Biology subjects

Xie, H.

Publications and source records attributed to Xie, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Elucidating the neuropathological and molecular heterogeneity of amyloid-beta and tau in Alzheimer's disease through machine learning and transcriptomic integration

Discerning functional brain network variations related to neuropathological aggregates in Alzheimers disease (AD), including amyloid-{beta} (A{beta}) and phosphorylated tau (p-tau), is crucial for understanding their link to cognitive decline and underlying molecular mechanisms. However, these variations are often confounded by normal aging-related changes, complicating interpretation. To address this challenge, we first defined Alzheimers continuum cases (A{beta} positive (A+), n = 129) and normal elderly (A{beta} negative (A-), n = 160) using cerebral spinal fluid amyloid levels, and then applied a novel deep learning approach to resting-state connectivity using functional magnetic resonance imaging (fMRI) of the 289 subjects to disentangle A+-specific dimensions in brain network alterations from those shared with A- individuals. The identified A+-specific dimensions were further refined to predict individual A{beta} and p-tau levels separately. We observed that resulting brain signatures, defined from A+-specific dimensions for predicting these two CSF biomarkers, were both attributed to the right superior temporal and anterior cingulate cortices and associated with attention and memory domains. When linking the brain signatures to gene expression data from a public transcriptomic atlas, we found that the brain signatures were associated with molecular pathways involving synaptic dysfunction and disruptions in pathways containing activity of excitatory neurons, astrocytes, and microglia. For A--shared dimensions, the A{beta}-linked brain signature involved the left fusiform and right middle cingulate cortices, correlating with the language cognitive measurement and language-related molecular pathways. The p-tau-linked signature predominantly involved the right insula and inferior temporal cortices, correlating with the aging-related molecular pathways. Collectively, our findings provided new insights in understanding of Alzheimers continuum pathological biomarkers.

neuroscience↗

bioRxiv2024

Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression

BackgroundMajor depressive disorder (MDD) is a prevalent psychiatric disorder characterized by substantial clinical and neurobiological heterogeneity. Conventional studies that solely focus on clinical symptoms or neuroimaging metrics often fail to capture the intricate relationship between these modalities, limiting their ability to disentangle the complexity in MDD. Moreover, patient neuroimaging data typically contains normal sources of variance shared with healthy controls, which can obscure disorder-specific variance and complicate the delineation of disease heterogeneity. MethodsWe employed contrastive principal component analysis to extract disorder-specific variations in fMRI-based resting-state functional connectivity (RSFC) by contrasting MDD patients (N=233) with age-matched healthy controls (N=285). We then applied sparse canonical correlation analysis to identify latent dimensions in the disorder variations by linking the extracted contrastive connectivity features to clinical symptoms in MDD patients. ResultsTwo significant and generalizable dimensions linking distinct brain circuits and clinical profiles were discovered. The first dimension, associated with an apparent "internalizing-externalizing" symptom dimension, was characterized by self-connections within the visual network and also associated with choice reaction times of cognitive tasks. The second dimension, associated with personality facets such as extraversion and conscientiousness typically inversely associated with depression symptoms, is primarily driven by self-connections within the dorsal attention network. This "depression-protective personality" dimension is also associated with multiple cognitive task performances related to psychomotor slowing and cognitive control. ConclusionsOur contrastive RSFC-based dimensional approach offers a new avenue to dissect clinical heterogeneity underlying MDD. By identifying two stable, neurophysiology-informed symptom dimensions in MDD patients, our findings may enhance disease mechanism insights and facilitate precision phenotyping, thus advancing the development of targeted therapeutics for precision mental health. Trial RegistrationEstablishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094

neuroscience↗

bioRxiv2024

Diversity and characteristics of the oral microbiome influenced by race and ethnicity

