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At least 19 recordsLinked to original sources

PubMed2026

Loss of the Mechanistic Target of Rapamycin Complex 1 Causes a Lethal Alpha-1 Antitrypsin Deficiency-Associated Liver Disease.

BACKGROUND & AIMS: SERPINA1 mutations cause retention of the otherwise secreted alpha-1 antitrypsin and lead to the proteotoxic alpha-1 antitrypsin deficiency-related liver disease. As mechanistic target of rapamycin is a key coordinator of proteostasis, we studied its role in alpha-1 antitrypsin deficiency-related liver disease. METHODS: PiZ mice overexpressing the characteristic SERPINA1 mutation were mated with rodents harboring a hepatocyte specific-ablation of the interaction partners regulatory-associated protein of mechanistic target of rapamycin or rapamycin-insensitive companion of mammalian target of rapamycin, corresponding to mechanistic target of rapamycin complexes 1 or 2, or with mice lacking mechanistic target of rapamycin. Serum proteomics, liver bulk proteomics, spatial proteomics, and metabolomics were applied to characterize molecular and metabolic alterations. RESULTS: At 2 months of age, PiZ-mTORΔhep and PiZ-RaptorΔhep but not PiZ-RictorΔhep mice showed signs of increased liver injury and mortality despite diminished hepatic alpha-1 antitrypsin accumulation. PiZ-RaptorΔhep animals displayed increased levels of the proapoptotic protein C/EBP homologous protein, but C/EBP homologous protein ablation did not rescue the phenotype. Serum proteomics revealed no signs of advanced synthetic liver failure but immature hepatocellular products. Liver bulk proteomics and small metabolite measurement demonstrated a metabolic reprogramming of PiZ-RaptorΔhep mice. Spatial proteomics revealed alterations in liver zonation with increased ammonia levels as the likely cause of death in PiZ-RaptorΔhep animals. CONCLUSIONS: In summary, in alpha-1 antitrypsin deficiency-related proteotoxic liver injury, regulatory-associated protein of mechanistic target of rapamycin preserves a liver zonation, thereby protecting from lethal metabolic dysregulation.

Animals↗

PubMed2025

BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights.

Despite the advent of mechanistic toxicology using omics data to link molecular perturbations with systemic outcomes, regulatory toxicology still lacks the application of mechanism-anchored metrics from such data. This is partially because traditional gene-centric analysis often falls short of linking molecular changes to adverse outcomes. To address this gap, BMDx2, an open-source tool that transforms multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for human chemical safety assessment is developed. BMDx2 couples benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment to derive transcriptomic-based points of departure, enabling potency ranking, chemical prioritization, and mechanistically anchored explanations of the effect of chemical exposures. BMDx2 can process a broad range of data, including DNA microarray and RNA sequencing studies. Here, case studies are used to illustrate the versatility of BMDx2 in characterizing the mechanism of action of chemicals. An initial case study on carbon nanotubes exposure applies integrative analysis of transcriptomics and genome-wide DNA methylation data, uncovering cellular reprogramming processes underlying fibrosis. A second case study on bleomycin exposure demonstrate how transcriptomic data alone can be mapped to fibrosis-related AOPs in a standardized, regulatory appropriate manner. Together, these examples show how BMDx2 supports the regulatory application of toxicogenomics and accelerates mechanism-based chemical safety evaluation.

Toxicogenetics↗

PubMed2026

Mechanistic Insights Into the Association Between Gut Microbiota Diversity and Atherosclerosis, Acute Coronary Syndrome, and Peripheral Arterial Disease Progression.

