increased osteoblast numbers and enhanced bone formation relative to controls. In adult zebrafish, nanovibration increased the osteoblast response to a fracture-like injury, indicating enhanced osteogenic activity during repair. To assess tissue specificity, we examined additional cell types and systems relevant to skeletal regeneration, including cartilage, muscle, vasculature and innate immune cells. Although nanovibrational stimulation promoted myogenic differentiation of C2C12 cells in vitro, its effects on muscle and other non-skeletal tissues in zebrafish larvae were comparatively limited. These findings suggest that nanovibrational stimulation exerts a preferential effect on osteogenic processes in vivo. These findings demonstrate that nanovibrational stimulation preferentially enhances osteoblast-mediated bone formation and skeletal injury responses in zebrafish, without causing significant perturbations in other tissues. Our results establish zebrafish as a tractable in vivo model for investigating vibration-induced mechanobiological processes, providing a more physiologically relevant representation of tissue-level mechanotransduction than conventional two-dimensional culture systems. Furthermore, these findings highlight the potential of nanovibrational stimulation as a non-invasive strategy to promote bone regeneration and fracture repair.

physiology↗

bioRxiv2026

Homeobox transcription factor MSX2 down-regulates ERα action to facilitate anti-estrogensensitivity in ERα+ breast cancer

Breast cancer is the most common malignancy among women worldwide. Estrogen receptor (ER)-positive breast cancer is about 70% in the total breast cancer. It has variable prognosis and high recurrent risk, frequently developing resistance to endocrine therapies. Herein, we have identified that a homeobox transcription factor MSX2 downregulated in ER-positive breast cancer is correlated with the advanced grade and poor survival outcomes. Our results have demonstrated that MSX2 interacts with ER to inhibit ER-mediated transactivation. Mechanistically, MSX2 associates with HDAC1/HDAC2 to form a protein complex. MSX2 is required for recruitment of HDAC1/HDAC2 complex to estrogen response elements (EREs) region on ER downstream target genes, reducing histone H3K9ac and H3K27ac levels to inactivate gene transcription. Functionally, ectopic expression of MSX2 suppresses cell growth and enhances the sensitivity to anti-estrogen treatment in ER-positive breast cancer cells. Our results indicate that MSX2 as a novel co-repressor of ER is involved in suppression of ER-positive breast cancer progression. Restoring MSX2 protein may provide a promising strategy to overcome endocrine resistance in ER-positive breast cancer.

Molecular Biology↗

bioRxiv2026

Functional orthogonality of WRN inhibitor resistance enables alternating therapy and mutation-tolerant inhibitor design in MSI-H cancers

Werner syndrome helicase (WRN) is a synthetic-lethal vulnerability in microsatellite instability-high (MSI-H)/mismatch repair-deficient (dMMR) cancers1-5, and non-covalent and covalent WRN inhibitors are now entering clinical development6-9. A central unresolved question is whether resistance to one WRN inhibitor class inevitably compromises the target, or instead creates actionable vulnerabilities to an alternate modality. Here we generated ten stable acquired-resistance models across three MSI-H cell lines using the non-covalent inhibitor HRO761 and the covalent inhibitor VVD-214. Whole-exome sequencing, biochemical reconstitution and isogenic knock-in models identified recurrent on-target WRN missense mutations as dominant resistance drivers, but with sharply modality-specific spectra: HRO761 resistance clustered at G729/F730/I852, whereas VVD-214 resistance concentrated at E846. These mutations impaired inhibitor engagement and abolished the canonical WRN inhibitor (WRNi)-induced pharmacodynamic cascade, including WRN reduction, DNA damage response (DDR) activation and G2/M arrest. Crucially, most resistance mutations retained biochemical, cellular and in vivo sensitivity to the alternate inhibitor modality, revealing a functional orthogonality that enabled a 7-day cyclic alternating regimen to delay tumour regrowth in xenografts. We further identified F730L as an engineered cross-resistant bottleneck model and used structure-guided, artificial intelligence (AI)-enabled optimization to generate GBA-007, a proof-of-concept mutation-tolerant WRN inhibitor candidate with promising activity against F730L in vitro and in vivo. Thus, clinically relevant WRN inhibitor classes impose distinct on-target resistance trajectories that can be exploited through schedule design, while cross-resistant bottlenecks can be addressed by rapid mutation-aware inhibitor engineering.

