Biology subjects

Liu, A.

Publications and source records attributed to Liu, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Glutamate indicators with increased sensitivity and tailored deactivation rates

Identifying the input-output operations of neurons requires measurements of synaptic transmission simultaneously at many of a neurons thousands of inputs in the intact brain. To facilitate this goal, we engineered and screened 3365 variants of the fluorescent protein glutamate indicator iGluSnFR3 in neuron culture, and selected variants in the mouse visual cortex. Two variants have high sensitivity, fast activation (< 2 ms) and deactivation times tailored for recording large populations of synapses (iGluSnFR4s, 153 ms) or rapid dynamics (iGluSnFR4f, 26 ms). By imaging action-potential evoked signals on axons and visually-evoked signals on dendritic spines, we show that iGluSnFR4s/4f primarily detect local synaptic glutamate with single-vesicle sensitivity. The indicators detect a wide range of naturalistic synaptic transmission, including in the vibrissal cortex layer 4 and in hippocampal CA1 dendrites. iGluSnFR4 increases the sensitivity and scale (4s) or speed (4f) of tracking information flow in neural networks in vivo.

neuroscience↗

bioRxiv2025

OpenSpliceAI: An efficient, modular implementation of SpliceAI enabling easy retraining on non-human species

The SpliceAI deep learning system is currently one of the most accurate methods for identifying splicing signals directly from DNA sequences. However, its utility is limited by its reliance on older software frameworks and human-centric training data. Here we introduce OpenSpliceAI, a trainable, open-source version of SpliceAI implemented in PyTorch to address these challenges. OpenSpliceAI supports both training from scratch and transfer learning, enabling seamless retraining on species-specific datasets and mitigating human-centric biases. Our experiments show that it achieves faster processing speeds and lower memory usage than the original SpliceAI code, allowing large-scale analyses of extensive genomic regions on a single GPU. Additionally, OpenSpliceAIs flexible architecture makes for easier integration with established machine learning ecosystems, simplifying the development of custom splicing models for different species and applications. We demonstrate that OpenSpliceAIs output is highly concordant with SpliceAI. In silico mutagenesis (ISM) analyses confirm that both models rely on similar sequence features, and calibration experiments demonstrate similar score probability estimates.

genomics↗

bioRxiv2025

Spatiotemporal Patterns Differentiate Hippocampal Sharp-Wave Ripples from Interictal Epileptiform Discharges in Mice and Humans

Hippocampal sharp-wave ripples (SPW-Rs) are high-frequency oscillations critical for memory consolidation in mammals. Despite extensive characterization in rodents, their application as biomarkers to track and treat memory dysfunction in humans is limited by coarse spatial sampling, interference from interictal epileptiform discharges (IEDs), and lack of consensus on human SPW-R localization and morphology. We demonstrate that mouse and human hippocampal ripples share spatial, spectral and temporal features, which are clearly distinct from IEDs. In 1024-channel hippocampal recordings from APP/PS1 mice, SPW-Rs were distinguishable from IEDs by their narrow localization to the CA1 pyramidal layer, narrowband frequency peaks, and multiple ripple cycles on the unfiltered local field potential. In epilepsy patients, ripples showed similar narrowband frequency peaks and visible ripple cycles in CA1 and the subiculum but were absent in the dentate gyrus. Conversely, IEDs showed a broad spatial extent and wide-band frequency power. We introduce a semi-automated, human ripple detection toolbox ("ripmap") selecting optimal detection channels and separating event waveforms by low-dimensional embedding. Our approach improves ripple detection accuracy, providing a firm foundation for future human memory research.

neuroscience↗

bioRxiv2025

Haplotype rather than single causal variants effects contribute to regulatory gene expression associations in human myeloid cells

