Biology subjects

Dai, A.

Publications and source records attributed to Dai, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Algorithmic Geometry Shapes the Biological Meaning of Thalamocortical Structural Covariance

Neuroimaging studies often derive and discuss structural covariance (SC) as a representation of underlying brain circuitry that reflects coordinated maturation, anatomical connectivity, transcriptional similarity, and shared genetic influences. These associations motivate its use to study brain organization across development, aging, and disease. However, the algorithms used to derive SC networks impose constraints that may shape their biological interpretation. To understand the impact of algorithm choice, we used the thalamocortical system as an example and compared five common representations of voxelwise SC, namely, principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), orthogonal projective NMF (OPNMF), and \textit{k}-means clustering, in 755 participants aged 8--22 years from the Philadelphia Neurodevelopmental Cohort (PNC). SC networks derived from deformation-based morphometry (DBM) were evaluated against three complementary biological benchmarks: age-related individual differences, fractional-anisotropy (FA)-based microstructural connectivity of regionally-specific thalamocortical connections, and Allen Human Brain Atlas gene expression. Each algorithm demonstrated underlying sensitivity to differing aspects of neurobiology: PCA and OPNMF showed the strongest associations between participant-level component weights and age. NMF, OPNMF, and \textit{k}-means showed greater spatial overlap between positive cortical SC and tractography-derived projections. ICA and PCA showed stronger correspondence between thalamic and cortical gene-expression profiles across the transcriptome, whereas NMF, OPNMF, and \textit{k}-means more often identified thalamic components with relatively high core-matrix gene expression. This study emphasizes that algorithmic constraints effectively act as biological priors and decomposition methods do not provide neutral compression of the data. We conclude that it is critical to consider whether the algorithmic objective matches the representational geometry of the neurobiology being studied. Overall, our findings suggest that SC studies should select and justify algorithms according to the biological question, explicitly considering whether their constraints favour distributed gradients, overlapping regional parts, or discrete clusters. Meanwhile, interpretations of SC findings could also be informed by the specific algorithmic constraints used to derive them.

neuroscience↗

bioRxiv2026

Dietary fiber intake associates with improved survival and microbiomecomposition in allogeneic hematopoietic cell transplantation

Diet is linked to changes in gut microbiota and metabolite production with clinical relevance in several disease settings, although these effects remain poorly defined. We performed prospective, real-time diet monitoring (37,929 food items, 3,837 patient days) and longitudinal microbiome and metabolite profiling (1,230 fecal samples) in a clinical cohort of 173 patients undergoing allogeneic hematopoietic cell transplantation. Patients with pre-transplant fiber intake above the cohort average had significantly improved overall survival (p=0.014) and reduced incidence of grades 2-4 acute graft-versus-host disease (GVHD) (p=0.032) post-transplant. Those consuming insoluble fiber had increased microbial diversity, enriched butyrate-producing taxa, and depleted Enterococcus. Those who developed lower gastrointestinal GVHD had reduced fecal butyrate levels. In a GVHD preclinical model, we confirmed that a fiber-enriched diet increased survival, cecal butyrate, and regulatory-to-conventional T cell ratio. Thus, we demonstrated that dietary fiber has clinical significance as a modifiable factor with microbiome-mediated effects.

cancer biology↗

bioRxiv2026

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

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

bioinformatics↗

bioRxiv2026

Open neuroinformatics infrastructure ecosystem for federated multisite studies

Despite growing understanding of the benefits of having Findable, Accessible, Interoperable, and Reusable (FAIR) data, many datasets still cannot be shared. Federated analysis methods can enable multisite studies that do not require the sharing of participant-level information. However, there are many practical hurdles that prevent the large-scale adoption of federated methods. We discuss challenges related to cross-site data preparation for federated learning, present solutions offered by recent neuroinformatics projects, and showcase an example of tool integration applied to neurodegenerative disease data.

neuroscience↗

bioRxiv2025

Correlating High-dimensional longitudinal microbial features with time-varying outcomes with FLORAL

