Bryan A. Krantz

Single-molecule protein sequencing promises to democratize clinical proteomics, but platforms retrofitting static DNA-sequencing nanopores face a fundamental biophysical bottleneck: they only measure one-dimensional excluded volume. Consequently, these static calipers struggle to resolve isobaric residues, requiring complex DNA-handle chemistries and target concentrations that exceed clinically relevant abundance ranges. Here, we introduce a dynamical, target-docking translocase engine--the anthrax toxin protective antigen (PA)--as a label-free single-molecule peptide sensor. By extracting the multi-state thermodynamic friction generated as the pore's active site dynamically "breathes" around translocating analytes, we trained a physics-informed machine learning (PIML) architecture to classify a 20-member guest-host peptide library panel representing all 20 canonical amino acids at the single-event level. Operating at low nanomolar concentrations under a 35-millisecond thermodynamic read constraint, the translocase resolved isobaric variants (leucine and isoleucine). Furthermore, we achieved 98.02 (+/-0.05)% classification accuracy on a panel of five un-tagged, native clinical biomarkers (e.g., KRAS G12D, angiotensin, bradykinin). Transitioning from static volumetric measurement to time-domain thermodynamic fingerprinting establishes the requisite protein nanopore hardware for de novo proteomics.

Historic epidemiological studies have long observed a paradoxical resistance to solid tumors in cohorts with severe psychiatric conditions, such as schizophrenia (SCZ), despite higher prevalences of lifestyle risk factors. Concurrently, oncology has established that solid tumors utilize Warburg glycolysis to generate a “lactate shield,” binding the HCAR1 receptor on infiltrating macrophages to suppress immune proliferation. Here, we identify the shared genomic etiology resolving this paradox. Utilizing cross-trait genome-wide association studies (GWAS), we demonstrate that solid tumors exhibit an absolute mutational avoidance (a “statistical desert”) at the HCAR1 locus, relying entirely on the host’s intact baseline receptor for immune evasion. By contrast, the SCZ cohort harbors massive structural variance at this exact 3’ regulatory enhancer for HCAR1 . Cross-referencing SCZ risk alleles against pan-UK Biobank oncology data reveals profound antagonistic pleiotropy: the identical HCAR1 enhancer fractures driving psychotic susceptibility mathematically reduce the risk of colorectal, breast, and melanoma cancers. We propose that the SCZ mutational burden renders peripheral macrophages transcriptomically “lactate blind,” preventing the tumor from engaging the immune brake and effectively conferring a hardcoded, genetic immunotherapy against solid malignancies.

The advent of single-molecule nanopore sequencing established a powerful platform for modern genomics by using static biological pores to report the translocation of canonical nucleic acids, enabling rapid, accessible nucleic acid analysis. However, extending this strategy to single-molecule proteomics has stalled against a fundamental biophysical bottleneck. Current efforts in nanopore proteomics attempt to retrofit these static, spatial “caliper” biological nanopores (e.g., α-hemolysin, MspA, CsgG, aerolysin) for protein sequencing despite the immense steric, charge, and conformational heterogeneity of proteins. Unlike the chemically uniform, polyanionic phosphodiester backbone of DNA, the proteome contains isosteric and isobaric variants that confound purely volumetric measurements made by static pores. To address this bottleneck, we propose the application of dynamical translocases – naturally evolved, protein-handling nanomachines (e.g., the anthrax toxin protective antigen). Unlike static pores that rely on passive diffusion, dynamical translocases employ target-docking clamp architectures that achieve low nanomolar sensitivity. Active-site conformational dynamics generate high-dimensional kinetic fingerprints that enable molecular discrimination during translocation. By coupling dynamical translocases with Physics-Informed Machine Learning (PIML), we demonstrate that amino-acid side-chain-dependent thermodynamic friction can be mathematically decoded, enabling >90% accurate classification of chemically distinct amino acid classes and doing so label-free without the artificial DNA-handles required by legacy platforms.

Multiple Sclerosis (MS) pathogenesis is contingent upon the hyper-proliferative infiltration of peripheral macrophages across the blood-brain barrier. While front-line therapeutics, such as Dimethyl Fumarate, achieve clinical efficacy by agonizing the HCAR2 immune cooling switch, the tandemly duplicated HCAR1 lactate sensor has remained entirely unexplored. Here, by cross-referencing MS and Schizophrenia (SCZ) genomic architectures, we identify a massive shared structural fracture strictly localized to the HCAR tandem regulatory domain. We demonstrate that this locus acts as a highly specific neuroimmune ignition switch: it drives disease susceptibility but is unequivocally unassociated with MS severity or classical systemic autoimmune phenotypes (Crohn's Disease, Lupus, Rheumatoid Arthritis, and Psoriasis). Crucially, utilizing high-resolution eQTL mapping in purified human immune lineages, we reveal that the shared MS/SCZ risk allele drives a profound, state-independent transcriptomic collapse of HCAR1 exclusively in peripheral macrophages. This enhancer failure renders activated macrophages physically "lactate blind"--unable to sense their own glycolytic exhaust to engage the cAMP-suppressing negative feedback loop required to halt immune proliferation. By bridging psychiatric genetics and neuroimmunology, this study reframes the HCAR tandem array as a master neuroimmune bifurcation point and introduces the un-drugged HCAR1 lactate brake as a critical therapeutic checkpoint for arresting demyelinating disease.

