Biology subjects

Lu, H.

Publications and source records attributed to Lu, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Humanization of N-glycan-dependent protein quality control system in Kluyveromyces marxianus promotes glycoprotein secretion

Human N-glycoproteins constitute a market worth hundreds of billions of dollars. However, their production in yeast is often limited by misfolding and subsequent degradation, largely due to differences in N-glycan-dependent protein quality control (QC) systems between humans and yeast. Notably, yeast lacks the UGGT-mediated reglucosylation-refolding cycle that rescues misfolded glycoproteins, and its degradation pathway involves fewer rate-limiting steps. To address this, we engineer the glycoprotein QC system in Kluyveromyces marxianus, a promising host for protein production, by introducing key human components and modifying native pathways. Expression of human UGGT1 or UGGT2 enhances the soluble and secretory production of glycoproteins in an activity-dependent manner. This effect is further improved by co-expression of the UGGT cochaperone SEP15 and by reducing native glucosidase II trimming activity. In addition, introduction of human EDEM2, a rate-limiting enzyme in glycoprotein degradation, delays ER-associated degradation and increases secretion. Integration of these engineering strategies substantially enhances the production of several high-value human-derived glycoprotein therapeutics, including etanercept, dulaglutide, and abatacept, with up to a [~]12-fold increase. These findings demonstrate that engineering a human-like glycoprotein QC network in yeast is an effective strategy to improve glycoprotein folding and secretion.

bioengineering↗

bioRxiv2026

Bridging genomes and peptidomes: hybrid sequencing reveals conserved bioactive peptides in crustaceans

Endogenous peptides are critical regulators of signaling and immunity but remain difficult to characterize in organisms with incomplete genomic annotation. We developed a hybrid discovery platform that integrates transformer-based de novo sequencing (Casanovo), neuropeptide-focused database searching (EndoGenius), and empirical false discovery rate estimation via NovoBoard. This pipeline enables confident identification of endogenous peptides while expanding coverage beyond conventional database-only or de novo-only approaches. Applied to neuroendocrine tissues from Callinectes sapidus and Cancer borealis, the workflow revealed numerous high-abundance novel peptides and provided structural and genomic support for their biological relevance. Notably, we report the first histone-2A-derived antimicrobial peptide in the C. sapidus and characterize naturally occurring sequence variants. We also identified unexpected peptide homologies between crustaceans and Rattus norvegicus, enabling annotation of conserved housekeeping proteins in sparsely annotated genomes. This hybrid platform establishes a scalable, open-source strategy for advancing neuropeptidomics and endogenous peptide discovery in emerging model organisms.

bioinformatics↗

bioRxiv2026

Targeted medial prefrontal cortex stimulation prevents incubation of cocaine craving and restores functional connectivity

BackgroundRelapse remains a central obstacle in the treatment of cocaine use disorder (CUD), for which no medications have received approval from the U.S. Food and Drug Administration. Transcranial magnetic stimulation (TMS) has shown promise as a potential therapeutic intervention. However, current clinical trials often rely on a "trial-and-error" approach in target selection and experimental design. We previously developed a novel TMS platform and high-density theta burst stimulation (hdTBS) technology, enabling precise, focal stimulation of the rat medial prefrontal cortex (mPFC), including the prelimbic and anterior cingulate cortices. MethodsWe applied hdTBS intervention to a well-established rat model of cocaine relapse and craving after cessation of extended access intravenous drug self-administration and assessed brain response using resting-state functional magnetic resonance imaging (fMRI). ResultsAs expected, we observed robust time-dependent increases in cocaine seeking (incubation of cocaine craving) in control rats receiving sham stimulation over 3 weeks of abstinence accompanied by a reduction in prefrontal functional connectivity. In contrast, daily sessions of hdTBS for 7 days delivered on abstinence days 14-20 prevented the emergence of the incubation effect and restored prefrontal network functional connectivity. ConclusionsThis study provides strong preclinical evidence demonstrating that precise circuit modulation of medial prefrontal subregions causally reverses both behavioral and network-level adaptations associated with relapse vulnerability. Given the clinical accessibility and established safety profile of TMS, this work provides a mechanistically grounded framework for target selection and supports the translation of focal TMS of the mPFC for relapse prevention in CUD patient. One Sentence SummaryFocal transcranial magnetic stimulation (TMS) of the mPFC using the hdTBS procedure prevents incubation of cocaine craving and restores functional connectivity.