Correlating time-dependent patient characteristics and matched microbiome samples can identify biomarkers in longitudinal microbiome studies. Existing approaches typically repeat a pre-specified modeling approach for all taxonomic features, followed by a multiple testing adjustment step for false discovery rate (FDR) control. In this work, we develop an alternative strategy of using log-ratio penalized generalized estimating equations, which directly models the longitudinal patient characteristic of interest as the outcome variable and treats microbial features as high-dimensional compositional covariates. A cross validation procedure is developed for variable selection and model selection among different working correlation structures. In extensive simulations, the proposed method achieved superior sensitivity over the state-of-the-art methods with robustly controlled FDR. In the analyses of correlating longitudinal dietary intake, bloodstream infection status, and microbial features from matched samples of cancer patients, the proposed method effectively identified gut health indicators and clinically relevant microbial markers, showing robust utilities in real-world applications. The method is implemented under the open-source R package FLORAL, which is available at (https://vdblab.github.io/FLORAL/).

bioinformatics↗

bioRxiv2025

Multiple interactions mediate the localization of BLTP2 at ER-PM contacts to control plasma membrane dynamics

BLTP2/KIAA0100, a bridge-like lipid transfer protein, was reported to localize at contacts of the endoplasmic reticulum (ER) with either the plasma membrane (PM) or recycling tubular endosomes depending on the cell type. Our findings suggest that mediating bulk lipid transport between the ER and the PM is a key function of this protein as BLTP2 tethers the ER to tubular endosomes only after they become continuous with the PM and that it also tethers the ER to macropinosomes in the process of fusing with the PM. We further identify interactions underlying binding of BLTP2 to the PM, including phosphoinositides, the adaptor proteins FAM102A and FAM102B, and also N-BAR domain proteins at membrane-connected tubules. The absence of BLTP2 results in the accumulation of intracellular vacuoles, many of which are connected to the plasma membrane, pointing to a role of the lipid transport function of BLTP2 in the control of PM dynamics.

cell biology↗

bioRxiv2024

Sugar-rich foods exacerbate antibiotic-induced microbiome injury

Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury. One Sentence SummaryAnalyses of hematopoietic cell transplant patients and of mice uncover links between foods and microbiome disruption.

microbiology↗

bioRxiv2024

GPR30 in spinal cholecystokinin-positive neurons modulates neuropathic pain via mediating descending facilitation

Neuropathic pain, a major health problem affecting 7-10% of the global population, lacks effective treatment due to its elusive mechanisms. Cholecystokinin-positive (CCK+) neurons in the spinal dorsal horn (SDH) are critical for neuropathic pain, yet the underlying molecular mechanisms remain unclear. Here, we show that the membrane estrogen receptor G-protein coupled estrogen receptor (GPER/GPR30) in spinal neurons was significantly upregulated in chronic constriction injury (CCI) mice and that inhibition of GPR30 in CCK+ neurons reversed CCI-induced neuropathic pain. Furthermore, GPR30 in spinal CCK+ neurons was essential for the enhancement of AMPA-mediated excitatory synaptic transmission in CCI mice. Moreover, GPR30 was expressed in spinal CCK+ neurons that received direct projection from the primary sensory cortex (S1-SDH). Chemogenetic inhibition of S1-SDH post-synaptic neurons alleviated CCI-induced neuropathic pain. Conversely, chemogenetic activation of these neurons mimicked neuropathic pain symptoms, which were attenuated by spinal inhibition of GPR30. Finally, we confirmed that GPR30 in S1-SDH post-synaptic neurons was required for CCI-induced neuropathic pain. Taken together, our findings suggest that GPR30 in spinal CCK+ neurons and S1-SDH postsynaptic neurons is pivotal for neuropathic pain, thereby representing a promising therapeutic target for neuropathic pain.

neuroscience↗

bioRxiv2024

Molecular mechanisms of uric acid transport by the native human URAT1 and its inhibition by anti-gout drugs

Gout, a common and painful disease, stems from hyperuricemia, where elevated blood uric acid levels lead to urate crystal formation in joints and kidneys. The human urate transporter 1 (hURAT1) plays a critical role in urate homeostasis by facilitating urate reabsorption in the renal proximal tubule, making it a key target for gout therapy. Pharmacological inhibition of hURAT1 with drugs such as dotinurad, benzbromarone, lesinurad, and verinurad promotes uric acid excretion and alleviates gout symptoms. Here we present cryo-electron microscopy structures of native hURAT1 bound with these anti-gout drugs in the inward-open state, and with uric acid in inward-open, outward-open, and occluded states. Complemented by mutagenesis and cell-based assays, these structures reveal the mechanisms of uric acid reabsorption and hURAT1 inhibition. Our findings elucidate the molecular basis of uric acid transport and anti-gout medication action, and provide a structural framework for the rational design of next-generation therapies for hyperuricemia and gout.