BACKGROUND: The gut microbiome has emerged as a potential contributor to cardiovascular diseases (CVDs), including atherosclerosis, acute coronary syndrome (ACS), and peripheral arterial disease (PAD). While observational studies link dysbiosis to CVD, causal relationships remain uncertain. METHODS: This narrative review synthesizes evidence from human observational studies, clinical interventions, and experimental models to distinguish association from mechanistic plausibility and clinical causality. Literature was searched through July 2026 in PubMed/MEDLINE, Web of Science, and Scopus. RESULTS: Microbial metabolites-including trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs), bile acids, and lipopolysaccharide (LPS)-modulate endothelial function, immune cell programming, platelet activity, and plaque stability through receptor-mediated signaling and epigenetic regulation. SCFAs demonstrate potentially protective effects via GPCR and HDAC pathways, while TMAO is associated with atherothrombotic risk. However, much mechanistic evidence derives from preclinical studies. Heterogeneity from diet, geography, host characteristics, renal function, and medications substantially influences microbiota-CVD associations. CONCLUSION: The gut-vascular connection is biologically plausible, but definitive clinical causality remains unproven. Microbiome-directed therapies (dietary modulation, pre/pro/synbiotics, targeted metabolite inhibition) are investigational. Prospective, standardized, adequately powered human studies with clinically meaningful outcomes are essential before routine cardiovascular application.

Gastrointestinal Microbiome↗

PubMed2026

Mechanistic insights into Claudin-14 dysfunction implicated in veins of Galen malformation.

Claudin-14 (CLDN14) is a key component of tight junctions (TJs) critical for maintaining paracellular barrier function. Variants of CLDN14 have been linked to Vein of Galen malformations (VOGMs), a rare cerebrovascular disorder; however, the molecular mechanisms underlying their pathogenicity remain unknown. Here, we investigate the mechanistic effects of two VOGM-associated mutations, A113P and V143M, using reinforcement-learning driven enhanced sampling molecular dynamics simulations combined with DiffNets-based deep learning and independent trajectory-wide structural analyses. Our analysis reveals that A113P induces broader structural disruption of CLDN14, perturbing paracellular sealing, pore symmetry, and inter-protomer communication, whereas V143M induces structural rearrangements centred around TM3 and the TM3-ECL2 region. In both cases, mutation-specific alterations are observed in structural stability and interfacial organization across oligomeric assemblies. Notably, these effects are qualitatively consistent across different modelled architectures, despite variability in local responses. In the absence of experimentally resolved structures, the structural perturbations reported here provide a mechanistic understanding of how VOGM-associated variants may influence CLDN14 structure and dynamics.

Aneurysm↗

PubMed2026

Antibody diversification in cartilaginous fishes: Mechanistic insights from the nurse shark and comparative perspectives across jawed vertebrates.

Antibody diversity in vertebrates arises through the coordinated actions of V(D)J recombination and somatic hypermutation (SHM). Cartilaginous fishes occupy a key phylogenetic position as the sister lineage to bony vertebrates and therefore provide important comparative insights into the evolution of adaptive immunity. This review focuses on the nurse shark (Ginglymostoma cirratum) as a representative model for examining antibody-diversification mechanisms in cartilaginous fishes. Shark immunoglobulin genes exhibit a multicluster organization, while immunoglobulin new antigen receptor (IgNAR), a heavy-chain-only isotype, contains a single variable domain with an extended complementarity-determining region 3 (CDR3) that can be stabilized by non-canonical disulfide bonds. These structural features, together with intracluster multi-D V(D)J recombination and distinctive SHM characterized by single and tandem substitutions and insertions/deletions, contribute to antibody diversification in sharks. By comparing cartilaginous fishes, ray-finned fishes, and mammals, this review highlights lineage-specific combinations of immunoglobulin gene organization, recombination, mutational processing, and affinity maturation. Within the heuristic framework proposed here, shark and mammalian systems are described as emphasizing "breadth-first" repertoire generation and "precision-first" affinity optimization, respectively. These terms indicate relative mechanistic emphases rather than mutually exclusive categories or sequential evolutionary stages, while ray-finned fishes exhibit a distinct combination of genomic organization and mutational features. Investigating antibody diversification in cartilaginous fishes not only advances our understanding of vertebrate immune evolution but also provides structural and mechanistic insights that may inform the development of engineered antibodies based on the IgNAR scaffold.

