bioRxiv Science⌕ Search

Biology subjects

Guan, L.

Publications and source records attributed to Guan, L..

At least 19 recordsLinked to original sources
bioRxiv2026

Unraveling APA dynamics during quiescence transitions reveals Pabp modulation of sod2 expression via APA to regulate cellular quiescence

Quiescence is a reversible proliferation arrest enabling cells to adapt to environmental changes, yet the post-transcriptional mechanisms governing its transitions remain poorly understood. Here, we map genome-wide alternative polyadenylation (APA) dynamics across 15 time points of quiescence transitions in fission yeast using 3'-end RNA sequencing. We reveal that APA undergoes extensive remodeling: driving global 3'UTR lengthening during early quiescence entry, 3' UTR shortening upon quiescence establishment, and progressive reversal to proliferative-state lengths during quiescence exit. Integrating 3' UTR dynamics with differential expression analysis, we identify candidate genes potentially regulated through APA-mediated 3' UTR mechanisms. We demonstrate that sod2, encoding mitochondrial superoxide dismutase, autoregulates its mRNA and protein levels via APA-dependent 3' UTR changes. Disrupting proximal APA site of sod2 in a mitophagy-deficient (atg43{Delta}) background exacerbates quiescence maintenance defects and mitochondrial dysfunction. We further identify Pabp as an upstream regulator of sod2 APA. This study establishes the temporal APA remodeling during quiescence transitions and reveals a Pabp-APA-sod2 regulatory axis governing post-transcriptional control of cellular quiescence.

cell biology↗
bioRxiv2026

An Open Benchmark for Systems Vaccinology: Insights from the CMI-PB Challenges

Systems vaccinology approaches have identified factors affecting vaccine responses in multiple studies, but the ability of computational models to generalize these findings to unseen data remains unclear. We established a community resource to create and compare models predicting B. pertussis booster vaccination responses and put such modeling approaches to the test. We compiled multi-modal experimental training data from three independent cohorts (n=117 individuals), and asked investigators to predict vaccine responses in a cohort of 54 newly recruited individuals using only their pre-booster vaccination data. We benchmarked a total of 107 computational models. Top-performing models were characterized by workflows that prioritized rigorous data preprocessing, robust imputation of missing data, and the use of multi-omics integration or non-linear machine learning. We identified pre-existing antigen-specific antibody titers and baseline monocyte frequencies as the most consistent predictors of post-vaccination immunity, highlighting the dominant role of individual immune setpoints. We established the resulting datasets and evaluation framework as a community resource to advance predictive immunology and facilitate personalized vaccination strategies.

immunology↗
bioRxiv2026

BXD51: A Robust and Translational Mouse Model for Studying the Pathophysiology of Glaucoma

The aim of this study was to characterize the BXD51 mouse strain as a reproducible model of chronic progressive glaucoma. Unlike the highly susceptible DBA/2J (D2) mutant strain, BXD51 is a genetically stable recombinant inbred line derived from C57BL/6J (B6) and D2 parental lines. Longitudinal assessments of intraocular pressure (IOP), visual acuity (VA), contrast sensitivity (CS), and pattern electroretinogram (pERG) demonstrated that BXD51 mice undergo a delayed decline in visual and retinal ganglion cell (RGC) function. Their decline is biphasic, with a period of initial ocular stress followed by a late-onset, accelerated structural and functional deterioration of RGCs. Anterior segment structural analysis by optical coherence tomography (OCT) and histology demonstrated increasing pigment dispersion and subsequent iridocorneal angle closure. Immunofluorescence analysis of structural neuronal markers (TUBB3 and MAP1A/2) exhibited thinning of the ganglion cell layer (GCL) and inner plexiform layer (IPL) together with axonal degeneration, mirroring the laminar degeneration seen in human glaucoma patients. BXD51 also revealed marked spatial heterogeneity between peripheral and central retina. Multivariate analysis confirmed that BXD51 follows a distinct clinical trajectory that separates it from both wild-type (B6) and a severe glaucoma model (D2). By spanning the range between resistance and extreme susceptibility to glaucomatous neurodegeneration, this study establishes the BXD51 mouse as a translational platform for mechanistic studies and for evaluating long-term neuroprotective strategies.