Cancer Biology↗

bioRxiv2026

EditorForge: An Active-Site-Aware Framework for Inverse-Folding-Based Protein Redesign

Inverse-folding models can rapidly generate protein sequences compatible with a supplied backbone, but unconstrained redesign is poorly suited to enzyme and genome-editor-associated domains, where catalytic, substrate-proximal, and conserved structural regions must remain protected. In this paper, we present EditorForge, a modular constraint-and-audit suite for editor-domain protein redesign that wraps fixed-backbone inverse folding with explicit design masks, fixed-position enforcement, active-site-proximity auditing, active-site-shielded regeneration, and downstream structural quality control. Using full-length Moloney murine leukemia virus reverse transcriptase structure 4MH8 (MMLV RT 4MH8) as a demonstration target, EditorForge first restricted redesign to a bounded 25-position envelope while fixing 428 residues. An initial audit detected active-site-proximal failure modes despite fixed-position integrity. Later, the Active Site Shield module then removed five unsafe design positions, replaced them with lower-contact alternatives, and regenerated candidates under stricter constraints. Post Shield Audit evaluated 24 regenerated candidates, all of which satisfied the hard sequence/mask and active-site-shield constraints. For the eight candidates that were selected or returned for structure-prediction/refolding quality control, Enhanced RefoldQC found that all 8 evaluated predicted structures passed the computational structure-QC screen. That said, the selected 8 candidates passed the computational structure-QC screen, with global C RMSD values of 1.2061-1.5555 {degrees}A, active-site C RMSD values of 0.4098-1.8397 {degrees}A, mutation-neighborhood C RMSD values of 1.3155-1.6848 {degrees}A, and average pLDDT-like confidence values of 94.87-95.11. In short, EditorForge provides a reproducible triage layer that converts general inverse-folding output into constrained and editor-specific candidate sets for downstream structural and biological review on top of existing structural prediction tools.

bioinformatics↗

bioRxiv2026

BTK inhibition enhances immunovirotherapy in glioblastoma via tertiary lymphoid structure modulation

Glioblastoma (GBM) is a highly aggressive type of glioma that is resistant to immunotherapy and is associated with poor prognosis, largely due to its immunosuppressive tumor microenvironment. Brutons tyrosine kinase (BTK) is a non-receptor kinase that not only plays an important role in oncogenic signaling, particularly in tumor growth, but also regulates the activity of tumor-infiltrating myeloid cells, including dendritic cells, macrophages, and microglia in brain tumors. High BTK expression is associated with poor survival in patients with glioma. Oncolytic herpes simplex virus type 1 (oHSV)-derived virotherapy, a novel treatment strategy, has demonstrated effectiveness against GBM; however, its efficacy is limited by the tumor microenvironment. In this study, we found that BTK is predominantly expressed in GBM-infiltrating myeloid cells. Intratumoral injection of oHSV not only promotes infiltration of myeloid cells and T cells but also activates BTK in these myeloid cells, thereby limiting oHSV infection and replication in tumor cells. Combination treatment with BTK inhibitor ibrutinib improves anti-tumor efficacy of oHSV in both human GBM12 xenograft and syngeneic murine GSC005 models. Mechanistically, BTK inhibition increases oHSV-mediated tumor cell death (cleaved caspase-3) and cytotoxic CD8 T cell infiltration, while decreasing tumor cell proliferation (Ki-67). BTK inhibition not only suppresses oHSV clearance by tumor-infiltrating microglia and macrophages but also reduces their pro-invasive effects on tumor cells. Addition of IDO inhibitor, an immune modulator, further prolongs survival in tumor-bearing mice in a syngeneic GBM model. Single-cell mRNA sequencing (scRNA-seq) analysis indicates that combination treatment modifies key signaling pathways in both tumor-infiltrating myeloid cells (macrophages and microglia) and CD8 T cells. Further analysis shows that BTK inhibition, with or without IDO inhibition, promotes the formation of tumor-infiltrating tertiary lymphoid structures (TLS) during intratumoral oHSV treatment, subsequently remodeling T cell, NKT cell, and monocyte-macrophage populations. These results indicate that BTK inhibition exerts multifaceted effects in enhancing the anti-tumor efficacy of oHSV therapy.