Genome-wide association studies typically identify hundreds to thousands of loci, many of which harbor multiple independent peaks, each parsimoniously assumed to be due to the activity of a single causal variant. Fine-mapping of such variants has become a priority and since most associations are located within regulatory regions, it is also assumed that they colocalize with regulatory variants that influence the expression of nearby genes. Here we examine these assumptions by using a moderate throughput expression CROPseq protocol in which Cas9 nuclease is used to induce small insertions and deletions across the credible set of SNPs that may account for expression quantitative trait loci (eQTL) for genes associated with inflammatory bowel disease (IBD). Of the 4,384 SNPs targeted in 88 loci (an average of 50 per locus), 439 were significant and further examined for validation. From these, 98 significantly altered target gene expression in HL-60 myeloid cell line, 74 in induced macrophages from these HL-60 cells, and 78 in induced neutrophils for a total of 201 validated effects (46%), 43 of which were observed in at least two of the cell types. Considering the observed sensitivity and specificity of the controls, we estimate that there are at least 150 true positives per cell type, an average of almost 2.4 for each of the 64 eQTL for which putative causal variants have been fine-mapped. This implies that haplotype effects are likely to explain many of the associations. We also demonstrate that the same approach can be used to investigate the activity of very rare variants in regulatory regions for 89 genes, providing a rapid strategy for establishing clinical relevance of non-coding mutations.

genomics↗

bioRxiv2024

LINC00599 Promotes Pulmonary Hypertension via LLPS with G3BP1 and MYH9

BACKGROUNDPulmonary hypertension (PH) represents a significant cardiovascular disorder marked by both functional and structural alterations within the pulmonary vasculature. Long non-coding RNAs (lncRNAs) have been closely associated with the pathogenesis and progression of PH. Nonetheless, the precise mechanisms by which lncRNAs interact with its downstream target molecules to modulate the disease remain inadequately elucidated. METHODSThe expression levels of LINC00599 were quantified in the lung tissues of mice and pulmonary arterial smooth muscle cells (PASMCs) under hypoxic conditions. The involvement of LINC00599 in the progression of PH and vascular remodeling was evaluated through in vivo studies. To investigate the mechanisms by which LINC00599 influences the proliferation of human PASMCs, small interfering RNA and overexpression plasmids were employed. RESUITSThe expression of LINC00599 is upregulated in the medial layer of pulmonary arteries in experimental models of PH and in hypoxic PASMCs. Administration of a single dose of lentivirus-mediated shRNA targeting LINC00599 effectively reverses hypoxic PH in murine models. LINC00599 plays a critical role in PASMC proliferation by modulating stress granule formation through N6-methyladenosine (m6A) modification and promoting proliferation via liquid-liquid phase separation with myosin heavy chain 9. Furthermore, the expression of LINC00599 is regulated by a super-enhancer, which is mediated by the transcription factor ZNF263. CONCLUSIONSThese findings demonstrate for the first time that LINC00599, involved in liquid-liquid phase separation, facilitates the progression of pulmonary hypertension by enhancing the proliferation of pulmonary artery smooth muscle cells. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/629439v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@7ac192org.highwire.dtl.DTLVardef@13a88b3org.highwire.dtl.DTLVardef@1e4c761org.highwire.dtl.DTLVardef@ddd105_HPS_FORMAT_FIGEXP M_FIG C_FIG What Is New?This study identified LINC00599 as a critical regulator of liquid-liquid phase separation through m6A modification and as a pivotal target in promoting the progression of PH. What Is Relevant?LncRNAs are intricately associated with the pathogenesis and progression of PH through the modulation of downstream target molecules. However, it remains unclear whether lncRNAs contribute to PH by forming specific subcellular structures with these target molecules. Furthermore, some studies have suggested that the increased presence of stress granules in PASMCs is implicated in the pathogenesis of pulmonary arterial hypertension. In this study, we provide evidence that LINC00599 promotes the development of PH by forming stress granules with its target proteins. Our findings indicate that the binding of LINC00599, modified with m6A, to G3BP1 and MYH9 in PASMCs suggests that the regulation of liquid-liquid phase separation by lncRNA m6A modification may represent a significant pathological mechanism underlying PH. What Are the Pathophysiological Implications?We found that LINC00599 levels were elevated in hypoxic PASMCs and experimental PH models. Knockout LINC00599 effectively prevented PH, indicating its potential as both a bomarker and therapeutic target for PH.

physiology↗

bioRxiv2024

Hydralazine inhibits cysteamine dioxygenase to treat preeclampsia and senesce glioblastoma