Antibody diversity↗

PubMed2026

Structural complexity and mechanistic diversity of MECOM rearrangements in myeloid neoplasms.

Rearrangements involving MECOM at chromosome 3q26.2 are recurrent in myeloid neoplasms, classically represented by inv(3)(q21q26.2) and t(3;3)(q21;q26.2), which reposition the GATA2-distal haematopoietic enhancer and drive aberrant EVI1 overexpression. However, the full structural and mechanistic diversity of MECOM rearrangements (MECOM-r) is yet to be explored. We retrospectively analysed 97 cases with cytogenetically defined MECOM-r and identified 12 with complex rearrangements using GTG-banded karyotyping and tri-colour interphase/metaphase fluorescence in situ hybridisation analyses. These 12 cases demonstrated remarkable structural heterogeneity. The abnormalities encompassed translocations, inversions, insertions, duplications, and deletions, which often coexisted within the same specimen as multiple rearranged subclones. Insertional events emerged as a distinct mechanism of MECOM activation. These encompassed insertions of MYNN and/or MECOM into chromosomes 1 and 6, insertion of chromosome 8 segment into MECOM, and inverted insertions between homologous chromosome 3 segments. Recurrent breakpoints at 3q21 across multiple cases, together with localised copy number imbalances frequently involving the MYNN and GOLIM4 loci at 3q26.2, underscore the architectural fragility of these two regions. Co-occurring abnormalities such as -5/del(5q), -7/del(7q), and TP53 loss were common, reflecting a permissive genomic background for chromosomal reassembly. Our findings expand the mechanistic landscape of MECOM-r beyond canonical inv(3)/t(3;3), establishing 3q21 and 3q26.2 as structural 'hotspots' and genomic instability hubs. Distinct from fusion-driven oncogenes such as KMT2A, MECOM activation results from enhancer hijacking and regional structural remodelling, leading to EVI1 overexpression and clonal evolution in myeloid malignancies.

Humans↗

PubMed2026

Proteomic analysis of pancreatic endocrine cells by mechanistic single-cell isolation identifies membrane pathways.

To better understand diabetes and normoglycemia, pancreatic islet biology requires a precise molecular understanding of islet cell types at both the transcriptomic and proteomic levels. While transcriptomic analyses are well established, comprehensive proteomic characterization has been lacking, limiting our knowledge of islet molecular complexity. Here we introduce a nonenzymatic, mechanistic single-cell isolation technology using laser microdissection (LMD7), facilitating proteomic and transcriptomic analysis of physically isolated α-, β- and δ-cells from fresh-frozen, unfixed pancreatic tissue. This mechanistic approach avoids enzymatic digestion and chemical fixation, preserving the cells' native molecular state before processing. Given the limited existing proteomic data, we supplemented our findings with transcriptomic analysis generated using the same method and compared our results with data from enzymatically isolated cells, obtained by fluorescence-activated cell sorting and compiled by others. Our analysis revealed that enzymatic digestion alters gene expression patterns, particularly those of membrane-associated proteins, underscoring the impact of isolation techniques on biological outcomes. We identified cell-type-specific proteins typically underrepresented in pancreatic single-cell transcriptomic datasets. β-cells exhibited enrichment in vesicle trafficking proteins, α-cells displayed distinct calcium-dependent action potential machinery and δ-cells showed elevated expression of focal adhesion-related proteins. In addition, we report an inverse molecular relationship between β- and δ-cells, potentially driven by transcriptional regulators such as Mlxipl. By establishing robust molecular profiles directly from intact pancreatic tissue, this work provides a reference point for future pathological comparisons, offering a framework to investigate how diabetes and other endocrine disorders reshape islet cell biology.

Journal Article↗

PubMed2026

Knowledge-driven interpretable neural networks provide mechanistic insight.