Metabolic psychiatry has recently achieved unprecedented clinical rescue in treatment-resistant Schizophrenia (SCZ) utilizing targeted ketogenic interventions. However, the field has operated without a defined genomic anchor, leaving the biophysical mechanism of these therapies largely unexplained. Here, we report the discovery of the definitive metabolic sensor array driving this pathology. By integrating high-resolution topological mapping of SCZ GWAS summary statistics, 3D chromatin conformation (Hi-C), and multi-tissue transcriptomics, we identify massive, non-coding structural variances flanking the HCAR2/HCAR1 tandem locus—the brain’s master thermodynamic governor. We demonstrate that while the protein-coding hardware of these receptors remains intact, their shared 3D Topologically Associating Domain (TAD) is fundamentally fractured. This structural collapse drives a perfect transcriptomic double dissociation in the human cortex: the 3’ mutational “skyscraper” severely downregulates the HCAR1 lactate emergency brake, while the 5’ mutational cluster selectively paralyzes the HCAR2 β-hydroxybutyrate (BHB) and niacin cooling switch. This dual-flank enhancer failure elegantly provides a definitive genomic etiology for historical SCZ biomarkers, physically explaining both chronic cerebrospinal fluid lactate pooling and the infamous “absent niacin flush.” Furthermore, peripheral eQTL mapping reveals profound antagonistic pleiotropy, characterized by a hyper-activation of the HCAR1 lactate shuttle in the testis, explaining the evolutionary conservation of this metabolically catastrophic architecture. Ultimately, we reframe Schizophrenia not as an intrinsic neurological defect, but as an evolutionary “fuel mismatch.” The high-performance cognitive architecture of the hominid brain, evolved for ancestral ketogenic environments, experiences a catastrophic thermodynamic crash when deprived of its requisite BHB coolant by modern, high-glycemic diets.

The genetic basis of extreme cognitive plasticity in human innovators remains poorly characterized. Here, we demonstrate that the genomic architecture underlying scientific innovation significantly overlaps with the polygenic risks for neuropsychiatric phenotypes, such as schizophrenia. Utilizing a comparative genomic approach across psychiatric cohorts (PGC) and the UK Biobank (Scientific Creativity), we identify a coordinated “Vanguard Engine” consisting of hyper-tuned voltage-gated calcium channels ( CACNA1C, CACNB2 ), glutamatergic receptors ( GRIN2A ), synaptic plasticity regulators ( BDNF ), and the core linguistic-symbolic coordinator ( FOXP2 ). We posit that these variants establish a high-voltage neural environment optimized for associative divergence. Furthermore, we characterize the PDHB and HCAR2 loci as critical metabolic governors against thermal overload and identify structural variance in HDAC2 as the epigenetic clamp linking ancestral fuel availability (β-hydroxybutyrate) directly to the transcriptional control of this plasticity network. We conclude that psychiatric pathology is an emergent property of a fuel-mismatch, wherein a high-performance cognitive architecture is sustained by a carbohydrate-heavy diet, leading to systemic thermodynamic failure. This framework provides a unified, mechanistic explanation for the spectrum between extreme cognitive innovation and pathological collapse.

The development of high-performance functional biointerfaces requires precise control over molecular recognition mechanisms at the nanoscale. A fundamental limitation in current biological nanopore materials is that wild-type (WT) channels often lack the specific physicochemical "grip" required to resolve chemically similar analytes. Here, we demonstrate that rationally engineering a key active site, called the φ-clamp, in the anthrax toxin protective antigen (PA) nanopore creates a tunable biointerface with orthogonal selectivity. By mutating the φ-clamp constriction (F427A), we generated a variant that─despite being a defective large protein biological translocase─functions as a superior material for molecular recognition, achieving ∼93% classification accuracy for peptides that confound the WT pore. We integrated the WT and F427A variants into a multistage machine learning ensemble (XGBoost) to leverage the complementary physicochemical selectivity of each pore─WT for aromatics and F427A for small polar residues─achieving a balanced F1-score of >0.91. This work proposes a design principle for multiplexed biomaterials, demonstrating that attenuating native transport function via rational engineering can enhance the specificity of the biointerface for targeted analytical applications.

Nanopore sensing holds the potential to revolutionize proteomics, yet current methods often rely on ensemble aggregation, where thousands of events must be statistically aggregated or averaged to identify a protein or peptide signature. While effective for pure samples, this aggregation strategy fails in complex, heterogeneous mixtures where the identity of individual molecules must be determined in real-time. Here, we demonstrate high-fidelity classification of peptides from single, individual translocation events, eliminating the need for ensemble averaging. This sensitivity is achieved using the anthrax toxin protective antigen (PA) nanopore. Unlike static pores used more generally, the PA pore’s dynamic active-site clamps generate information-rich, multi-state signals. These clamps also enable the utility of high-affinity capture, permitting analysis at low nanomolar concentrations. We developed a machine learning framework that makes inferences on these dynamical multi-state signals and achieves ~91% accuracy on single events. This work establishes a framework for true single-molecule proteomics, enabling the resolution of complex mixtures that bulk aggregation methods cannot decipher.