Periodontitis disproportionately affects racial/ethnic populations. Besides social determinants contributing to disparities in periodontal health, variations of oral microbial communities may also be a key factor influencing oral immune responses. To characterize the oral microbiome from different racial/ethnic populations, we collected 161 dental plaque samples from African Americans (AAs), Caucasian Americans (CAs), and Hispanic Americans (HAs) with clinical gingival health or biofilm-induced gingivitis on an intact periodontium. Using metagenomic sequencing, we found significant difference in diversity and abundance of microbial taxa in the dental plaque samples from AA, CA, and HA groups and unique microbial species that can only be detected in a particular racial/ethnic group. Moreover, we revealed racial/ethnic associated variations in functional potential of the oral microbiome, showing that diversity and abundance of antibiotic resistant genes were greater in the oral microbiome of the AAs than those in CAs or HAs, and that the AAs exhibited higher levels of genes involving in modification of glycoconjugates, oligo- and polysaccharides. These findings indicate more complex and higher virulence potential oral microbiome in AA and HA populations, which likely contributes to higher prevalence of periodontitis in AAs and HAs. ImportanceRecognizing the variations in the oral microbiome among racial/ethnic populations offers insight into the microbial determinants contributing to oral health disparities. In the study presented here, we found a higher level of bleeding on probing (BOP), an indicator of tissue inflammatory response, in the AA group, which is correspondence with a more complex oral microbiome detected in this group. Our observations suggest that the variations of the oral microbiome associated with racial/ethnic backgrounds may directly relate to their virulence potential including their abilities to induce host immune responses and to resist antibiotic treatment. Therefore, these finding can be a stepping stone for developing precision medicine and personalized periodontal prevention/treatment and for reducing oral health disparities.

microbiology↗

bioRxiv2024

INCOMPATIBILITY GROUPS OF PSEUDOMONAS PLASMIDS REVISITED: COMPREHENSIVE ANALYSIS OF R-FACTORS AND THEIR REPLICONS

Plasmids are the most influential engines of bacterial evolution and horizontal gene transfer, fueling the global spread of traits such as antimicrobial resistance. Their deep evolutionary relationships, however, remain difficult to resolve because current classification schemes are constrained by host range and nucleotide similarity. Replication initiation proteins (RIPs), which govern plasmid persistence and diversification, also remain poorly annotated across public databases. Here we establish PInc, a curated and experimentally grounded replicon classification framework anchored in historically defined incompatibility groups of Pseudomonas plasmids. Homology searches beyond PInc revealed that most replication initiators analyzed here share a conserved winged-helix (WH) domain, defining a broad WH RIP superfamily. Using the conserved WH region, we reconstructed a large-scale phylogeny that linked WH RIPs to over 100,000 plasmids, representing approximately half of those analyzed across public databases. This phylogeny resolved eight major clades and the deep split between the single- and double-winged-helix superclades, while revealing clade-specific host and environmental distributions and substantial RIP diversity not captured by current typing tools or annotation schemes. Together, these results overcome the historical host bias of plasmid typing and provide a replication-centered view of plasmid diversification across bacterial lineages and environments.

microbiology↗

bioRxiv2024

ARTIC RSV amplicon sequencing reveals global RSV genotype dynamics.

Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections (LTRIs) in young children and adults over 65, contributing significantly to global healthcare burdens. With the recent approval of multiple pharmacological interventions for RSV, there is an increased demand for efficient, high-throughput sequencing methods to monitor RSV genetic diversity and any potential impact these interventions may have. Here we introduce two novel amplicon-based sequencing schemes designed for RSV A and B, optimised for integration with widespread existing ARTIC sequencing workflows. We demonstrate that these primer schemes can produce high quality genomes from RSV samples across the globe, with eight laboratories in five countries generating complete genomes on both Nanopore and Illumina sequencing platforms. The ability to effectively multiplex these RSV A and B primer schemes, enables streamlined, high-throughput sequencing without prior subtyping. Furthermore, these results provide a snapshot of the circulating diversity of RSV. Phylogenetic analysis of the 882 samples sequenced for this study suggests only minimal geographic clustering of RSV sequences, underscoring the global nature of RSV spread. It also highlights the distinct lineage dynamics seen between RSV A and B. This study represents an advancement in RSV genomics, providing robust tools for global sequencing efforts aimed at tracking RSV evolution and assessing the efficacy of new therapeutic interventions both rapidly and at scale.