Analyzing omics data in the context of pathway knowledge is critical for understanding the molecular mechanisms underlying pathological changes. However, current pathway analysis methods do not model the detailed mechanistic nature of biological interactions, limiting the understanding of pathway behavior to a relatively shallow level. To address this issue, we present a knowledge-driven machine learning framework that embeds features into pathway graphs and models reactions analytically, producing interpretable feature hierarchies and subnetworks in which functional associations are estimated to model biological interactions. The approach is agnostic to feature selection, enabling the use of full omics data sets without discarding weak signals. Applications to breast cancer microRNA-gene regulation data and COVID-19 metabolomic data highlight immune and metabolic pathways relevant to disease progression. This framework bridges predictive modeling with mechanistic interpretation and offers a foundation for integrative pathway analysis.

Humans↗

PubMed2026

Arginine-substituted Mastoparan-C derivatives combat dual bacterial pathogens: in vitro mechanistic insights and in vivo efficacy in polymicrobial wounds.

UNLABELLED: The synergistic interactions in multi-pathogen infections compromise wound healing and limit therapeutic efficacy. In this study, we designed and synthesized arginine-substituted derivatives of the antimicrobial peptide Mastoparan-C (MP-C). Among them, Arg²MP-C and Arg4.11.12MP-C exhibited potent, broad-spectrum activity against both Escherichia coli and Staphylococcus aureus. Their enhanced antibacterial activity is associated with increased positive charge and optimized hydrophobicity. Mechanistically, both peptides employ a dual-target strategy, disrupting bacterial membranes and binding genomic DNA; Arg²MP-C acted most rapidly against the E. coli envelope, while Arg4.11.12MP-C caused the strongest membrane damage to S. aureus. In a murine polymicrobial wound model, Arg²MP-C treatment nearly achieved complete wound closure by day 10, significantly reduced bacterial loads, and promoted tissue regeneration. This study demonstrates that arginine engineering can yield peptides with potent, multi-mechanistic action, identifying Arg²MP-C as a promising candidate for combating polymicrobial wound infections. IMPORTANCE: Wounds infected with multiple bacterial species are notoriously difficult to treat, often leading to poor healing and limited effectiveness of existing therapies. In this study, we developed new antimicrobial peptides by introducing arginine substitutions into a natural peptide called Mastoparan-C. Two of our engineered peptides, Arg²MP-C and Arg4.11.12MP-C, showed potent activity against two common wound pathogens, Escherichia coli and Staphylococcus aureus. These peptides work through a dual mechanism: disrupting bacterial membranes and binding to bacterial DNA. In a mouse model of mixed-infection wounds, treatment with Arg²MP-C led to nearly complete wound closure by day 10, drastically reduced bacterial counts, and promoted tissue repair. Our findings highlight arginine engineering as a promising strategy to create next‑generation antimicrobial agents that can effectively combat complex polymicrobial wound infections, addressing a critical unmet need in clinical wound care.

Animals↗

PubMed2026

Digenic HNF1A and ABCC8 variants provide mechanistic insight into early-onset diabetes.

CONTEXT: Oligogenic inheritance in maturity-onset diabetes of the young (MODY) remains poorly characterized, and the contribution of multiple candidate variants to disease pathogenesis is incompletely understood. OBJECTIVE: To investigate the pathogenicity and mechanistic contribution of multiple MODY gene variants identified in a MODY-like family and determine their role in early-onset diabetes. METHODS: Comprehensive genetic analysis of known MODY genes was performed in a MODY-like family. Functional effects of HNF1A and HNF1B variants were assessed using luciferase reporter assays in HEK293T cells. Functional characterization of ABCC8 variants included Kir6.2-dependent thallium (Tl+) flux assays, sulfonylurea responsiveness, and channel stability. RESULTS: Four variants in 3 MODY genes were identified in the proband: novel HNF1A p.Ser551Lysfs*2, HNF1B p.Glu102Ala, and ABCC8 p.Arg298Cys and p.Arg521Gln. Functional analysis showed that HNF1A p.Ser551Lysfs*2 retained approximately 5% of wild-type transactivation activity, consistent with loss-of-function, whereas HNF1B p.Glu102Ala and ABCC8 p.Arg521Gln exhibited wild-type-like function. In contrast, ABCC8 p.Arg298Cys reduced channel activity to 77% of wild-type levels while preserving sulfonylurea responsiveness. Segregation analysis identified HNF1A p.Ser551Lysfs*2 and ABCC8 p.Arg298Cys in affected parents. The proband, who inherited both pathogenic variants, developed diabetes earlier than either parent and was exposed to maternal hyperglycemia in utero, which may also have contributed to this early onset. CONCLUSION: Functional characterization distinguishes pathogenic from variants of unknown significance and supports digenic inheritance of HNF1A and ABCC8. Their additive effects, together with intrauterine hyperglycemia, likely accelerated disease onset. This study provides mechanistic evidence for oligogenic contributions to MODY and expands the genetic architecture of early-onset diabetes.