cancer biology↗

bioRxiv2026

CellClick: an interactive platform for adjustable and accurate cell type annotation in single-cell and spatial omics data

Single-cell omics and spatial omics technologies are nowadays widely used in biological and medical research. In both single-cell and spatial omics data analysis, accurate cell type annotation is a key step for downstream analysis and scientific discoveries. However, high-quality cell annotation usually requires multiple rounds of manual analysis for result refinement, which poses great challenges to most researchers. Here, we present CellClick, an interactive platform for convenient and accurate cell type annotation in single-cell and spatial omics data. CellClick provides Data Preprocessing, Data Visualization, Cell Annotation, Annotation Validation, and Cell Reannotation modules, which facilitate automatic or user-guided cell selection and annotation. The feasibility of using CellClick to generate more accurate cell annotation results was exemplified by both scRNA-seq and spatial transcriptomics data.

bioinformatics↗

bioRxiv2026

Identification of genes important for response of Pseudomonas aeruginosa biofilms to ciprofloxacin exposure

Pseudomonas aeruginosa is an opportunistic pathogen that can cause severe infections in immunocompromised individuals, such as patients with cystic fibrosis where it commonly forms biofilms. Ciprofloxacin is used extensively to treat P. aeruginosa infections, but its effectiveness can be significantly reduced due to biofilm formation. Although many individual genes associated with biofilm formation or ciprofloxacin resistance have been characterised, the genetic basis of P. aeruginosa biofilm fitness related to antibiotic challenge remains incompletely understood. In this study we employed a whole genome screen to assay the impact of gene disruptions or altered gene expression on survival of P. aeruginosa biofilms exposed to different concentrations of ciprofloxacin. Genes impacting fitness in the biofilm context were identified by comparing the biofilm samples to planktonic samples harvested at 12h, 24h and 48h with and without ciprofloxacin. Genes associated with c-di-GMP regulation and Gac/Rsm signalling were identified as primary regulators for biofilm formation in the presence and absence of ciprofloxacin. In addition, a group of genes involved in respiration, metabolism (especially polyamine metabolism), and various transporter and efflux systems were identified as important for biofilm fitness. Ciprofloxacin specifically imposed a selective pressure on flagellar function and Psl production which were essential for survival in early biofilms. Moreover, transposon insertions within the CPA gene clusters (PA5448-PA5451 and PA5455-PA5456) and the salvage peptidoglycan recycling pathway showed reduced fitness in late biofilms at high concentration of ciprofloxacin, indicating that cell envelope integrity is beneficial for mature biofilms. This study identifies important determinants of survival for biofilms at different stages of maturity in the presence and absence of ciprofloxacin and implicates potential therapeutic targets for antibiofilm drug development.

genomics↗

bioRxiv2026

An LSEC-focused computational drug repurposing platform for liver fibrosis: Identification of vorinostat and other LSEC-protective candidates