genomics↗

bioRxiv2024

Spatial Transcriptomics and Single-Nucleus Multi-omics Analysis Revealing the Impact of High Maternal Folic Acid Supplementation on Offspring Brain Development

Folate, an essential vitamin B9, is crucial for diverse biological processes including neurogenesis. Folic acid (FA) supplementation during pregnancy is a standard practice for preventing neural tube defects (NTDs). However, concerns are growing over the potential risks of excessive maternal FA intake. Here, we employed mouse model and spatial transcriptomics and single-nucleus multi-omics approaches to investigate the impact of high maternal FA supplementation during the periconceptional period on offspring brain development. Maternal high FA supplementation affected gene pathways linked to neurogenesis and neuronal axon myelination across multiple brain regions, as well as gene expression alterations related to learning and memory in thalamic and ventricular regions. Single-nucleus multi-omics analysis revealed that maturing excitatory neurons in the dentate gyrus (DG) are particularly vulnerable to high maternal FA intake, leading to aberrant gene expressions and chromatin accessibility in pathways governing ribosomal biogenesis critical for synaptic formation. Our findings provide new insights into specific brain regions, cell types, gene expressions and pathways that can be affected by maternal high FA supplementation.

neuroscience↗

bioRxiv2024

A systematic evaluation of dynamic functional connectivity methods using simulation data

Numerous dynamic functional connectivity (dFC) methods have been proposed to study time-resolved network reorganization in rest and task fMRI. However, a comprehensive comparison of their performance is lacking. In this study, we compared the efficacy of seven dFC methods (and their enhanced versions) to track transient network reconfiguration using simulation data. The seven methods include flexible least squares (FLS), dynamic conditional correlation (DCC), general linear Kalman filter (GLKF), multiplication of temporal derivatives (MTD), sliding-window functional connectivity with L1-regularization (SWFC), hidden Markov models (HMM), and hidden semi-Markov models (HSMM). Multiple datasets of non-fMRI-BOLD and fMRI-BOLD signals with predefined covariance structures, signal-to-noise ratio levels, and sojourn time distributions were simulated. We adopted inter-subject analysis to eliminate the effects of signals of non-interest, resulting in enhanced methods: ISSWFC, ISMTD, ISDCC, ISFLS, ISKF, ISHMM, and ISHSMM. Efficacy was defined as the spatiotemporal association between simulated and estimated data. We found that all enhanced dFC methods outperformed their original versions. Efficacies depend on several factors, such as considering the neurovascular effect in simulated data, the covariance structure between two time series, state sojourn distribution, and signal-to-noise ratio levels. These results highlight the importance of selecting appropriate dFC methods in fMRI study.

neuroscience↗

bioRxiv2024

Selective illumination on line-scanning confocal mesoscope enhances background rejection in cortex-wide mouse brain imaging

Confocal microscope has optical sectioning that is accessible for structural and dynamic imaging in in vivo mouse brain. With the requirement of brain-wide field-of-view (FOV) in many neuroscience researches, existing confocal microscope fails to fulfill the requirement. Here, we proposed the brain-wide, high resolution line-scan confocal mesoscope (LSCM) for in vivo mouse imaging, achieving 6.6-mm-FOV, 3.2-m-resolution and video-rate acquisition. To further enhance the background rejection ability, we introduced the selective illumination method into our system. We demonstrated that the proposed technique is s able to image the neurodynamics in in vivo mouse brain. Comparing to the LSCM and wide-field mesoscope, our selective illumination line-scan confocal mesoscope improves more than 25% and 3 times background rejection ability, respectively.

bioengineering↗

bioRxiv2024

Silicone Wire Embolization-induced Acute Retinal Artery Ischemia and Reperfusion Model in Mouse: Gene Expression Provide Insight into Pathological Processes