neuroscience↗

bioRxiv2026

HYPER-Net: Physics-Conditioned Self-Supervised Reconstruction for Fourier Light-Field Microscopy

The rapid convergence of optical innovation and machine intelligence is reshaping biological imaging by enabling platforms that jointly advance image formation and computational reconstruction for highspeed, high-resolution volumetric microscopy. However, broadly accessible three-dimensional imaging at high spatiotemporal resolution remains limited by the reliance of existing supervised methods on large modality-matched training datasets, the computational burden of conventional iterative reconstruction, and sensitivity to optical mismatch arising from small deviations in the spatial-angular point spread functions. Here, we introduce HYPER-Net, a physics-conditioned self-supervised framework for Fourier light-field microscopy that integrates scan-free volumetric acquisition with fast, robust three-dimensional reconstruction. HYPER-Net incorporates experiment-specific point-spread functions into the learning process in two complementary roles: as the forward operator that enforces measurement consistency and as a conditioning signal that adaptively modulates intermediate feature representations. This design reduces reliance on paired experimental ground-truth volumes, improves robustness to system variation, and enables generalizable reconstruction across diverse biological contexts. Using human colon organoids, embryonic Xenopus laevis hearts, hiPSC-derived cardiac spheroids, and freely moving Caenorhabditis elegans, we demonstrate high-fidelity volumetric imaging of tissue morphology, cardiac function, calcium-contraction coupling, and locomotion-associated neural and muscular dynamics. These results position HYPER-Net as a versatile framework for rapid volumetric imaging and quantitative analysis of dynamic biological systems across basic research and biomedical applications.

bioengineering↗

bioRxiv2026

Direct Reconstruction of DC Cortical Conductivity from Large-Scale Electron Microscopy Data

Electrical conductivity of cortical gray matter governs the magnitude and spatial distribution of electric fields generated by brain stimulation and intrinsic neuronal activity measured with M/EEG and intracortical recordings. However, reported macroscopic conductivity values vary by more than threefold, limiting the fidelity of bioelectromagnetic models and leaving unresolved whether this variability reflects measurement uncertainty or genuine structural heterogeneity of cortical tissue. Here, we present a multiscale computational framework that, for the first time, attempts to derive mesoscale conductivity maps of mouse visual cortex at 50-{micro}m resolution directly from large-volume, segmented nanometer-scale electron microscopy data. The Minnie 65 subvolume of the MICrONS dataset is accurately subdivided into 1,224 50-{micro}m cubic blocks. Each block contains, on average, 40-50 million membrane facets of a highly convoluted and dense cellular structure. Three orthogonal electrode pairs are applied to each isolated block to estimate the three principal components of the conductivity tensor. Quasistatic electric modeling is enabled by an iterative boundary-element fast multipole method (BEM-FMM) under the approximation of non-conducting membranes (DC conductivity). Spatially averaged conductivity values predicted by our framework agree well with prior low-resolution measurements in rats, validating the approach. At the same time, the resulting mesoscale maps reveal pronounced conductivity granularity at 50-100 {micro}m scales as well as significant variations in both radial and tangential directions. These results indicate that mesoscale conductivity heterogeneity could be an intrinsic structural property of the cortex. Limitations and extensions of this study are discussed in detail.

neuroscience↗

bioRxiv2026

Non-invasive MRI mapping of tissue-CSF water exchange reveals glymphatic fluid movement in live human cortex

Efficient metabolic waste clearance, via the postulated glymphatic system, is essential for neural homeostasis. However, direct visualization of tissue-cerebrospinal fluid (CSF) exchange remains limited, leading to ongoing debate in the neuroscientific field. The present work revealed evidence of tissue-CSF water exchange in the live human cortex, by employing a novel MRI technique demonstrating the flux of water molecules across the perivascular interface. We observed robust water exchange inside the cortical ribbon, which was more prominent than white matter and deep brain tissue. We validated that the signal originates from CSF and is independent of cerebral perfusion. Water exchange between tissue and CSF declined with age. Furthermore, we demonstrated for the first time that tissue-CSF exchange was impaired in Alzheimers disease (AD), in particular in regions where the perivascular space is clogged by anti-amyloid immunotherapy.