neuroscience↗
bioRxiv2026

Evolutionary constraints limit additional mammalian adaptation of bovine-derived H5N1 influenza viruses in ferrets

The outbreak of clade 2.3.4.4b H5N1 viruses among U.S. dairy cattle has raised concerns that sustained circulation among agricultural mammals could facilitate viral adaptation toward efficient human transmission. However, the evolutionary dynamics governing such adaptation remain poorly understood. Here we investigated the evolution of two bovine-derived H5N1 B3.13 genotype viruses during infection and airborne transmission in ferrets, building on prior characterization of their robust replication and inefficient airborne transmission. Within hosts, viral genetic diversity was limited and viruses were subject to genetic drift and weak purifying selection. Transmission, when it occurred, was characterized by stringent bottlenecks that sharply reduced viral genetic diversity. We found no evidence of mammalian adaptation during infection or transmission. Together, these findings indicate that bovine-derived H5N1 viruses face evolutionary constraints during acute mammalian infection and transmission, limiting movement toward enhanced airborne spread. These constraints may help explain why efficient mammalian replication does not necessarily coincide with efficient transmission. Continued circulation of HA clade 2.3.4.4b viruses nevertheless creates repeated opportunities for rare but consequential evolutionary events, underscoring the importance of sustained surveillance and risk mitigation.

microbiology↗
bioRxiv2026

Robust semi-supervised scRNA-seq integration from virtual adversarial learning

Single-cell RNA sequencing integration methods that rely solely on transcriptomic data often struggle to preserve fine-grained distinctions between closely related cell subtypes. As a result, cell populations that are separable in the raw data may become over-mixed after integration, reducing biological resolution and interpretability. Incorporating marker gene information can potentially address these issues; however, the variability and complexity of available marker sets limit their effective application. To address this, we introduce scCRAFT+, a semi-supervised integration model that innovatively incorporates marker gene information through Virtual Adversarial Training (VAT). By jointly optimizing marker-derived supervision and transcriptome-wide representations, VAT enforces local prediction smoothness among transcriptionally similar cells, improving robustness to noisy marker annotations while enhancing both integration quality and cell type auto-annotation. This targeted approach significantly enhances annotation accuracy and robustness, particularly when faced with incomplete or incorrect marker gene sets. Benchmarking shows that scCRAFT+ achieves consistently stronger performance than current unsupervised and supervised integration approaches, resulting in improved integration quality and biologically meaningful sub-cell type auto-annotations.

bioinformatics↗
bioRxiv2026

Patient-Calibrated Dynamical Modeling and Embedded Trend-Zone Predictive Control for Closed-Loop Deep Brain Stimulation in Parkinson's Disease

Closed-loop deep brain stimulation (cDBS) for Parkinsons disease requires control strategies that tolerate noisy sensing, patient-specific stimulation responses, medication-related fluctuations, and embedded hardware constraints. We developed a patient-calibrated minute-scale dynamical model of subthalamic beta activity and an embedded explicit trend-zone predictive controller, eTZPC. The model combined a basal-ganglia mechanistic prior with stimulation-amplitude and medication-cycle recordings from five patients, and incorporated individualized stimulation-{beta}STN maps, fast- and slow-timescale stimulation responses, levodopa-related modulation, background drift, and observation noise. eTZPC was designed to maintain {beta}STN activity within a patient-specific target zone under stimulation-amplitude, step-size, and quantization constraints. Compared with dual-threshold (DT) and proportional-integral-derivative (PID) controllers across four disturbance scenarios, eTZPC achieved target-zone regulation close to PID while reducing stimulation-switching burden toward the low-switching profile of DT. Ablation analyses identified distinct contributions of smoothing, trend prediction, patient-specific action modeling, and embedded explicit implementation. Parameter-mismatch tests showed that eTZPC was relatively robust to dynamic and disturbance-parameter deviations, but remained sensitive to errors in the steady-state stimulation-{beta}STN map. Patient-in-the-loop recordings in five patients further confirmed execution consistency and compliance with stimulation-boundary and step-size constraints. These findings support patient-calibrated dynamical modeling combined with low-complexity explicit control as a feasible framework for further embedded cDBS evaluation.

neuroscience↗
bioRxiv2026

Visual Function Correlates More Strongly with Glial Coverage than Axon Count Across Multiple Mouse Strains