Liver sinusoidal endothelial cells (LSECs) are increasingly recognized as a critical yet underexplored cell type in anti-fibrotic drug development. This study presents a computational drug screening platform integrating LSEC-specific transcriptomic analysis across simple steatosis, fibrotic nonalcoholic steatohepatitis (NASH), and cirrhosis, with tiered gene signature selection combining machine learning, large language model-assisted curation, gene safety assessment, and Connectivity Map-based screening using human endothelial perturbational profiles. The platform identifies 6 clinical-stage and 8 preclinical candidates with LSEC-protective potential. Among these, vorinostat (SAHA), a clinically approved histone deacetylase (HDAC) inhibitor, is selected for experimental validation. In hepatocyte-specific Asah1-deficient mice fed a Paigen diet, SAHA attenuates hepatic inflammation, fibrosis, LSEC dysfunction, and portal hemodynamic abnormalities, with effects confirmed in a hepatotoxin (CCl4)-induced fibrosis model. High mobility group box 1 (HMGB1) is identified as a key hepatocyte-derived paracrine mediator of LSEC injury through Transwell co-culture and glycyrrhizin rescue. Vorinostat dose-dependently reverses HMGB1-induced LSEC dysfunction across inflammation, capillarization, fibrogenesis, and vasoconstriction, associated with endothelial transcription factor reprogramming including KLF2 upregulation, validated in primary LSECs and in vivo. SAHA also protected LSECs from TNF--induced inflammation and reduced monocyte adhesion. These findings establish an LSEC-focused drug repurposing framework and identify candidates for LSEC-protective anti-fibrotic therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/727430v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@41e95dorg.highwire.dtl.DTLVardef@1401031org.highwire.dtl.DTLVardef@e72fc4org.highwire.dtl.DTLVardef@1f11347_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Nipoppy: A framework for standardizing neuroimaging studies to facilitate international derived-data sharing

Neuroimaging data management and processing are tedious and error-prone, prompting reproducibility concerns. Globally, studies with heterogeneous infrastructure and governance policies lead to eclectic data processing and sharing, necessitating standardization of data workflows to ensure reusability and comparability of multi-centric datasets. The Nipoppy neuroinformatics framework facilitates such standardization by combining specification, protocol, and software to manage study-level data workflows. With its adoption, researchers can share standardized, derived datasets enabling efficient, reproducible, and inclusive research.

bioinformatics↗

bioRxiv2026

Kinemomics: spatiotemporal morphodynamic mapping of ventricular kinematic subpopulations in organotypic fetal heart slices

Recent advancements in omics technologies have deepened our understanding of complex biological systems and the interplay among gene expression, mechanical cues, and cellular metabolism. However, capturing the spatiotemporal dynamics of live cellular behavior within intact tissue contexts remains a major challenge. Here, we introduce Kinemomics, a framework for spatiotemporal mapping of morphogenetic kinematic states in living tissue. Using a novel fetal cardiac organotypic slice culture system that preserves both beating and morphogenesis, Kinemomics integrates live fluorescent labeling, timelapse imaging, and endpoint immunofluorescence to generate morphodynamic profiles across full-thickness developing myocardium. We validate Kinemomics under controlled Yap-1 signaling perturbations and demonstrate its ability not only to intrinsically decode region- and treatment-specific phenotypes, but also to resolve their spatiotemporal evolution during development and malformation. Kinemomics further reveals localized emergent developmental and malforming fronts that drive system-level behavior, establishing a generalizable platform for investigating computational morphodynamics and cross-scale interactions in complex spatiotemporal systems.

developmental biology↗

bioRxiv2026

A Small-Molecule Mitochondrial Complex I Modulator Improves Behavioral and Mitochondrial Dysfunction in Schizophrenia

Weak inhibition of mitochondrial complex I (mtCI) has been shown to have neuroprotective effects in cellular and animal models of Alzheimers and Huntingtons diseases, at least in part by enhancing mitochondrial biogenesis and function. Mitochondrial dysfunction has also been demonstrated in schizophrenia patients and mouse models of schizophrenia. We tested whether weak inhibition of mtCI would ameliorate mitochondrial and behavioral phenotypes in a mouse model of schizophrenia. In mice with four copies of the Gldc gene, 8 weeks of treatment with the weak mtCI inhibitor, the small-molecule tricyclic pyrone compound CP2, reversed spontaneous alternation deficits in the Y maze, startle habituation deficits, and social novelty deficits in the three-chamber social interaction test. Consistent with the mechanism of action, Western blots revealed that CP2 reverses the reduced expression of PGC-1, a master regulator of mitochondrial biogenesis, and of the VDAC1, a primary gatekeeper for the exchange of metabolites, ions, and ATP between mitochondria and the cytosol. These findings suggest that the improvement of mitochondrial function may represent a novel strategy to reverse pathophysiological and behavioral deficits in schizophrenia.

neuroscience↗