bioengineering↗

bioRxiv2026

Patchouli alcohol suppresses gastric cancer growth and immune evasion via inhibition of the NF-κB/PD-L1 axis

ObjectiveThis study aimed to investigate the anti-gastric cancer effect of Patchouli alcohol (PA), especially its influence on PD-L1-mediated immune evasion, and to elucidate the underlying molecular mechanisms. MethodsA CCK-8 assay was used to evaluate the effects of PA on the viability of the gastric cancer cell lines HGC-27 and MKN-45. RT-qPCR and western blotting were performed to analyze the mRNA and protein levels of NF-{kappa}B and PD-L1, respectively. In a coculture system of gastric cancer cells and peripheral blood mononuclear cells (PBMCs), the effect of PA pretreatment on the PBMC-induced apoptosis of cancer cells was analyzed by flow cytometry, and the cytotoxic activity of the PBMCs was assessed by a lactate dehydrogenase (LDH) release assay. Flow cytometry was also used to determine the proportions of CD3CD8 T cells and IFN-{gamma}CD8 T cells. ELISA was used to measure the levels of IFN-{gamma}, TNF-, and granzyme B in the coculture supernatants. Immunofluorescence staining was conducted to assess NF-{kappa}B nuclear translocation. In a mouse xenograft model, tumor volume and weight were measured after 14 days of PA treatment. Histopathological changes and apoptosis were analyzed by HE and TUNEL staining. A luciferase reporter assay was used to examine the transcriptional regulation of PD-L1 by NF-{kappa}B. ResultsPA inhibited the viability of HGC-27 and MKN-45 cells in a dose- and time-dependent manner and significantly downregulated the expression of NF-{kappa}B and PD-L1 at both the mRNA and protein levels. In a PBMC coculture model, PA pretreatment enhanced the ability of PBMCs to induce apoptosis and directly kill gastric cancer cells. Furthermore, PA pretreatment increased the proportions of CD3CD8 T cells and IFN-{gamma}CD8 T cells in a dose-dependent manner. Consistent with this immunostimulatory effect, PA increased the levels of IFN-{gamma}, TNF-, and granzyme B in the coculture supernatants. Mechanistically, western blotting analysis demonstrated that PA significantly reduced the protein levels of AKT, NF-{kappa}B, and PD-L1 in gastric cancer cells. Immunofluorescence staining further indicated that PA suppressed the nuclear translocation of NF-{kappa}B. In a mouse xenograft model, PA treatment significantly inhibited tumor growth, induced apoptosis, and downregulated NF-{kappa}B and PD-L1 protein expression in tumor tissues. Flow cytometry of tumor-infiltrating lymphocytes revealed increased proportions of CD3CD8 and IFN-{gamma}CD8 T cells following PA treatment. Finally, luciferase reporter assays demonstrated that NF-{kappa}B directly regulates PD-L1 transcription by binding to its promoter region. ConclusionPA exerts antitumor effects in gastric cancer by suppressing the NF-{kappa}B/PD-L1 axis, thereby enhancing CD8 T-cell-mediated cytotoxicity and inhibiting immune evasion.

pharmacology and toxicology↗

bioRxiv2026

Spontaneous emergence of context-dependent statistical learning in humans and neural networks

Humans readily extract statistical regularities from experience, yet natural environments require flexible adaptation when associative structures shift across changing contexts, often without warning. Across two experiments, we show that humans can incidentally learn overlapping and conflicting visual associations even when contexts dynamically alternate and remain unsignaled or only minimally cued. To probe the computational mechanisms supporting this adaptive capacity, we trained recurrent neural networks with gated recurrent units on the same statistical learning task without providing any explicit context information. These models spontaneously developed distributed internal representations that robustly separated conflicting associations and supported rapid adaptation to latent context shifts. Critically, we show that these distributed representations, strongly shaped by the models initial weight configuration, played a key role in preventing catastrophic interference between contexts. Together, these behavioral and computational results significantly advance our understanding of how humans and artificial systems can successfully learn and flexibly retrieve context-dependent associations under challenging conditions.