Humans↗

PubMed2026

A minimal three-arm oral regimen for healthspan: mechanistic alignment with transcriptomic signals from a large parental-lifespan GWAS.

A large genome-wide association study of parental lifespan was reported in 2019. A later transcriptome-wide association study (TWAS) based on those summary statistics identified a set of transcriptional programs associated with longer genetically predicted survival, including increased brain NAD + salvage, especially NMNAT2, reduced glucose-stimulated insulin secretion, a shift toward synaptic pruning with less broad plasticity, and a glial pattern characterized by relatively greater microglial and lower astrocytic signatures, with only weak pan-tissue senescence signals. Building on those directional findings, this short communication proposes a minimal three-arm oral regimen with unequal evidentiary weight: first, the Cheung Glutamatergic Regimen, consisting of low-dose dextromethorphan potentiated by a CYP2D6 inhibitor together with piracetam and L-glutamine, as an exploratory adjunct aimed at preserving residual functional connectivity; second, daily nicotinamide mononucleotide and N-acetylcysteine with pulsed senolytics for NAD + salvage and senescence modulation; and third, GLP-1 receptor agonism for metabolic reprogramming. The NAD+/senescence arm is the primary mechanistic anchor, GLP-1 receptor agonism provides secondary metabolic support, and the glutamatergic arm is exploratory. Each arm targets a separate node within the pruning-plasticity-metabolic triad. The regimen is fully oral, uses conservative dosing, and draws on prior therapeutic or human-exposure data, although the proposed combination has no established safety profile. Although direct combination data are lacking and the foundational TWAS remains a preprint, the components show plausible but uneven mechanistic alignment with the TWAS signals and may justify carefully designed, safety-focused pilot evaluation.

GLP-1↗

PubMed2026

Mechanistic Perspectives From Genomics and Pangenomics of Medicinal and Aromatic Plants: Linking Genome Architecture to Phytochemical Diversity.

Medicinal and aromatic plants (MAPs) produce a remarkable diversity of specialized metabolites with significant pharmaceutical, nutraceutical, and industrial value. Although advances in long-read sequencing, chromosome-scale genome assembly, and pangenomics have greatly expanded genomic resources, the mechanistic links between genome architecture and phytochemical diversity remain incompletely understood. The present review synthesizes current evidence describing how structural genomic variation may contribute to phytochemical diversity, while acknowledging that many proposed genome-to-metabolite relationships require further experimental validation. Examples illustrate how genome architecture is associated with specialized-metabolite biosynthesis through multiple regulatory processes. However, the strength of supporting evidence varies considerably among MAP species. Moreover, relatively few genome-to-metabolite relationships have been confirmed through direct functional validation. We further discuss how pangenomics, multiomics integration, genome editing, synthetic biology, and artificial intelligence support the discovery, validation, and engineering of specialized metabolic pathways. Casual conclusions are evaluated according to the strength of available evidence, highlighting where causal relationships have been experimentally established and where conclusions remain primarily association-based. Overall, this review provides an integrated conceptual and evidence-based perspective summarizing proposed relationships between genome architecture and phytochemical diversity and outlines future priorities for functional genomics, precision breeding, metabolic engineering, and sustainable utilization of MAPs.

artificial intelligence↗

PubMed1978

Kinetics of enzymatic hydrolysis of cellulose: analytical description of a mechanistic model.