biochemistry↗

bioRxiv2023

Investigating individual variability in microstructural-functional coupling in the human cortex

Understanding the relationship between the structural and functional architecture of the human brain remains a key question in neuroscience. In this regard variation in cortical myelin may provide key insights into the functional organization. Previous findings have demonstrated that regions sharing myeloarchitectonic features are also likely to be structurally and functionally connected. However, this association is not uniform for all regions. For example, the strength of the association, or coupling, between microstructure and function is regionally heterogeneous, with strong coupling in primary cortices but weaker coupling in higher order transmodal cortices. However, the bases of these observations have been typically made at the group level, leaving much to be understood regarding the individual-level behavioural relevance of microstructural-functional coupling variability. To examine this critical question, we apply a multivariate framework to a combination of high-resolution structural, diffusion, and functional magnetic resonance imaging (MRI) data in a sample of healthy young adults. We identify four distinct patterns of coupling variation that vary across individuals. Remarkably, we find that while microstructural-functional coupling is consistently strong in primary cortices, significant variation in transmodal cortices exists. Importantly, we identified coupling variability maps and their association with behaviour that demonstrate the existence of latent dimensions of variability related to inter-individual performance on cognitive tasks. These findings suggest that the existence of behaviourally relevant coupling variation is a key principle for brain organization.

neuroscience↗

bioRxiv2023

Scalable Log-ratio Lasso Regression Enhances Microbiome Feature Selection for Predictive Models

Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL (https://vdblab.github.io/FLORAL/), an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility of longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance testing methods for datasets with smaller sample size. In a survival analysis in allogeneic hematopoietic-cell transplant, we further demonstrated considerable improvement by FLORAL in microbial feature selection by utilizing longitudinal microbiome data over only using baseline microbiome data.

bioinformatics↗

bioRxiv2023

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimers Disease. They are indicative of vascular pathology but represent a mixture of microstructural tissue alterations that is highly variable between individuals. To better understand these alterations, we leveraged the signal of different MRI contrasts sampled within WMHs, which have differential sensitivity to microstructural properties. Subsequently, we sought to examine the asso of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimers Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimers Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimers Disease (n=9) as a means of ascertaining a spectrum of impairment. We sampled the median signal within WMHs on weighted MRI images that are commonly acquired (T1-weighted [T1w], T2-weighted [T2w], T1w/T2w ratio, Fluid-Attenuated Inversion Recovery [FLAIR]), and the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. Main analyses were performed with a periventricular/deep/superficial white matter parcellation and were repeated with a lobar white matter parcellation. We demonstrated that the correlations between WMH signal measures were variable, suggesting that they are likely influenced by different microstructural properties. We observed that the WMH qT2* and FLAIR measures displayed different age- and disease-related trends compared to normal-appearing white matter, highlighting sensitivity to WMH-specific tissue deterioration. Further, WMH qT2* particularly in periventricular and occipital white matter regions was consistently associated with several of our clinical variables of interest using both parcellation schemes in univariate analyses, and further showed high contributions to a pattern of brain variables that was associated with age and cognitive variables in multivariate Partial Least Squares Correlation analyses. qT1 and FLAIR measures showed consistent clinical relationships in multivariate analyses only, while T1w, T2w, and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to WMHs. Combining volumetric and signal measures of WMH, particularly qT2* and to a lesser extent qT1 and FLAIR, should be considered to more precisely characterize the severity of WMHs in vivo. These findings may have implications in determining the reversibility of WMHs and potential efficacy of cardio- and cerebrovascular treatments.

neuroscience↗

bioRxiv2022

Molecular recognition of two endogenous hormones by the human parathyroid hormone receptor-1

Parathyroid hormone (PTH) and PTH-related peptide (PTHrP) are two endogenous hormones recognized by PTH receptor -1 (PTH1R), a member of class B G protein couple receptors (GPCRs). Both PTH and PTHrP analogs including teriparatide and abaloparatide, are approved drugs for osteoporosis, but they exhibit distinct pharmacology. Here we report two cryo-EM structures of human PTH1R bound to PTH and PTHrP in the G protein-bound state at resolutions of 2.6 and 3.2 [A], respectively. Detailed analysis of these structures uncovers both common and unique features for the agonism of PTH and PTHrP. Molecular dynamics (MD) simulation and together with site-directed mutagenesis studies reveal the molecular basis of endogenous hormones recognition specificity and selectivity to PTH1R. These results provide a rational template for the clinical use of PTH and PTHrP analogs as an anabolic therapy for osteoporosis and other disorders.