neuroscience↗

bioRxiv2026

Nucleotide-dependent Structural Selection Governs c-Src Phosphorylation of Oncogenic KRas4B-G12D

c-Src, the first identified oncogene, and KRas, one of the most frequently mutated proteins in human cancers, can activate each other to promote tumorigenesis. Although normal KRas proteins cycle between the inactive GDP bound and the active GTP bound forms, oncogenic mutants are predominantly GTP bound. Importantly, c-Src preferentially recognizes and phosphorylates the GTP-bound form of KRas but the molecular mechanism underlying this specific recognition remains unknown. Here, we employ molecular simulation tools to identify the mechanism underlying the c-Src recognition of the GTP-loaded state of the G12D mutant of KRas4B (the most prevalent in humans). Combining extensive all-atom Molecular Dynamics simulations and Markov State Models analysis, we found that the most populated states of GTP-bound KRas maintain more open and dynamic switch regions, facilitating easier access of c-Src to the phosphorylation sites of KRas (Tyr32 and Tyr64). These states are sparsely populated for GDP loaded KRas. Docking calculations refined by molecular dynamics identify two c-Src specific regions (residues 340-359 and 453-473) able to stabilize phosphorylation-competent KRas conformations. Therefore, c-Src engages highly populated macrostates of GTP-loaded KRas, while interactions with the GDP form are limited to rare conformations. These KRas conformations selectively recognized by c-Src constitute privileged targets for the rational design of peptide-based or small-molecule inhibitors that specifically target active KRas4B-G12D while sparing the inactive GDP-bound form.

biophysics↗

bioRxiv2026

Cell type-resolved transcriptomic map of skeletal muscle in women with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is associated with skeletal muscle insulin resistance, fibrosis, and lipotoxicity, yet the cellular origins remain unknown. Here, we present a comprehensive cellular atlas of skeletal muscle from hyperinsulinemic and hyperandrogenic women with PCOS and controls of similar age, weight, and BMI. Analysis of 72,247 nuclei from 19 biopsies revealed cell-type-specific dysregulation in PCOS, with fiber-type-specific metabolic impairment, converging with pro-fibrotic reprogramming of fibro-adipogenic progenitors (FAPs) and enhanced FAP-myofiber crosstalk, characterized by enhanced collagen and laminin signaling. Metformin intervention for 16-weeks selectively reversed PCOS-associated transcriptional dysregulation in FAPs, revealing heterogeneous cellular responses in skeletal muscle. In vitro, PCOS myotubes retained metabolic dysfunction, yet show normalized glucose responsiveness, indicating plasticity despite metabolic memory. Systemic hyperinsulinemia and hyperandrogenemia correlated with transcriptional signatures in muscle fibers and FAPs, linking endocrine imbalance to pro-fibrotic remodeling. These findings identify novel therapeutic targets beyond conventional insulin-sensitizing approaches. Highlights- First single-nuclei atlas of human skeletal muscle in women with PCOS - FAPs subpopulations display activated pro-fibrotic phenotype - Metformin selectively targets distinct cell populations - Hyperinsulinemia and hyperandrogenemia correlate with transcriptional signatures of skeletal muscle fibers and FAPs

physiology↗

bioRxiv2026

LysinFusion: Integrating Multi-Feature Encoding and Hybrid CNN-Transformer Architecture for Phage Lysin Prediction