Acute retinal ischemia and ischemia-reperfusion injury are the primary causes of retinal neural cell death and vision loss in retinal artery occlusion (RAO). The absence of an accurate mouse model for simulating the retinal ischemic process has hindered progress in developing neuroprotective agents for RAO. We developed a unilateral pterygopalatine ophthalmic artery occlusion (UPOAO) mouse model using silicone wire embolization combined with carotid artery ligation. The survival of retinal ganglion cells and visual function were evaluated to determine the duration of ischemia. Immunofluorescence staining, optical coherence tomography, and haematoxylin and eosin staining were utilized to assess changes in major neural cell classes and retinal structure degeneration at two reperfusion durations. Transcriptomics was employed to investigate alterations in the pathological process of UPOAO following ischemia and reperfusion, highlighting transcriptomic differences between UPOAO and other retinal ischemia-reperfusion models. The UPOAO model successfully replicated the acute interruption of retinal blood supply observed in RAO. 60-minutes of Ischemia led to significant loss of major retinal neural cells and visual function impairment. Notable thinning of the inner retinal layer, especially the ganglion cell layer, was evident post-UPOAO. Temporal transcriptome analysis revealed various pathophysiological processes related to immune cell migration, oxidative stress, and immune inflammation during the non-reperfusion and reperfusion periods. A pronounced increase in microglia within the retina and peripheral leukocytes accessing the retina was observed during reperfusion periods. Comparison of differentially expressed genes (DEGs) between the UPOAO and high intraocular pressure models revealed specific enrichments in lipid and steroid metabolism-related genes in the UPOAO model. The UPOAO model emerges as a novel tool for screening pathogenic genes and promoting further therapeutic research in RAO.

neuroscience↗

bioRxiv2024

Automated Collective Variable Discovery for MFSD2A transporter from molecular dynamics simulations

Biomolecules often exhibit complex free energy landscapes in which long-lived metastable states are separated by large energy barriers. Overcoming these barriers to robustly sample transitions between the metastable states with classical molecular dynamics (MD) simulations presents a challenge. To circumvent this issue, collective variable (CV)-based enhanced sampling MD approaches are often employed. Traditional CV selection relies on intuition and prior knowledge of the system. This approach introduces bias, which can lead to incomplete mechanistic insights. Thus, automated CV detection is desired to gain a deeper understanding of the system/process. Analysis of MD data with various machine learning algorithms, such as Principal Component Analysis (PCA), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA)-based approaches have been implemented for automated CV detection. However, their performance has not been systematically evaluated on structurally and mechanistically complex biological systems. Here, we applied these methods to MD simulations of the MFSD2A (Major Facilitator Superfamily Domain 2A) lysolipid transporter in multiple functionally relevant metastable states with the goal of identifying optimal CVs that would structurally discriminate these states. Specific emphasis was on the automated detection and interpretive power of LDA-based CVs. We found that LDA methods, which included a novel gradient descent-based multiclass harmonic variant, termed GDHLDA, we developed here, outperform PCA in class separation, exhibiting remarkable consistency in extracting CVs critical for distinguishing metastable states. Furthermore, the identified CVs included features previously associated with conformational transitions in MFSD2A. Specifically, conformational shifts in transmembrane helix 7 and in residue Y294 on this helix emerged as critical features discriminating the metastable states in MFSD2A. This highlights the effectiveness of LDA-based approaches in automatically extracting from MD trajectories CVs of functional relevance that can be used to drive biased MD simulations to efficiently sample conformational transitions in the molecular system. STATEMENT OF SIGNIFICANCETo elucidate the biological mechanisms of pertinent biomolecules, it is crucial to understand their complex free energy landscapes. Such landscapes are often constructed from molecular dynamics (MD) simulations using collective variable (CV)-guided enhanced sampling methods. Identifying proper CVs for this task is critical but can be challenging with traditional intuition-based approaches. Here we propose an automated protocol for CV discovery which is based on linear discriminant analysis (LDA) for dimensionality reduction of MD data. By applying the protocol to MD simulations of the MFSD2A lysolipid transporter, a structurally and mechanistically complex biological system, we show that LDA-based methods efficiently detect system-specific CVs that accurately classify different metastable states of MFSD2A and are highly interpretable in a detailed structural context.

biophysics↗

bioRxiv2024

Longitudinal Exposomics in a Multiomic Wellness Cohort Reveals Distinctive and Dynamic Environmental Chemical Mixtures in Blood