The vasodilator hydralazine (HYZ) has been used clinically for [~] 70 years and remains on the World Health Organizations List of Essential Medicines as a therapy for preeclampsia. Despite its longstanding use and the concomitant progress toward a general understanding of vasodilation, the target and mechanism of HYZ have remained unknown. We show that HYZ selectively targets 2-aminoethanethiol dioxygenase (ADO) by chelating its metal cofactor and alkylating one of its ligands. This covalent inactivation slows entry of proteins into the Cys/N-degron pathway that ADO initiates. HYZs capacity to stabilize regulators of G-protein signaling (RGS4/5) normally marked for degradation by ADO explains its effect on blood vessel tension and comports with prior associations of insufficient RGS levels with human preeclampsia and analogous symptoms in mice. The established importance of ADO in glioblastoma led us to test HYZ in these cell types. Indeed, a single treatment induced senescence, suggesting a potential new HYZ-based therapy for this deadly brain cancer.

biochemistry↗

bioRxiv2024

Genome-enabled stilbenoid gene cluster discovery in Pleuropterus multiflorus

Stilbenoids, a class of compounds with the stilbene skeleton as part of plant secondary metabolism, are renowned for their diverse health benefits. Among them, 2,3,5,4'-Tetrahydroxystilbene-2-O-{beta}-D-glucoside (THSG), specifically abundant in the famous medicinal plant Pleuropterus multiflorus, exhibits significant pharmacological properties. A selfing progeny of P. multiflorus commercial variety Jinwufugui No.1, which contains high THSG content, was used for genome sequencing. Through the combination of weighted correlation network analysis, genome mining, and enzymatic characterization studies, we identified an unpredicted biosynthetic gene cluster responsible for THSG biosynthesis. This cluster includes a stilbene synthase (PmSTS1), a flavin-containing monooxygenase (PmFMO3), and a UDP-glycosyltransferase (UGT72B90). Our findings suggest this stilbenoid gene cluster is formed by transposable element-mediated gene duplications and neofunctionalization, and regulated by MYB and NAC type transcription factors. Notably, PmFMO3, as the first identified stilbenoid-2-hydroxylase, was confirmed that it can modify the other stilbenoids without the A ring modifications. The novel type of gene cluster, in which FMO serves as the key decorating enzyme, will guide the identification of more biosynthetic gene clusters in plants. In addition, the characterization of PmFMO3 extends our understanding of the FMO gene function in plants, and provides an important catalytic bioparts for the heterologous synthesis of polyhydroxylated stilbenoids.

molecular biology↗

bioRxiv2024

Reliable odorant sensing but variable associative learning in C. elegans

Animals can move towards or away from an odorant. Such chemotaxis has been used as a paradigm for learning when coupled with pre-exposure to the sensed odorant. Here we develop an assay for the nematode C. elegans that avoids the typical use of chemical or physical immobilization when measuring the response of worms to odorants. Using two sets of rectangular arenas that are oriented such that worms in one set must move in the opposite direction to worms in the other set for the same response, we found that unfed worms show reproducible movement towards the odorants butanone and benzaldehyde, and away from the odorant nonanone. In addition to the use of opposing orientations to control for gradients of unknown cues outside the arena, we introduce a measure of dispersal to control for locomotion defects and unknown cues within the arena. Since this assay avoids the use of paralytics or physical constraints, it is useful for the analysis of graded responses to a variety of chemicals and the discovery of underlying molecular mechanisms. Using this setup, we found that pre-exposure of unfed worms to butanone to induce an association of starvation with butanone resulted in different extents of such associative learning during different trials - from no learning to learned avoidance. Given this variation in associative learning despite the artificially controlled lab setting, we speculate that in dynamic natural environments such learning might be rare and highlight the challenge in discovering evolutionarily selected mechanisms that could underlie learning in the wild.

animal behavior and cognition↗

bioRxiv2024

Accurate de novo design of high-affinity protein binding macrocycles using deep learning

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest. We test 20 or fewer designed macrocycles against each of four diverse proteins and obtain medium to high-affinity binders against all selected targets. Designs against MCL1 and MDM2 demonstrate KD between 1-10 M, and the best anti-GABARAP macrocycle binds with a KD of 6 nM and a sub-nanomolar IC50 in vitro. For one of the targets, RbtA, we obtain a high-affinity binder with KD < 10 nM despite starting from the target sequence alone due to the lack of an experimentally determined target structure. X-ray structures determined for macrocycle-bound MCL1, GABARAP, and RbtA complexes match very closely with the computational design models, with three out of the four structures demonstrating Ca RMSD of less than 1.5 [A] to the design models. In contrast to library screening approaches for which determining binding mode can be a major bottleneck, the binding modes of RFpeptides-generated macrocycles are known by design, which should greatly facilitate downstream optimization. RFpeptides thus provides a powerful framework for rapid and custom design of macrocyclic peptides for diagnostic and therapeutic applications.