A generalized mechanistic model for the enzymatic hydrolysis of cellulose is developed and expressed mathematically. The model is based on Michaelis--Menten-type kinetics for concurrent random and endwise attack of the substrate involving end-product inhibitions and three types of enzymes: an endo-beta-1,4-glucanase, an exo-beta-1,4-glucanase, and beta-glucosidase. Basic parameters of the model which can explain synergistic and other effects observed experimentally are quantified and discussed. It is shown that cellulose degradation kinetics are expected to be strongly affected by the ratio of endo- to exocellulases in the reaction mixture as indicated by previous experimental data, and the substrate degree of polymerization, a factor not fully appreciated in previous studies, which appear to be overridingly important in many practical cases.

Cellulase↗

PubMed1979

Mechanistic and quantitative evaluation of precorneal pilocarpine disposition in albino rabbits.

The low ocular bioavailability of topically applied pilocarpine is attributed to extensive precorneal drug loss in conjection with the resistance to corneal penetration. Several elements of precorneal loss were reported earlier, but a complete mechanistic understanding has not been available. The present study was designed to gain a better understanding of the mechanisms governing pilocarpine disposition in the precorneal areas as well as the relative influence of these parameters on ocular drug bioavailability. Radioactive pilocarpine and glycerin solutions were instilled into the precorneal area of the albino rabbit eye under various experimental conditions, and the drug concentration in the lacrimal lake was monitored as a function of time. The results demonstrated that nonconjunctival loss of pilocarpine, vasodilation due to the drug, and lacrimation due to vehicle formulation are additional aspects of precorneal drug disposition. The individual influence of all precorneal loss parameters on drug bioavailability was then assessed using a mathematical model formulated from experimental findings on both precorneal and intraocular drug disposition. Drainage and vasodilation, as well as nonconjunctival pilocarpine loss, exerted major influences on drug loss at the absorption site.

Administration, Topical↗

PubMed2026

Fungi to the rescue: recent advances, mechanistic insights and omics-based perspectives in heavy metal mycoremediation.

Heavy metal (HM) contamination arising from rapid industrialization poses critical threats to global ecosystem integrity and public health. Conventional physicochemical approaches are limited by high costs, incomplete removal, and toxic waste generation, necessitating sustainable alternatives. Mycoremediation, which harnesses the remarkable, diverse capacities of fungi to tolerate and mitigate HM stress through sophisticated biological mechanisms, has emerged as a promising and sustainable approach to address HM pollution. This review examines the sources and ecotoxicological impacts of HM pollution, alongside the intracellular and extracellular mechanisms underlying fungal tolerance and removal, including biosorption, precipitation, membrane transport, antioxidant defense, chelation, bioaccumulation, and biotransformation. It further synthesizes fungal-based bioremediation strategies, while examining how metagenomic, metatranscriptomic, transcriptomic, proteomic, and metabolomic approaches are advancing understanding of fungal community structure and active detoxification pathways. This work uniquely integrates community- and isolate-level multi-omics data, explicitly bridges mechanistic understanding with omics-driven insights, and extends this into translational roadmap for applied bioremediation.

Biodegradation, Environmental↗

PubMed2026

PTBP1 at the host-virus interface: mechanistic roles in viral RNA translation, replication, and immune modulation.