ObjectiveTo determine whether non-axon optic nerve morphometric features correlate with clinical visual function as strongly as the traditional axon count gold standard. DesignCross-sectional histological analysis with longitudinal clinical correlation. SubjectsEighteen mice from three strains: C57BL/6J (n=6), BXD51 (n=6), and DBA/2J (n=6). MethodsLeft eye (OS) optic nerves from mice euthanized at 12 months of age were resin-embedded and stained with p-phenylenediamine. Bright-field cross-sectional images were segmented using an AxonDeepSeg-based workflow to generate axon, myelin, whole nerve, and glial coverage masks for morphometric quantification. Seven morphometrics were extracted: axon count (nAx), axon density (AxDen), glial coverage area ratio (GliaR), mean solidity (Sol), mean axon diameter (AxDiam), mean myelin area (MyArea), and mean axon-myelin area (AxMyArea). Morphometrics were correlated with longitudinal clinical data collected at 1, 3, 6, 9, and 12 months, including visual acuity (VA), contrast threshold, intraocular pressure (IOP), and pattern electroretinography P50 and N95 amplitudes (PERG P50 and N95). Main Outcome MeasuresPearson correlation coefficients were used to assess associations between morphometric features and clinical measures, and Fisher z-transformed meta-analytic correlations were used to aggregate these associations across ages. ResultsVA and contrast threshold demonstrated strong correlations with GliaR that matched or exceeded nAx. Meta-analysis across ages revealed GliaR correlated with VA (r = -0.84, p = 4.49 x 10-21) and contrast threshold (r = 0.86, p=7.55 x 10-23), comparable to nAx correlations with VA (r = 0.80, p=8.13x10-17) and contrast threshold (r = -0.80, p= 1.74x10-16). Structure-function relationships shifted with age: at 6 months, GliaR had the strongest correlation with contrast threshold (r = 0.96), while at 12 months, AxDiam became the dominant correlate of both VA (r = 0.77) and contrast threshhold (r = -0.74). IOP, PERG P50, and PERG N95 exhibited weak correlations with all morphometrics (|r| < 0.27). ConclusionsNon-axon morphometrics, particularly glial coverage area ratio, correlate with visual function as strongly as traditional axon count. Automated optic nerve assessment should incorporate glial and other non-axon features. Further, stage-aware biomarker selection may better capture structure-function relationships in glaucoma.

neuroscience↗
bioRxiv2026

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗
bioRxiv2026

MONICA: A Web Application for Automated Whole Optic Nerve Contour Extraction and Morphometric Analysis Validated Across Taxonomic Orders and Image Quality Levels

Quantitative assessment of optic nerve health requires metrics beyond axon counts alone. Axon density and glial coverage fraction correlate with clinical measures of visual function, yet no existing automated tool extracts optic nerve cross-sectional boundaries to enable their calculation. We developed MONICA (Morphometrics from Optic Nerve Imaging Contour Analysis), a web application that integrates AxonDeepSeg deep learning segmentation with a novel morphology-based contour extraction algorithm to automatically derive whole nerve boundaries alongside axon and myelin masks. The contour extraction algorithm was validated against manual ground truth annotations using 15 optic nerve cross-sections spanning two taxonomic orders (mouse, rabbit), two mouse strains (BXD29, BXD51), and varying preparation quality levels (modern and archival samples). Automated contour extraction demonstrated excellent agreement with manual annotations, achieving an overall Dice similarity coefficient (a measure of segmentation overlap) of 0.987 {+/-} 0.009. Balanced precision (0.985) and recall (0.989) values indicated that the algorithm neither systematically over-segments nor under-segments nerve boundaries. MONICA requires no local software installation and runs entirely in-browser, providing batch processing for high-throughput phenotyping alongside a full suite of per-axon morphometrics. MONICA provides researchers with an accessible tool for complete nerve cross-section morphometry.

neuroscience↗
bioRxiv2025

ER-to-Golgi transport machinery promotes the excessive cargo-triggered unfolded protein response