The escalating antimicrobial resistance crisis has intensified the urgent need for alternative antibacterial agents. Phage lysins exhibit potent bactericidal activity with low resistance potential, yet their large-scale discovery from rapidly expanding genomic resources remains limited, as existing computational methods often rely on sequence homology and few reproducible, independently validated, and practically deployable prediction frameworks are currently available. We present LysinFusion, a reproducible deep learning framework that integrates heterogeneous sequence features via a hybrid CNN-Transformer architecture for accurate lysin identification. Trained on a curated, de-redundant corpus (PHROG + inphared) and validated on 148 experimentally confirmed UniProt proteins, LysinFusion achieves an accuracy of 0.81, an AUC of 0.89, and an MCC of 0.62, outperforming the state-of-the-art DeepMineLys by up to 52.3% across metrics while reducing false positives by 64% (12 vs. 33). Ablation studies confirm that both CNN and Transformer modules are individually essential and that serial processing outperforms parallel alternatives. Model interpretability via occlusion and LIME aligns with established lysin biology, with attention concentrating on the N-terminal catalytic domain and decision boundaries reflecting characteristic charge-composition thresholds documented in Gram-negative lysin C-terminal regions. The framework, including all source code, curated datasets, and an accompanying web server, is freely available at https://github.com/sinuo560/LysinFusion.

bioinformatics↗

bioRxiv2026

Focal Transcranial Magnetic Stimulation of the Rat Anterior Cingulate Cortex Inhibits Incubation of Opioid Craving after Voluntary Abstinence

Relapse remains a major challenge in opioid addiction treatment, underscoring the need for innovative therapies. Progress in neuromodulation therapies has been limited by insufficient mechanistic understanding of stimulation engagement and disease-related changes in the brain. We used a novel, focal transcranial magnetic stimulation (TMS) system to deliver high-density theta burst stimulation (hdTBS) combined with resting-state fMRI to test whether anterior cingulate cortex (ACC) stimulation reduces relapse-like behavior and alters functional circuitry in a rodent model of opiate dependence. The coil focality and stimulation parameters approximate human TMS protocols, and the targeted region represents a functional homolog of the human ACC. We trained rats to self-administer oxycodone intravenously for 14 days. We then introduced an electric barrier for 13 days, which caused cessation of drug self-administration. We assessed relapse to oxycodone seeking immediately after training (early abstinence) and after electric-barrier exposure (late abstinence). We administered daily hdTBS or sham stimulation for 7 days before the late-abstinence test. Sham-treated rats showed a time-dependent increase in oxycodone seeking during abstinence (incubation of oxycodone craving) and reduced ACC functional connectivity. In contrast, hdTBS prevented the incubation of oxycodone craving and restored ACC connectivity with the dorsal and ventral striatum. Tracer-based axonal-projection data further showed that stimulation-induced effects aligned with regions receiving dense projections from the stimulation site, suggesting that the projection architecture is critical to the propagation of focal stimulation across distributed networks. These findings identify ACC-centered circuits as mechanistically informed targets for TMS-based interventions that aim to reduce opioid relapse during abstinence. One sentence SummaryPrefrontal TMS stimulation reduced relapse-like behavior and restored corticostriatal circuits, highlighting translational targets for addiction treatment.

neuroscience↗

bioRxiv2026

NanoHIVSeq: A Long-Read Bioinformatics Pipeline for High-Throughput Processing of HIV Env Sequences

High-throughput sequencing of the HIV-1 envelope (Env) gene from viral quasispecies is essential for epidemiology, virus-antibody coevolution studies, and evaluating therapeutics, but the conventional single-genome amplification (SGA) coupled with Sanger sequencing is labor-intensive and low-throughput. Oxford Nanopore Technology (ONT) offers long-read sequencing advantages, but high error rates (1-7%) poses a challenge in identifying biological variants from sequencing artifacts. Without unique molecular identifiers (UMIs), which lose DNA template and add complexity in library preparation, here we introduce NanoHIVSeq, a UMI-free and reference-free bioinformatics pipeline that processes ONT data from bulk Env PCR amplicons through multistep clustering, consensus polishing, indel correction, denoising, and genotyping to recover functional full-length Env variants. By leveraging advanced ONT duplex sequencing technology, NanoHIVSeq was assessed using plasmid env and bulk HIV reservoir datasets, demonstrating high robustness, recovery rate, reproducibility, and accuracy (>99.9% or >Q30) comparable to UMI approaches. Our findings indicated that NanoHIVSeq allows flexible and simplified ONT library preparation for reproducible and efficient Env sequencing especially for large cohorts.

bioinformatics↗

bioRxiv2026

Brain morphological pattern is associated with the presence, severity, and transition of transdiagnostic psychiatric disorders in preadolescents