Chemical exposomes can now be comprehensively measured in human blood, but robust application of chemical exposomics in cohort studies requires knowledge of the longitudinal stability and interindividual variability of exogenous molecular profiles. Here we applied chemical exposomics to plasma of 46 adults, each sampled six times over two years in a multiomic wellness cohort. New chemicals were discovered, distinctive co-exposure patterns were observed, and intra-class correlation coefficients (ICC) for 519 confidently annotated substances are reported to support study design. Longitudinal stability of the chemical exposome (mean ICC 0.30) was significantly lower than the proteome, metabolome, lipidome or microbiome, and must be measured more frequently than other molecular profiles in health studies. Mixed-effects models nevertheless revealed significant associations between testosterone and perfluoroalkyl substances, and significant time-trends for low and high stability exposures alike. Complex exposome data structures were visualized and explored, demonstrating great potential for longitudinal exposomics in precision health research. TeaserThe first cohort-level application of longitudinal exposomics revealed novel and dynamic co-exposures in blood of relevance to precision health.

pharmacology and toxicology↗

bioRxiv2024

The selective cargo loading and release functions of the cellular sterol transporter StarD4 are allosterically controlled by the recognition of specific PIP2 subtypes in thetargeted membranes.

StarD4 is an intracellular cholesterol trafficking protein that facilitates the crucial non-vesicular sterol transport between the plasma membrane and the endoplasmic reticulum. It targets both sterol donor and acceptor membranes via interactions with anionic lipids. Experiments have illuminated the kinetics of this sterol transfer and shown it to be modulated by specific phosphatidylinositol phosphates (PIPs) on the target membrane. The distinct subtype distribution of PIPs in the membranes of cellular organelles serves as a guide to direct StarD4 to recognized cell components. However, little is known about the molecular mechanism of the recognition of the PIP2 subtype by StarD4, and how this affects the direction and kinetics of cholesterol transport, as the reaction pathways of the cholesterol uptake and release processes in StarD4 have never been observed. Here, we investigated 1)-how StarD4 transports a cholesterol from/to membranes; 2)-how StarD4 recognizes PIP2-subtypes in membranes; and 3)-how the PIP2-subtype recognition impacts cholesterol transport kinetics, using extensive molecular dynamics (MD) sampling with advanced machine learning and information theory methods for trajectory analysis. The findings revealed function-related allosteric dynamics of StarD4, connecting the identified PIP2-subtype-specific conformational states to the cholesterol binding modes in the pocket, which steers the dynamics of the gates towards conformations that support either cholesterol release or uptake. This reveals the crucial role of PIP2 subtypes in shaping functional StarD4 motifs responsible for organelle selectivity of the cholesterol trafficking, providing fundamental insights into cellular cholesterol regulation.

biophysics↗

bioRxiv2024

scDTL: single-cell RNA-seq imputation based on deep transfer learning using bulk cell information

MotivationThe growing amount of single-cell RNA sequencing (scRNA-seq) data allows researchers to investigate cellular heterogeneity and gene expression profiles, providing a high-resolution view of transcriptome at the single-cell level. However, dropout events, which are often present in scRNA-seq data, remain challenges for downstream analysis. Although a number of studies have been developed to recover single-cell expression profiles, their performance is sometimes limited by not fully utilizing the inherent relations between genes. ResultsTo address the issue, we propose a deep transfer learning based approach called scDTL for scRNA-seq data imputation by exploring the bulk RNA-sequencing information. scDTL firstly trains an imputation model for bulk RNA-seq data using a denoising autoencoder (DAE). We then apply a domain adaptation architecture that builds a mapping between bulk gene and single-cell gene domains, which transfers the knowledge learned by the bulk imputation model to scRNA-seq learning task. In addition, scDTL employs a parallel operation with a 1D U-Net denoising model to provide gene representations of varying granularity, capturing both coarse and fine features of the scRNA-seq data. At the final step, we use the cross-channel attention mechanism to fuse the features learned from the transferred bulk imputer and U-Net model. In the evaluation, we conduct extensive experiments to demonstrate that scDTL based approach could outperform other state-of-the-art methods in the quantitative comparison and downstream analyses. Contactzhangd@szu.edu.cn or tianj@sustech.edu.cn

bioinformatics↗

bioRxiv2024

Impaired central pattern generators due to abnormal EPHA4 signaling leads to idiopathic scoliosis