biochemistry↗

bioRxiv2022

Minimizing the elastic energy of growing leaves by conformal mapping

During morphogenesis, the shape of living species results from growth, stress relaxation and remodeling. When the growth does not generate any stress, the body shape only reflects the growth density. In two dimensions, we show that stress free configurations are simply determined by the time evolution of a conformal mapping which concerns not only the boundary but also the displacement field during an arbitrary period of time inside the sample. Fresh planar leaves are good examples for our study: they have no elastic stress, almost no weight, and their shape can be easily represented by holomorphic functions. The growth factor, isotropic or anisotropic, is related to the metrics between the initial and current conformal maps. By adjusting the mathematical shape function, main characteristics such as tips (convex or concave or sharp-pointed), undulating borders and veins, can be mathematically recovered, which are in good agreement with observations. It is worth mentioning that this flexible method allows to study complex morphologies of growing leaves such as the fenestration process in Monstera deliciosa, and can also shed light on many other 2D biological patterns.

biophysics↗

bioRxiv2022

The TaxUMAP atlas: efficient display of large clinical microbiome data reveals ecological competition involved in protection against bacteremia

The microbiome is associated with health and disease, but causal effects are hard to quantify-- especially in humans where controlled experiments are nearly impossible. Akin to natural experiments, closely monitored patients offer an alternative to characterize microbiome effects. We present TaxUMAP, a taxonomically-informed visualization method to effectively display diverse microbiome states. TaxUMAP charts a microbiome atlas from 1,870 cancer patients as they progress through therapy-induced perturbations, and quantifies the microbiome contribution to patients risk for life-threatening bacteremia. We find that the lowest diversity states (gut dominations) that follow antibiotic treatments are stable, and that diverse communities harbor more diverse antimicrobial resistance genes than dominations. We reveal that certain Klebsiella species are associated with reduced risk for bacteremia, an effect driven by bacterial competition that we validate experimentally in vitro and in vivo. TaxUMAP effectively maps longitudinal microbiome data that can facilitate research into causal microbiome effects on human health. HIGHLIGHTSO_LITaxUMAP charts an atlas of patients microbiome states and their clinical context to reveal new causal effects. C_LIO_LIAntibiotics deplete the biodiversity and reduce the number of different antimicrobial resistance genes in the gut microbiome. C_LIO_LICertain Klebsiella species are associated with lower risk of bacteremia by other gut-borne pathogens. C_LIO_LIThese Klebsiella outcompete other gram-negative pathogens in vivo. C_LI

microbiology↗

bioRxiv2022

Human Brain Development: a cross-sectional and longitudinal study integrating multiple neuromorphological features

Brain maturation studies typically examine relationships linking a single morphometric feature with aspects of cognition, behavior, age, or other demographic characteristics. However, the coordinated spatiotemporal arrangement of morphological features across development and their associations with behavior are unclear. Here, we examine covariation across multiple cortical features (cortical thickness [CT], surface area [SA], local gyrification index [GI], and mean curvature [MC]) using magnetic resonance images from the long-running National Institute of Mental Health developmental cohort (ages 5-25). Neuroanatomical covariance was examined using non-negative matrix factorization (NMF), which decomposes covariance resulting in a parts-based representation. Cross-sectionally, we identified six components of covariation which demonstrate differential contributions of CT, GI, and SA in hetero- vs. unimodal areas. We sought to use this technique longitudinally to examine covariance in rates of change, which highlighted a preserved SA in unimodal areas and changes in CT and GI in heteromodal areas. Using behavioral partial least squares (PLS), we identified a single latent variable (LV; 96 % covariance explained) that recapitulated patterns of reduced CT, GI, and SA that are generally related to older age, with limited contributions of IQ and SES. Longitudinally, PLS revealed three LVs that demonstrated a nuanced developmental pattern that highlighted a higher rate of maturational change in SA and CT in higher IQ and SES females. This novel characterization of brain maturation provides an important understanding of the interdependencies between morphological measures, their coordinated development, and their relationship to biological sex, cognitive ability, and the resources of the local environment. SignificanceThe complex anatomy of the cortical sheet is best characterized using multiple morphometric characteristics. We expanded on recent developments in matrix factorization to identify spatial patterns of covariance across the cortical sheet. Using a large, well-characterized dataset, we examined the differential contributions of neuroanatomical features to cortical covariation in a single analytical framework using both cross-sectional and longitudinal data. We identified dominant modes of covariance between cortical morphometric features and their coordinated pattern of change, demonstrating sexually differentiated patterns and a strong association with variability in age, socioeconomic status, and cognitive ability. This novel characterization of cortical morphometry provides an important understanding of the interdependencies between neuroanatomical measures in the brain and behavioral development context.