Cognitive function, psychological processes, mental states, and behaviors are key dimensions of human subjective experience that separately relate to mental disorders across diagnostic categories. However, whether these dimensions are linked to common or distinct brain morphological patterns that convey risk or resilience for psychiatric disorders remains unclear. The current study is a longitudinal investigation on 11,875 youths from the Adolescent Brain Cognitive Development (ABCD) Study aged 9-10 years at baseline. A machine learning approach based on canonical correlation analysis was used to identify latent dimensional associations of cortical morphology (4 metrics: surface area, cortical and subcortical volume, cortical thickness, and sulcal/gyral depth) with multidomain behavioral assessments including cognitive scores and psychological measures indexing motivation, impulse control, mental states, and behaviors across a normative continuum from healthy to pathological. Across morphological measures, we identified a robust latent brain structural variate that correlated positively with cognitive performance and negatively with psychological measures indexing greater psychology. Notably, higher scores on this brain variate reflected larger cortical surface area and cortical volume--especially in the temporal gyri--together with a posterior-anterior gradient in cortical thickness, showing relatively greater thickness in occipital, parietal, and temporal cortices and lower thickness in cingulate and frontal regions. This brain variate and the related cognitive-psychological-behavioral variate remained stable at the 2-year follow-up, demonstrating temporal consistency. Importantly, the brain variate showed a dose-dependent relationship with the cumulative number of psychiatric diagnoses assessed concurrently and at 2-year follow-up, with lower brain variate scores being associated with higher numbers of comorbid diagnoses. In addition, the brain scores were associated with longitudinal transitions between healthy and diagnosed states over the 2-year study period, in which lower scores at baseline were associated with persistent psychiatric diagnoses whereas higher scores at baseline were associated with persistent healthy states, suggesting that the brain scores capture a vulnerability- resilience continuum for psychopathology. By revealing shared brain structural substrates across conventional diagnostic boundaries, these findings advance the neurodevelopmental understanding of psychiatric disorders and highlight the potential utility of morphology-informed approaches for early screening and intervention in youth.

developmental biology↗

bioRxiv2026

Implantation failure linked to altered uterine NK cells in PCOS-like mice

Uterine NK (uNK) cells are essential for reproductive function, yet little is known how they are affected in polycystic ovary syndrome (PCOS), despite the strong association between PCOS and reproductive complications. We demonstrate that implantation failure coincides with distinct phenotypic alterations of uNK cells in a PCOS-like mouse model. Hyperandrogenism caused an increased influx of conventional NK (cNK) cells into the uterus, which contributed to an augmented uNK cell population, while tissue-resident NK (trNK) cells remained unchanged. Notably, CD69+ trNK cells were reduced and seemingly compensated by an upregulated expression of CD69 on cNK cells in the uterus. The maturation of uNK cells was disrupted and plausibly linked to an inability of cNK cells to convert into trNK cells. The inhibited maturation was associated with a reduced expression of the inhibitory receptor NKG2A, demonstrating an impaired education of uNK cells. This disruption of uNK cells could contribute to endometrial dysfunction and may be an underlying factor to reproductive comorbidities such as implantation failure, miscarriage and pre-eclampsia in PCOS.

immunology↗

bioRxiv2026

Evolutionary dynamics of insect odorant receptors reveal ecological tuning shaping olfactory perception

Insect olfaction is facilitated by a heterotetrameric odorant receptor-odorant receptor co-receptor (OR-Orco) complex, which is distinct from that of vertebrate ORs. However, extreme sequence divergence among insect ORs has hindered a unified understanding of their evolutionary history and ecological importance. In this study, we present a multiscale analysis of OR genes across 115 insect species. We overcome the limitations of traditional phylogenetic approaches by applying a protein similarity network-based strategy and introduce a "trunk-branch" framework to systematically describe the evolutionary trajectories of insect ORs across sequence, structural, and predicted olfactory potential levels. Although they possess different sequences and structural communities, all sampled insect orders contained ORs assigned to all six docking-derived functional communities. Notably, extant insect lineages with order-level origins spanning the end-Permian mass extinction (EPME) differed in docking-derived functional OR repertoires, and early-and late-diverging lineages differed in OR sequence-community diversity. The emergence of Orco represents a key evolutionary transition point, marking the shift from a homomeric to a heteromeric complex accompanied by specialization of the extracellular domain and binding pocket. Furthermore, we established robust associations between potential olfactory recognition breadth and ecological variables, including diet, circadian rhythm, and habitat. Our findings provide a class-level framework for investigating insect OR evolution and generate testable hypotheses about how receptor repertoire diversification may relate to ecological adaptation.