biochemistry↗

bioRxiv2024

CellPatch: a Highly Efficient Foundation Model for Single-Cell Transcriptomics with Heuristic Patching

The rapid advancement of foundation models has significantly enhanced the analysis of single-cell omics data, enabling researchers to gain deeper insights into the complex interactions between cells and genes across diverse tissues. However, existing foundation models often exhibit excessive complexity, hindering their practical utility for downstream tasks. Here, we present CellPatch, a lightweight foundation model that leverages the strengths of the cross-attention mechanism and patch tokenization to reduce model complexity while extracting efficient biological representations. Comprehensive evaluations conducted on single-cell RNA-sequencing datasets across multiple organs and tissue states demonstrate that CellPatch achieves state-of-the-art performance in downstream analytical tasks while maintaining ultra-low computational costs during both pretraining and finetuning phases. Moreover, the flexibility and scalability of CellPatch allow it to serve as a general framework that can be incorporated with other well established single-cell analysis software, thereby enhancing their performance through transfer learning on diverse downstream tasks.

bioinformatics↗

bioRxiv2024

Non-invasive imaging of cell-based therapies using acoustic reporter genes

Cell-based therapies are a major emerging category of medicine. The ability of engineered cells to traffic to and function at specific anatomical locations is a major aspect of their performance. However, there is a lack of non-invasive, non-ionizing, cost-accessible methods to track these therapies inside the body and ensure proper function. Here, we establish a platform for in vivo imaging of primary cell therapies using ultrasound - a ubiquitously accessible technology for high-resolution non-invasive imaging. We introduce and optimize a lentiviral delivery system to express acoustic reporter genes based on gas vesicles in primary mammalian cells such as T cells, showing that this results in robust ultrasound contrast. Additionally, we develop genetic circuits making it possible to monitor T cell activation via activity-dependent promoters. We apply this technology to primary human T cells, using it to non-invasively track their accumulation and proliferation as a targeted therapy in a mouse tumor xenograft model and compare it to invasive, terminal measures such as immunohistology. By making it possible to visualize cell-based therapies and their function inside opaque living organs with unprecedented resolution and accessibility, this technology has the potential to significantly accelerate their development and effective use.

bioengineering↗

bioRxiv2024

Multi-View Integrative Approach For Imputing Short-Chain Fatty Acids and Identifying Key factors predicting Blood SCFA

Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of dietary fiber within gastrointestinal tract. SCFAs produced by gut microbiotas (GMs) are absorbed by host, reach bloodstream, and are distributed to different organs, thus influencing host physiology. However, due to the limited budget or the poor sensitivity of instruments, most studies on GMs have incomplete blood SCFA data, limiting our understanding of the metabolic processes within the host. To address this gap, we developed an innovative multi-task multi-view integrative approach (M2AE, Multi-task Multi-View Attentive Encoders), to impute blood SCFA levels using gut metagenomic sequencing (MGS) data, while taking into account the intricate interplay among the gut microbiome, dietary features, and host characteristics, as well as the nuanced nature of SCFA dynamics within the body. Here, each view represents a distinct type of data input (i.e., gut microbiome compositions, dietary features, or host characteristics). Our method jointly explores both view-specific representations and cross-view correlations for effective predictions of SCFAs. We applied M2AE to two in-house datasets, which both include MGS and blood SCFAs profiles, host characteristics, and dietary features from 964 subjects and 171 subjects, respectively. Results from both of two datasets demonstrated that M2AE outperforms traditional regression-based and neural-network based approaches in imputing blood SCFAs. Furthermore, a series of gut bacterial species (e.g., Bacteroides thetaiotaomicron and Clostridium asparagiforme), host characteristics (e.g., race, gender), as well as dietary features (e.g., intake of fruits, pickles) were shown to contribute greatly to imputation of blood SCFAs. These findings demonstrated that GMs, dietary features and host characteristics might contribute to the complex biological processes involved in blood SCFA productions. These might pave the way for a deeper and more nuanced comprehension of how these factors impact human health.

