Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 253 records · Page 14Linked to original sources

bioRxiv2024

Utility of cellular imaging modality in subcellular spatial transcriptomic profiling of tumor tissues

Spatial transcriptomics (ST) technologies, like GeoMx Digital Spatial Profiler, are increasingly utilized to reveal the role of diverse tumor microenvironment components, particularly in relation to cancer progression, treatment response, and therapeutic resistance. However, in many ST studies, the spatial information obtained from immunofluorescence imaging is primarily used for identifying regions of interest, rather than as an integral part of downstream transcriptomic data interpretation. We developed ROICellTrack, a deep learning-based framework, to better integrate cellular imaging with spatial transcriptomic profiling. By examining 56 ROIs from urothelial carcinoma of the bladder (UCB) and upper tract urothelial carcinoma (UTUC), ROICellTrack accurately identified cancer-immune mixtures and associated cellular morphological features. This approach also revealed different sets of spatial clustering patterns and receptor-ligand interactions. Our findings underscore the importance of combining imaging and transcriptomics for comprehensive spatial omics analysis, offering potential new insights into within-sample heterogeneity and implications for targeted therapies and personalized medicine.

bioinformatics↗

bioRxiv2024

Denoising, Deblurring, and optical Deconvolution for cryo-ET and light microscopy with a physics-informed deep neural network DeBCR

Computational image-quality enhancement for microscopy (deblurring, denoising, and optical deconvolution) provides researchers with detailed information on samples. Recent general-purpose deep learning solutions advanced in this task. Yet, without consideration of the underlying physics, they may yield unrealistic and non-existent details and distortions during image restoration, requiring domain expertise to discern true features from artifacts. Furthermore, the large expressive capacity of general-purpose deep learning models requires more resources to train and use in applications. We introduce DeBCR, a physics-informed deep learning model based on wavelet theory to enhance microscopy images. DeBCR is a light model with a fast runtime and without hallucinations. We evaluated the image restoration performance of DeBCR and 12 current state-of-the-art models over 6 datasets spanning crucial modalities in advanced light microscopy and cryo-electron tomography. Leveraging optic models, DeBCR demonstrates superior performance in denoising, optical deconvolution, and deblurring tasks across both LM and cryo-ET modalities.

bioinformatics↗

bioRxiv2024

A multiomic atlas of human early skeletal development

Bone and joint formation in the developing skeleton rely on co-ordinated differentiation of progenitors in the nascent developing limbs and joints. The cell states, epigenetic processes and key regulatory factors underlying their lineage commitment to osteogenic and other mesenchymal populations during ossification and joint formation remain poorly understood and are largely unexplored in human studies. Here, we apply paired single-nuclei transcriptional and epigenetic profiling of 336,000 droplets, in addition to spatial transcriptomics, to construct a comprehensive atlas of human bone, cartilage and joint development in the shoulder, hip, knee and cranium from 5 to 11 post-conception weeks. Spatial mapping of cell clusters to our highly multiplexed in situ sequencing (ISS) data using our newly developed tool ISS-Patcher revealed new cellular mechanisms of zonation during bone and joint formation. Combined modelling of chromatin accessibility and RNA expression allowed the identification of the transcriptional and epigenetic regulatory landscapes that drive differentiation of mesenchymal lineages including osteogenic and chondrogenic lineages, and novel chondrocyte cell states. In particular, we define regionally distinct limb and cranial osteoprogenitor populations and trajectories across the fetal skeleton and characterise differential regulatory networks that govern intramembranous and endochondral ossification. We also introduce SNP2Cell, a tool to link cell-type specific regulatory networks to numerous polygenic traits such as osteoarthritis. We also conduct in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential pathogenic cell states and disease mechanisms involved. This work forms a detailed and dynamic regulatory atlas of human fetal skeletal maturation and advances our fundamental understanding of cell fate determination in human skeletal development.