Idiopathic scoliosis (IS) is the most common form of spinal deformity with unclear pathogenesis. In this study, we firstly reanalyzed the loci associated with IS, drawing upon previous studies. Subsequently, we mapped these loci to candidate genes using either location-based or function-based strategies. To further substantiate our findings, we verified the enrichment of variants within these candidate genes across several large IS cohorts encompassing Chinese, East Asian, and European populations. Consequently, we identified variants in the EPHA4 gene as compelling candidates for IS. To confirm their pathogenicity, we generated zebrafish mutants of epha4a. Remarkably, the zebrafish epha4a mutants exhibited pronounced scoliosis during later stages of development, effectively recapitulating the IS phenotype. We observed that the epha4a mutants displayed defects in left-right coordination during locomotion, which arose from disorganized neural activation in these mutants. Our subsequent experiments indicated that the disruption of the central pattern generator (CPG) network, characterized by abnormal axon guidance of spinal cord interneurons, contributed to the disorganization observed in the mutants. Moreover, when knocked down efnb3b, the ligand for Epha4a, we observed similar CPG defects and disrupted left-right locomotion. These findings strongly suggested that ephrin B3-Epha4 signaling is vital for the proper functioning of CPGs, and defects in this pathway could lead to scoliosis in zebrafish. Furthermore, we identified two cases of IS in NGEF, a downstream molecule in the EPHA4 pathway. Collectively, our data provide compelling evidence that neural patterning impairments and disruptions in CPGs may underlie the pathogenesis of IS.

genetics↗

bioRxiv2024

Bicyclic pyrrolidine inhibitors of Toxoplasma gondii phenylalanine t-RNA synthetase with antiparasitic potency in vitro and brain exposure

Previous studies have shown that bicyclic azetidines are potent and selective inhibitors of apicomplexan phenylalanine tRNA synthetase (PheRS), leading to parasite growth inhibition in vitro and in vivo, including in models of Toxoplasma infection. Despite these useful properties, additional optimization is required for the development of efficacious treatments of toxoplasmosis from this inhibitor series, in particular to achieve sufficient exposure in the brain. Here, we describe a series of PheRS inhibitors built on a new bicyclic pyrrolidine core scaffold designed to retain the exit-vector geometry of the isomeric bicyclic azetidine core scaffold while offering avenues to sample diverse chemical space. Relative to the parent series, bicyclic pyrrolidines retain reasonable potency and target selectivity for parasite PheRS vs. host. Further structure-activity relationship studies revealed that the introduction of aliphatic groups improved potency, ADME and PK properties, including brain exposure. The identification of this new scaffold provides potential opportunities to extend the analog series to further improve selectivity and potency and ultimately deliver a novel, efficacious treatment of toxoplasmosis. Lay abstractThe inhibition of protein synthesis in parasites has emerged as an attractive strategy to target parasitic diseases such as malaria, cryptosporidiosis, and toxoplasmosis. In this study, we report a new series of small molecules that inhibit the enzyme responsible for loading the amino acid phenylalanine onto its cognate tRNA in the parasite species Toxoplasma, directly upstream of protein synthesis. We show that small molecules in this new series inhibit Toxoplasma parasite growth at low concentrations, and that, orally administered to mice, these molecules achieve high concentrations in the brain, which hold promise for the treatment of forms of toxoplasmosis that result from parasitic brain infection.

microbiology↗

bioRxiv2024

A Systematically Optimized Miniaturized Mesoscope (SOMM) for large-scale calcium imaging in freely moving mice