bioinformatics↗

bioRxiv2024

LRRC8 complexes are adenosine nucleotide release channels regulating platelet activation and arterial thrombosis

Platelet shape and volume changes are early mechanical events contributing to platelet activation and thrombosis. Here, we identify single-nucleotide polymorphisms in Leucine-Rich Repeat Containing 8 (LRRC8) protein subunits that form the Volume-Regulated Anion Channel (VRAC) which are independently associated with altered mean platelet volume. LRRC8A is required for functional VRAC in megakaryocytes (MKs) and regulates platelet volume, adhesion, and agonist-stimulated activation, aggregation, ATP secretion and calcium mobilization. MK-specific LRRC8A cKO mice have reduced arteriolar thrombus formation and prolonged arterial thrombosis without affecting bleeding times. Mechanistically, platelet LRRC8A mediates swell-induced ATP/ADP release to amplify agonist-stimulated calcium and PI3K-AKT signaling via P2X1, P2Y1 and P2Y12 receptors. Small-molecule LRRC8 channel inhibitors recapitulate defects observed in LRRC8A-null platelets in vitro and in vivo. These studies identify the mechanoresponsive LRRC8 channel complex as an ATP/ADP release channel in platelets which regulates platelet function and thrombosis, providing a proof-of-concept for a novel anti-thrombotic drug target.

cell biology↗

bioRxiv2024

A near-tight lower bound on the density of forward sampling schemes

MotivationSampling k-mers is a ubiquitous task in sequence analysis algorithms. Sampling schemes such as the often-used random minimizer scheme are particularly appealing as they guarantee at least one k-mer is selected out of every w consecutive k-mers. Sampling fewer k-mers often leads to an increase in efficiency of downstream methods. Thus, developing schemes that have low density, i.e., have a small proportion of sampled k-mers, is an active area of research. After over a decade of consistent efforts in both decreasing the density of practical schemes and increasing the lower bound on the best possible density, there is still a large gap between the two. ResultsWe prove a near-tight lower bound on the density of forward sampling schemes, a class of schemes that generalizes minimizer schemes. For small w and k, we observe that our bound is tight when k {equiv} 1 (mod w). For large w and k, the bound can be approximated by [Formula]. Importantly, our lower bound implies that existing schemes are much closer to achieving optimal density than previously known. For example, with the current default minimap2 HiFi settings w = 19 and k = 19, we show that the best known scheme for these parameters, the double decycling-set-based minimizer of Pellow et al., is at most 3% denser than optimal, compared to the previous gap of at most 50%. Furthermore, when k {equiv} 1 (mod w) and the alphabet size{sigma} goes to {infty}, we show that mod-minimizers introduced by Groot Koerkamp and Pibiri achieve optimal density matching our lower bound. Availability and implementationMinimizer implementations: github.com/RagnarGrootKoerkamp/minimizers ILP and analysis: github.com/treangenlab/sampling-scheme-analysis

bioinformatics↗

bioRxiv2024

A Nerve-Fibroblast Axis in Mammalian Lung Fibrosis

Fibrosis contributes to incurable pathologies in vital organs including the lung. Myofibroblasts are fibrogenic effector cells that accumulate via incompletely understood mechanisms. We discovered that 1-adrenoreceptor expressing myofibroblasts receive sympathetic nerve-derived noradrenergic inputs in fibrotic mouse and human lungs. We combined optical clearing, whole lung imaging, cell-specific gene deletion in sympathetic nerves and myofibroblasts, pharmacologic interventions, sympathetic nerve co-culture and precision-cut lung slices, with analysis of bronchoalveolar lavage fluid, lung tissues, single-cell RNA sequencing datasets, and isolated lung fibroblasts from patients with diverse forms of pulmonary fibrosis to characterize a fibrogenic unit comprised of aberrantly patterned sympathetic nerves and 1-adrenoreceptor subtype D expressing myofibroblasts. The discovery of this previously undefined nerve-fibroblast axis that is conserved across species demonstrates the pivotal contribution of nerves to tissue remodeling and heralds a novel paradigm in fibrosis research.

cell biology↗

bioRxiv2024

Legume genome structures and histories inferred from Cercis canadensis and Chamaecrista fasciculata genomes