evolutionary biology↗

bioRxiv2026

Rapid and Quantitative Phage Susceptibility Test by Ramanome

Antimicrobial resistance poses an escalating global threat, renewing interest in bacteriophage therapy as a precision alternative to antibiotics. However, clinical translation remains hindered by the lack of rapid and quantitative phage susceptibility testing (PST) platforms capable of evaluating host range, infection potency, and effective multiplicity of infection (MOI). Here we present RPST, a ramanome-based phenotypic platform that captures infection-induced remodeling of bacterial macromolecular composition to unify these diagnostic requirements within a single workflow. RPST integrates four Raman biomarkers into a Composite Infection Index (CII), enabling rapid and lysis-independent discrimination between susceptible and resistant bacterial populations within [~]1 hour, with 96.0% categorical concordance (24/25) to plaque assays. As a continuous population-level metric, CII quantifies the proportion of infected cells, allowing quantitative ranking of phage potency against shared hosts. By resolving CII trajectories across the MOI and time, RPST further determines the minimal effective MOI, which is the lowest phage-to-bacterium ratio sustaining self-propagating infection, thereby defining the lower boundary for therapeutic feasibility. Together, these capabilities transform PST from static compatibility assays into a dynamic and quantitative framework that bridges in vitro infectivity assessment and infection dynamics relevant to phage therapy. Impact StatementBased on the rapid emergence of antimicrobial resistance, this study introduces RPST, a novel ramanome-based phage susceptibility testing platform. RPST detects phage-induced biochemical remodeling in bacteria within [~]1 hour, achieving 96.0% concordance with gold-standard plaque assays. By integrating four Raman biomarkers into a Composite Infection Index, it not only distinguishes susceptible from resistant strains but also quantifies phage potency and determines the minimal effective multiplicity of infection required for self-sustaining infection. This transformative approach moves beyond binary diagnostics to offer a dynamic, quantitative framework for precision phage therapy, significantly accelerating therapeutic decision-making and enhancing our ability to combat resistant infections.

microbiology↗

bioRxiv2026

Label-Free, Physics-Constrained Learning for Multi-Exposure Speckle Imaging Parameter Estimation

Multi-exposure speckle imaging (MESI) estimates flow-related parameters by fitting a physics-based speckle contrast model to measurements acquired over multiple exposure times. In standard pipelines, parameters are recovered via nonlinear least-squares fitting at each pixel, which is computationally expensive and can yield spatially inconsistent maps when uncertainty in the estimated speckle contrast variance [Formula] (from camera noise and finite spatial/temporal sampling used to compute speckle contrast) is amplified by independent pixel wise inversion. This work reframes MESI parameter estimation as identification of a globally shared inverse operator of the analytical forward model, exploiting the fact that a single physical mapping governs all pixels while noise drives large variance in independent pixel wise inversion. Rather than solving millions of iterative optimizations, a single parameterized inverse mapping is learned directly from a single acquired MESI dataset. Physics consistency is enforced by embedding the fixed MESI forward model as an analysis-by-synthesis layer that re-synthesizes speckle contrast curves from the predicted parameters. Training is self-supervised: the inverse mapping is optimized by minimizing a reconstruction loss between measured and re-synthesized speckle contrast curves, which constrains estimates to the set of physically admissible MESI curves without requiring ground truth parameter labels. Experiments on a numerical MESI phantom with known ground truth and on in vivo mouse cortex data show that the proposed method produces more stable inverse correlation time (ICT) maps (1/{tau}c) and improved spatial coherence relative to conventional per-pixel fitting, while substantially reducing inference time by replacing iterative optimization with a single feed-forward evaluation.

neuroscience↗