Disruptions to ER homeostasis trigger the unfolded protein response (UPR) to restore proteostatic balance. While defects in the secretory machinery are known to induce ER stress, it remains unclear whether specific trafficking components directly modulate UPR signaling. Here, we demonstrate that neuronal overexpression of the gap junction protein UNC-9 activates the IRE1-XBP1 arm of the UPR in C. elegans. Genetic deletion of ERGIC2 or ERGIC3--genes encoding COPII-associated proteins required for UNC-9 transport--suppresses this UPR activation, revealing an unexpected role for these factors beyond cargo trafficking. Mechanistically, ERGIC2 and ERGIC3 interact with the ER chaperone BiP, facilitating its release from IRE1 to enable UPR and alleviate cargo aggregation. Our findings redefine the UPR as a process dynamically regulated by early secretory components and provide novel insights into how cells integrate trafficking demand with stress adaptation, with implications for ER stress-associated diseases such as neurodegeneration.

cell biology↗
bioRxiv2025

IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry.

The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, current platforms lack meaningful ways to compare multiple properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

microbiology↗
bioRxiv2025

A Benchmark of Semi-Supervised scRNA-seq Integration Methods in Real-World Scenarios

Semi-supervised methods for single-cell RNA-seq integration promise to improve batch correction and biological signal preservation by leveraging cell-type labels. However, their reported benefits often rely on overly idealized settings. Here, we present the first systematic benchmark of five leading semi-supervised methods (scANVI, scGEN, ssSTACAS, scDREAMER, ItClust) against five widely used unsupervised baselines across six diverse datasets. We evaluate performance under five realistic annotation scenarios, including missing, erroneous, boundary-missing and mixed, batch-specific, and auto-generated labels, using nine established integration metrics. While semi-supervised methods show gains with perfect annotations, their robustness declines sharply under practical imperfections. Only scANVI and ssSTACAS maintain stable but modest improvements relative to their unsupervised counterparts, while none consistently outperform the strongest unsupervised method, scCRAFT. Our results highlight that current semi-supervised strategies offer limited practical advantage and that careful choice of integration method remains critical when label quality is uncertain.

bioinformatics↗
bioRxiv2025

Allosteric effects of the coupling cation in melibiose transporter MelB

The major facilitator superfamily (MFS) transporters play significant roles in human health and disease. Salmonella enterica serovar Typhimurium melibiose permease (MelBSt), which catalyzes the symport of galactosides with Na+, H+, or Li+, is a prototype of this important transporter superfamily. We have published the structures of the inward- and outward-facing conformations of MelBSt with galactoside or Na+ bound, determined the binding thermodynamic cycle, and proposed that positive cooperativity between the two co-transported solutes plays a key role in the symport mechanism of MelBSt. The molecular basis for this core mechanism remains unclear. In this study, we determined the molecular basis for this core symport mechanism through analyzing the structural dynamics of MelBSt and effects induced by melibiose, Na+, or both using hydrogen-deuterium exchange mass spectrometry (HDX-MS). We also refined the specific determinants for the sugar recognition in both protein and galactoside molecules by solving the crystal structures of a uniporter D59C MelBSt bound to melibiose and other sugars, and identified a critical water molecule as part of sugar recognition. Our integrated studies from structure, HDX-MS, and molecular dynamics simulations support the conclusion that sugar-binding affinity is directly correlated with protein dynamics. The binding of the coupling cation at a remote site functions as an allosteric activator to restrain the conformational flexibility of dynamic residues in the sugar-binding site and in the cytoplasmic gating salt-bridge network, thereby increasing sugar-binding affinity allosterically. This study provides a molecular-level schematic of the fundamental symport mechanism via positive cooperativity, which may serve as a general mechanism for cation-coupled symporters.

biophysics↗
bioRxiv2025

How AlphaFold and related models predict protein-peptide complex structures

Protein-peptide interactions mediate many biological processes, and access to accurate structural models, through experimental determination or reliable computational prediction, is essential for understanding protein function and designing novel protein-protein interactions. AlphaFold2-Multimer (AF2-Multimer), AlphaFold3 (AF3), and related models such as Boltz-1 and Chai-1 are state-of-the-art protein structure predictors that successfully predict protein-peptide complex structures. Using a dataset of experimentally resolved protein-peptide structures, we analyzed the performance of these four structure prediction models to understand how they work. We found evidence of bias for previously seen structures, suggesting that models may struggle to generalize to novel target proteins or binding sites. We probed how models use the protein and peptide multiple sequence alignments (MSAs), which are often shallow or of poor quality for peptide sequences. We found weak evidence that models use coevolutionary information from paired MSAs and found that both the target and peptide unpaired MSAs contribute to performance. Our work highlights the promise of deep learning for peptide docking and the importance of diverse representation of interface geometries in the training data for optimal prediction performance.