developmental biology↗

bioRxiv2024

ANASFV: a workflow for ASFV whole genome sequencing, assembly, and evaluation

African Swine Fever Virus (ASFV) poses an ongoing threat with widespread outbreaks affecting both domestic and wild pig populations globally. Effective management of ASFV outbreaks necessitates a deep understanding of its genetic diversity and evolutionary dynamics. Despite the advantages of nanopore sequencing for genome analysis, its application to ASFV genomes encounters specific challenges, such as high host DNA contamination that reduces viral genome coverage and an inherently higher error rate producing small insertions and deletions (indels). Another notable issue is the lack of standardized methods for assessing the quality of ASFV genomes. Furthermore, an increasing number of recombinant isolates of genotype I and II, have been observed, further complicating the task of phylogenetic analysis. To overcome these obstacles, we developed the ANASFV (analysis of an ASFV) pipeline. The pipeline is used to solve four tasks: In the first task, the pipeline introduces an amplicon sequencing approach that significantly improves genomic coverage, enabling reliable genome assembly. The pipeline also introduce reference-aided polishing techniques to correct small indels caused by nanopore sequencing errors. Moving on to the second task, a genome quality assessment system was established to evaluate the completeness and accuracy of the assembled genomes. For the third task, a method to rapidly analyze whether an isolate is a recombinant between genotype I and II, as well as to determine the pattern of recombination, based on gene similarity. Lastly, a comprehensive phylogenetic analysis based on coding sequences (CDS) was conducted, allowing us to generate a refined phylogenetic tree that includes all known ASFV genomes. The ANASFV pipeline will facilitate ASFV full genome sequencing using the nanopore platform. The pipeline will also support robust downstream bioinformatic analyses to assess genome integrity and conduct detailed phylogenetic studies based on whole-genome data.

genetics↗

bioRxiv2024

Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome

Intra-tumor heterogeneity is characterized by a diverse population of tumor clones and subclones which are important drivers of tumor evolution and therapeutic response. However, accurate subclonal reconstruction at scale remains challenging. We developed a machine learning tool, CliPP, and surveyed 9,972 tumors from 32 cancer types. We found that high subclonal mutation load (sML), the fraction of subclonal single nucleotide variants (SNVs) to all SNVs in the coding region, was prognostic of survival (progression free survival or overall survival) in 18 cancer types. In 14 cancers with low to moderate tumor mutation burden (TMB), high sML was associated with better prognosis. In immunotherapy trials for 42 metastatic prostate cancer (mCRPC), high sML was predictive of favorable response to ipilimumab and associated with increased CD8+ T-cell infiltration and decreased macrophage population. A validation using 613 whole-genomes of esophageal adenocarcinoma confirms the favorable effect of high sML and the observed tumor-associated macrophage. Our study identifies sML as a key feature of cancer, suggesting a biphasic relationship between evolutionary dynamics and differential immune environments. Finally, sML may serve as an orthogonal approach to identify likely responders of immune checkpoint blockade in low to moderate TMB tumors.

genomics↗

bioRxiv2024

Mesolimbic local field potentials are modulated by motor control

Background and ObjectivesWhile historically cortico-basal ganglia-thalamocortical loops were believed to process limbic and sensorimotor data in parallel, there is now evidence to suggest that the two information streams can be processed in a single open loop. However, the limbic-motor interface remains insufficiently characterized. We sought to further investigate how extrastriatal regions may regulate motor output by examining electrophysiological activity in these areas during a response inhibition paradigm. MethodsWe recorded local field potentials (LFPs) from epilepsy patients implanted with intracranial depth electrodes for seizure localization purposes. Participants performed the stop-signal task, during which they made speeded choice reactions to "go" stimuli and occasionally inhibited their reactions in the incident of a "stop" signal. To compare power during movement and the absence of movement, we applied a Wilcoxon signed-rank test. Additionally, we performed a linear mixed-effects model to relate power in limbic regions to power in the motor cortex. Finally, we implemented exploratory analyses to identify power differences for correct go versus correct stop trials and for correct stop versus incorrect stop trials using cluster-based permutation testing. Results14 patients participated. A comparison between movement and baseline fixation revealed that motor response is associated with reduced beta (15-35 Hz) power in the amygdala, hippocampus, and motor cortex and reduced gamma (35-100 Hz) power in the amygdala and hippocampus. Moreover, average beta and gamma power in the amygdala and hippocampus during motor execution were positively associated with average beta and gamma power in the motor cortex. Additionally, we identified significant differences between correct go and stop trials in delta (1-4 Hz) power for all three regions and in theta (4-8 Hz) power for the amygdala and motor cortex. Likewise, we identified significant differences between correct and incorrect stop trials in delta power for the hippocampus and motor cortex, in theta power for the motor cortex, in alpha (8-15 Hz) and beta power for the amygdala and motor cortex, and in gamma power for all three areas. DiscussionThese correlations between neural oscillations in the hippocampus and amygdala and movement strengthen the notion of mesolimbic modulation of motor activity.