Understanding how neuronal dynamics gives rise to ethologically relevant behavior requires recording of neuronal population activity via technologies that are compatible with unconstrained animal behavior. However, realizations of cellular resolution head-mounted microscopes for mice have been based on conventional microscope designs that feature various forms of ad-hoc miniaturization and weight reduction measures necessary for compatibility with the weight-limits for free animal behavior. As a result, they have typically remained limited to a small field of view (FOV) or low resolution, a shallow depth range and often remain susceptible to motion-induced artifacts. Here, we present a systematically optimized miniaturized mesoscope (SOMM), a widefield, head-mounted fluorescent mesoscope based on a principled optimization approach that allows for mesoscale, cellular resolution imaging of neuroactivity while offering robustness against motion-induced artifacts. This is achieved by co-optimization of a compact diffractive optical element and the associated computational algorithm under form-factor and weight constraints while maximizing the obtainable FOV, depth of field (DOF), and resolution. SOMM enables recordings of neuronal population activity at up to 16 Hz within a FOV of 3.6 x 3.6 mm2 in the cortex of freely moving mice while featuring 4-{micro}m resolution, a DOF of 300 {micro}m at a weight of less than 2.5 g. We show SOMMs performance of recording large-scale neuronal population activity during social interactions, during conditioning-type experiments and by investigating neurovascular coupling using dual-color imaging.

neuroscience↗

bioRxiv2024

Disrupting CD38-driven T cell dysfunction restores sensitivity to cancer immunotherapy

A central problem in cancer immunotherapy with immune checkpoint blockade (ICB) is the development of resistance, which affects 50% of patients with metastatic melanoma1,2. T cell exhaustion, resulting from chronic antigen exposure in the tumour microenvironment, is a major driver of ICB resistance3. Here, we show that CD38, an ecto-enzyme involved in nicotinamide adenine dinucleotide (NAD+) catabolism, is highly expressed in exhausted CD8+ T cells in melanoma and is associated with ICB resistance. Tumour-derived CD38hiCD8+ T cells are dysfunctional, characterised by impaired proliferative capacity, effector function, and dysregulated mitochondrial bioenergetics. Genetic and pharmacological blockade of CD38 in murine and patient-derived organotypic tumour models (MDOTS/PDOTS) enhanced tumour immunity and overcame ICB resistance. Mechanistically, disrupting CD38 activity in T cells restored cellular NAD+ pools, improved mitochondrial function, increased proliferation, augmented effector function, and restored ICB sensitivity. Taken together, these data demonstrate a role for the CD38-NAD+ axis in promoting T cell exhaustion and ICB resistance, and establish the efficacy of CD38 directed therapeutic strategies to overcome ICB resistance using clinically relevant, patient-derived 3D tumour models.

cancer biology↗

bioRxiv2024

Temporal Dynamics of Cyanobacterial Bloom Community Composition and Toxin Production from Urban Lakes

With a long evolutionary history and a need to adapt to a changing environment, cyanobacteria in freshwater systems use specialized metabolites for communication, defense, and physiological processes. However, the role that these metabolites play in differentiating species, maintaining microbial communities, and generating niche persistence and expansion is poorly understood. Furthermore, many cyanobacterial specialized metabolites and toxins present significant human health concerns due to their liver toxicity and their potential impact to drinking water. Gaps in knowledge exist with respect to changes in species diversity and toxin production during a cyanobacterial bloom (cyanoHAB) event; addressing these gaps will improve understanding of impacts to public and ecological health. In the current project, we utilized a multi-omics strategy (DNA metabarcoding and metabolomics) to determine the cyanobacterial community composition, toxin profile, and the specialized metabolite pool at three freshwater lakes in Providence, RI during summer-fall cyanoHABs. Species diversity decreased at all study sites over the course of the bloom event, and toxin production reached a maximum at the midpoint of the event. Additionally, LC-MS/MS-based molecular networking identified new toxin congeners. This work provokes intriguing questions with respect to the use of allelopathy by organisms in these systems and the presence of emerging toxic compounds that can impact public health. SYNOPSISThis study reports on cyanobacterial community succession and toxin dynamics during cyanobacterial bloom events. Results show relationships and temporal dynamics that are relevant to public health.

pharmacology and toxicology↗