bioinformatics↗
bioRxiv2025

Almost Free Enhancement of Multi-Population PRS: From Data-Fission to Pseudo-GWAS Subsampling

Many multi-population polygenic risk score (PRS) methods have been proposed to improve prediction accuracy in underrepresented populations; however, no single method outperforms other methods across all data scenarios. Although integrating PRS results across multiple methods and populations may lead to more accurate predictions, this approach may be limited by the availability of individual-level tuning data to calculate combination weights. In this manuscript, we introduce MIXPRS, a robust PRS integration framework based on data fission principles, to effectively combine multiple multi-population PRS methods using only genome-wide association study (GWAS) summary statistics from multiple populations. Specifically, MIXPRS employs SNP pruning to mitigate linkage disequilibrium (LD) mismatch between the training GWAS summary statistics and LD reference panels, and utilizes non-negative least squares regression to robustly estimate PRS combination weights. Extensive simulations and real-data analyses involving 22 continuous traits and four binary traits across five populations from the UK Biobank and All of Us datasets demonstrate that MIXPRS consistently outperforms the existing methods in prediction accuracy. Because MIXPRS relies solely on GWAS summary statistics, it enjoys broad accessibility, robustness, and generalizability for underrepresented populations.

genetics↗
bioRxiv2025

Enhancing Neural Synchrony with Endogenous-like 1/f Noise Stimulation

Aperiodic components of neural activity, characterized by endogenous 1/f noise dynamics, are hypothesized to support the emergence of large-scale cortical order and cognitive flexibility. Here, we combine computational modeling and human brain stimulation to elucidate the role of 1/f noise in modulating neural synchrony. Using a coupled oscillator model, we demonstrate that ubiquitous 1/f noise does more effectively enhances phase synchrony than spectrally flat (white) noise. Crucially, we identify a competitive synergy between noise intensity and the 1/f spectral exponent: starting from optimal white noise-induced synchrony, increasing the 1/f exponent while decreasing noise intensity leads to a further enhancement of synchrony, which peaks at a specific parameter regime before diminishing. To experimentally validate these findings, we developed a transcranial 1/f noise stimulation (tFNS) system and applied it to human subjects. Compared to spectrally white noise stimulation, the tFNS more robustly enhanced corticospinal synchrony, consistent with model predictions. These results uncover a functional advantage of scale-free brain noise in driving coordinated neural dynamics, offering a new framework for optimizing non-invasive brain stimulation. More broadly, our findings suggest that the brain may harness stochastic facilitation through adaptive modulation of its aperiodic activity to support ordered macro-dynamics.

biophysics↗
bioRxiv2025

Functional and phylogenetic analysis of placozoan GPCRs reveal the prebilaterian origin of monoaminergic signalling.

Monoamines are biologically active compounds crucial for neurotransmission and various physiological processes. They include neurotransmitters like serotonin, dopamine, and melatonin, which regulate mood, movement, and sleep in humans. In ecdysozoans, monoamines such as tyramine are important for modulating locomotion, learning, and feeding. The monoaminergic signalling system has been considered a bilaterian innovation, with conflicting evidence supporting its existence in earlier branching, non-bilaterian animals. Here, we challenge the bilaterian origin hypothesis by combining large-scale receptor deorphanisation with phylogenetic analyses to identify monoamine receptors from the placozoan Trichoplax adhaerens. We demonstrate that these receptors are homologous to known bilaterian GPCRs, and behavioural assays demonstrate that monoamines like tyramine and tryptamine affect the speed of locomotion and body shape of this animal, respectively. These responses, together with the presence of biosynthetic enzymes for these molecules, reveal that monoaminergic signalling is both active and endogenous in placozoans. Our findings provide compelling evidence for a prebilaterian origin of monoaminergic systems, reshaping our understanding of early nervous system evolution.

evolutionary biology↗