neuroscience↗

bioRxiv2022

Ligand-independent modulation of GIPR signaling by splice variants

Glucose-dependent insulinotropic polypeptide receptor (GIPR) is a potential drug target for metabolic disorders. It works with glucagon-like peptide-1 receptor (GLP-1R) and glucagon receptor (GCGR) in humans to maintain glucose homeostasis. Unlike the other two receptors, GIPR has at least 7 reported (EMBL-EBI, 2022; NCBI, 2022a, 2022b) splice variants (SVs) with previously undefined functions. To explore their roles in endogenous peptide mediated GIPR signaling, we investigated the outcome of co-expressing each of the four SVs in question with GIPR in terms of ligand binding, cAMP accumulation, Gs activation, {beta}-arrestin recruitment and cell surface localization. The effects of these SVs on intracellular cAMP responses modulated by receptor activity-modifying proteins (RAMPs) were also studied. It was found that while SVs of GIPR neither bound to the hormone nor affected its signal transduction per se, they differentially regulated GIPR-mediated cAMP and {beta}-arrestin responses. Specifically, SV1 and SV4 were preferable to Gs signaling, SV3 was biased towards {beta}-arrestin recruitment, whereas SV2 was inactive on both pathways. In the presence of RAMPs, only SV1 and SV4 synergized the repressive action of RAMP3 on GIP-elicited cAMP production. The results suggest a new form of signal bias that is constitutive and ligand-independent, thereby expanding our knowledge of biased signaling beyond pharmacological manipulation (i.e., ligand specific) as well as constitutive and ligand-dependent (e.g., SV1 of the growth hormone-releasing hormone receptor).

molecular biology↗

bioRxiv2022

Structural basis of peptidomimetic agonism revealed by small molecule GLP-1R agonists Boc5 and WB4-24

Glucagon-like peptide-1 receptor (GLP-1R) agonists are effective in treating type 2 diabetes and obesity with proven cardiovascular benefits. However, most of them are peptides and require subcutaneous injection except for orally available semaglutide. Boc5 was identified as the first orthosteric non-peptidic agonist of GLP-1R that mimics a broad spectrum of bioactivities of GLP-1 in vitro and in vivo. Here, we report the cryo-electron microscopy structures of Boc5 and its analog WB4-24 in complex with the human GLP-1R and Gs protein. Bound to the extracellular domain, extracellular loop 2, and transmembrane (TM) helices 1, 2, 3 and 7, one arm of both compounds inserted deeply into the bottom of the orthosteric binding pocket that is usually accessible by peptidic agonists, thereby partially overlapping with the residues A8-D15 in GLP-1. The other three arms, meanwhile, extended to the TM1-TM7, TM1-TM2, and TM2-TM3 clefts showing an interaction feature substantially similar to a previously known small molecule agonist LY3502970. Such a unique binding mode creates a distinct conformation that confers both peptidomimetic agonism and biased signaling induced by non-peptidic modulators at GLP-1R. Further, the conformational difference between Boc5 and WB4-24, two closed related compounds, provides a structural framework for fine tuning of pharmacological efficacy in the development of future small molecule therapeutics targeting GLP-1R. SignificanceGLP-1R agonists are efficacious in the treatment of type 2 diabetes and obesity. While most clinically used agents require subcutaneous injection, Boc5, as the first orthosteric non-peptidic agonist of GLP-1R, suffers from poor oral bioavailability that hinders its therapeutic development. The cryo-electron microscopy structures of Boc5 and its closely related analog WB4-24 presented here reveal a previously unknown binding pocket located deeper in the transmembrane domain for non-peptidic GLP-1R agonists. Molecular interaction with this site may facilitate a broad spectrum of in vivo agonistic activities, in addition to that with the upper helical bundles presumably responsible for biased signaling. These findings deepen our understanding of peptidomimetic agonism at GLP-1R and may help design better drug leads against this important target.

molecular biology↗