Viruses require the involvement of host RNA binding proteins for completion of important steps of their life cycle. Polypyrimidine tract binding protein 1 (PTBP1) is an RNA-binding protein found ubiquitously which performs important regulatory functions like alternative splicing, RNA stability, RNA localization, and translation by virtue of its four RRMs and shuttling between nucleus and cytoplasm. There is increasing evidence showing that many viruses make use of such regulatory roles of PTBP1 to facilitate their gene expression and replication. This review describes the existing mechanistic knowledge about the PTBP1 functions during viral infection, paying attention to the role of PTBP1 in viral RNA translation, viral RNA genome replication, and regulation of host antiviral response. Special attention is paid to the regulation by PTBP1 of IRES-dependent translation of enteroviruses and hepatitis C virus, as well as to the PTBP1 contribution to RNA stabilization, long-distance RNA interactions, and genome cyclization of flaviviruses such as dengue virus and Japanese encephalitis virus. Recent data on the PTBP1 function in coronavirus RNA metabolism are discussed as well. Furthermore, the role of PTBP1 in being both proviral and antiviral is reviewed in terms of innate immunity signalling pathways, stress granule biology, and virus-host interaction. Finally, we will explore the possibility of PTBP1 being used as a host-directed antiviral drug target despite the hurdles in doing so considering its multifunctionality as an essential cellular RNA-binding protein.

Polypyrimidine Tract-Binding Protein↗

PubMed2026

Antibacterial activity and mechanistic insights of Lucilia illustris antimicrobial peptide Cecropin A2 against Pseudomonas aeruginosa.

Pseudomonas aeruginosa (P. aeruginosa) poses a serious public health threat due to multidrug resistance and biofilm formation. This study investigated the antibacterial mechanisms of the antimicrobial peptide, Cecropin A2 (CA2), against P. aeruginosa. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of CA2 against P. aeruginosa ATCC 9027 (PA ATCC 9027) were determined by broth microdilution. Antibacterial activity was evaluated using growth curves and time-kill assays. The mechanism was explored by assessing membrane integrity (outer/inner membrane permeability, SEM, and fluorescence microscopy), and intracellular responses (ATP, SDH activity, and ROS). Biofilm effects were assessed by crystal violet staining (biomass) and viable cell counting (biofilm-embedded bacteria). The MIC and MBC of CA2 against PA ATCC 9027 were 37.34 μM and 74.68 μM, respectively. CA2 exhibited moderate antibacterial activity against PA ATCC 9027. Scanning electron microscopy (SEM) revealed marked morphological damage after treatment. CA2 affected intracellular metabolism, potentially interacted with genomic DNA, and reduced biofilm biomass. Cecropin A2 exhibits concentration-dependent in vitro antibacterial activity against P. aeruginosa ATCC 9027, providing mechanistic insights and a theoretical basis for the development of alternative antimicrobial strategies.

Antimicrobial activity↗

PubMed2023

Towards mechanistic models of mutational effects: Deep learning on Alzheimer's Aβ peptide.

Deep Mutational Scanning (DMS) has enabled multiplexed measurement of mutational effects on protein properties, including kinematics and self-organization, with unprecedented resolution. However, potential bottlenecks of DMS characterization include experimental design, data quality, and depth of mutational coverage. Here, we apply deep learning to comprehensively model the mutational effect of the Alzheimer's Disease associated peptide Aβ42 on aggregation-related biochemical traits from DMS measurements. Among tested neural network architectures, Convolutional Neural Networks and Recurrent Neural Networks are found to be the most cost-effective models with high performance even under insufficiently-sampled DMS studies. While sequence features are essential for satisfactory prediction from neural networks, geometric-structural features further enhance the prediction performance. Notably, we demonstrate how mechanistic insights into phenotype may be extracted from the neural networks themselves suitably designed. This methodological benefit is particularly relevant for biochemical systems displaying a strong coupling between structure and phenotype such as the conformation of Aβ42 aggregate and nucleation, as shown here using a Graph Convolutional Neural Network (GCN) developed from the protein atomic structure input. In addition to accurate imputation of missing values (which here ranged up to 55% of all phenotype values at key residues), the mutationally-defined nucleation phenotype generated from a GCN shows improved resolution for identifying known disease-causing mutations relative to the original DMS phenotype. Our study suggests that neural network derived sequence-phenotype mapping can be exploited not only to provide direct support for protein engineering or genome editing but also to facilitate therapeutic design with the gained perspectives from biological modeling.

Alzheimer's disease↗