O_LIThe legume family originated ca. 70 million years ago and soon diversified into at least six lineages (now extant subfamilies). The signal of whole genome duplications (WGD) is apparent in species sampled from all six subfamilies. The early diversification has posed difficulties for resolving the legume backbone structure and the timing of WGDs. C_LIO_LIIn this study, we report the genome sequences and annotations for Cercis canadensis (Cercidoideae) and Chamaecrista fasciculata (Caesalpinoideae) to help resolve the relative taxonomic placements along the legume backbone, the timings of WGDs relative to subfamily origins, and the ancestral legume karyotype. C_LIO_LIAnalyses of genome assemblies from four subfamilies within Fabaceae show that the last common ancestor of all legumes likely had seven chromosomes, with a genome structure similar to the extant Cercis genome. Our analysis supports an allopolyploid origin of the subfamily Caesalpinoideae, with progenitors involving lineages along the backbone of the legume phylogeny. C_LIO_LIA probable allopolyploid origin of Caesalpinoideae subfamily provides a partial explanation for the difficulty in resolving the structure of the legume backbone. The retained karyotype structure and lack of a WGD in the last 100+ Mya, underscore the utility of the Cercis genome as an ancestral reference for the legume family. C_LI

genomics↗

bioRxiv2024

Natural Language Processing Applied to Spontaneous Recall of Famous Faces Reveals Memory Dysfunction in Temporal Lobe Epilepsy Patients

Objective and BackgroundEpilepsy patients rank memory problems as their most significant cognitive comorbidity. Current clinical assessments are laborious to administer and score and may not always detect subtle memory decline. The Famous Faces Task (FF) has robustly demonstrated that left temporal lobe epilepsy (LTLE) patients remember fewer names and biographical details compared to right TLE (RTLE) patients and healthy controls (HCs). We adapted the FF task to capture subjects entire spontaneous spoken recall, then scored responses using manual and natural language processing (NLP) methods. We expected to replicate previous group level differences using spontaneous speech and semi-automated analysis. MethodsSeventy-three (N=73) adults (28 LTLE, 18 RTLE, and 27 HCs) were included in a case-control prospective study design. Twenty FF in politics, sports, and entertainment (active 2008-2017) were shown to subjects, who were asked if they could recognize and spontaneously recall as much biographical detail as possible. We created human-generated and automatically-generated keyword dictionaries for each celebrity, based on a randomly selected training set of half of the HC transcripts. To control for speech output, we measured the speech duration, total word count and content word count for the FF task and a Cookie Theft Control Task (CTT), in which subjects were merely asked to describe a visual scene. Subjects responses to FF and CTT tasks were recorded, transcribed, and analyzed in a blinded manner with a combination of manual and automated NLP approaches. ResultsFamous face recognition accuracy was similar between groups. LTLE patients recalled fewer biographical details compared to HCs and RTLEs using both the gold-standard human-generated dictionary (24%{+/-}12% vs. 31%{+/-}12% and 30%{+/-}12%, p=0.007) and the automated dictionary (24%{+/-}12% vs. 31%{+/-}12% and 32%{+/-}13%, p=0.007). There were no group level differences in speech duration, total word count, or content word count for either the FF and CTT to explain difference in recall performance. There was a positive, statistically significant relationship between MOCA score and FF recall performance as scored by the human-generated ({rho}= .327, p= .029) and automatically-generated dictionaries ({rho}= .422, p= .004) for TLE subjects, but not HCs, an effect that was driven by LTLE subjects. DiscussionLTLE patients remember fewer details of famous people than HCs or RTLE patients, as discovered by NLP analysis of spontaneous recall. Decreased biographical memory was not due to decreased speech output and correlated with lower MOCA scores. NLP analysis of spontaneous recall can detect memory dysfunction in clinical populations in a semi-automated, objective, and sensitive manner.

neuroscience↗

bioRxiv2024

Closing the genome of Teredinibacter turnerae T7902 by long-read nanopore sequencing

We present the complete closed circular genome sequence derived from Oxford Nanopore sequencing of the shipworm endosymbiont Teredinibacter turnerae T7902 (DSM 15152, ATCC 39867), originally isolated from the shipworm Lyrodus pedicellatus (1). This sequence will aid in the comparative genomics of shipworm endosymbionts and the understanding of host-symbiont evolution.

microbiology↗