neuroscience↗

bioRxiv2024

Realizing Mechanical Frustration at the Nanoscale Using DNA Origami

Structural designs inspired by physical and biological systems have been previously utilized to develop advanced mechanical metamaterials. These are based on the clever geometric arrangement of their building blocks, resulting in enhanced mechanical properties such as shape morphing and auxetic behavior. Until now, the benefits from such designs have yet to be leveraged at the nanoscale. Here, we use the DNA origami method to realize a nanoscale metastructure exhibiting mechanical frustration, the mechanical counterpart of the well-known phenomenon of magnetic frustration. We show that this DNA metastructure can be precisely controlled to adopt either frustrated or non-frustrated mechanical states, each characterized by a distinct free energy profile. Switching among the states is achieved by engineering reconfigurable struts into the structure. Actuation of the struts causes a global deformation of the metastructures. In the non-frustrated state, strain can be distributed homogeneously throughout the structure, while in the frustrated state, strain is concentrated at a specific location. Molecular dynamics simulations reconcile the contrasting behaviors of the two modes and provide detailed insights into the mechanics. Our work demonstrates how combining programmable DNA self-assembly with mechanical design principles can overcome engineering limitations encountered at the macroscale, enabling the development of dynamic, deformable nanostructures with tunable responses. These may lay the foundation for mechanical energy storage elements, nanomechanical computation, and allosteric mechanisms in DNA-based nanomachinery.

biophysics↗

bioRxiv2024

Inhibitor of cardiolipin biosynthesis-related enzyme MoGep4 confers broad-spectrum anti-fungal activity

Plant pathogens cause devastating diseases, leading to serious losses to agriculture. Mechanistic understanding of pathogenesis of plant pathogens lays the foundation for the development of fungicides for disease control. Mitophagy, a specific form of autophagy, is important for fungal virulence. The role of cardiolipin, mitochondrial signature phospholipid, in mitophagy and pathogenesis is largely unknown in plant pathogenic fungi. The functions of enzymes involved in cardiolipin biosynthesis and relevant inhibitors were assessed using a set of assays, including genetic deletion, plant infection, lipidomics, chemical-protein interaction, chemical inhibition, and field trials. Our results showed that the cardiolipin biosynthesis-related gene MoGEP4 of the rice blast fungus Magnaporthe oryzae regulates growth, conidiation, cardiolipin biosynthesis, and virulence. Mechanistically, MoGep4 regulated mitophagy and Mps1-MAPK phosphorylation, which are required for virulence. Chemical alexidine dihydrochloride (AXD) inhibited the enzyme activity of MoGep4, cardiolipin biosynthesis and mitophagy. Importantly, AXD efficiently inhibited the growth of 10 plant pathogens and controlled rice blast and Fusarium head blight in the field. Our study demonstrated that MoGep4 regulates mitophagy, Mps1 phosphorylation and pathogenesis in M. oryzae. In addition, we found that the MoGep4 inhibitor, AXD, displays broad-spectrum antifungal activity and is a promising candidate for fungicide development.

microbiology↗

bioRxiv2024

H2A.Z deposition at meiotic prophase I underlies homologous recombination and pachytene genome activation during male meiosis

Accurate meiotic progression is important for gamete formation and the generation of genetic diversity. However, little is known about the identity of chromatin regulators that underlie mammalian meiosis in vivo. Here, we identify the multifaceted functions of the chromatin remodeler ZNHIT1 in governing meiosis. The expression of Znhit1 gradually increases during the meiotic prophase, and Znhit1 knockout in spermatocytes results in arrested pachytene development, impaired DNA double-strand break repair, and defective homologous recombination. Single-cell RNA sequencing and transcriptome analysis reveal that Znhit1 loss dysregulates meiotic transcriptional programs at the pachytene stage. Chromatin immunoprecipitation data show that ZNHIT1 is needed for the incorporation of the histone variant H2A.Z into pachytene chromatin. Moreover, we found that H2A.Z cooperates with the transcription factor A-MYB to co-bind DNA elements and control gene activity. Our findings provide insights into the regulatory mechanisms governing meiotic progression and highlight ZNHIT1 as a critical regulator of meiotic progression.

developmental biology↗

bioRxiv2024

Differential prevalence and risk factors for infection with coronaviruses in bats collected during 2020 in Yunnan Province, China

Coronaviruses (CoVs) pose a threat to human health globally, as highlighted by severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the COVID-19 pandemic. Bats from the Greater Mekong Subregion (GMS) are an important natural reservoir for CoVs. Here we report the differential prevalence of CoVs in bats across biological and ecological factors within Yunnan Province. We also show the coexistence of CoVs in individual bats and identify an additional putative host for SARS-related CoV, with higher dispersal capacity than other known hosts. Notably, 11 SARS-related coronaviruses (SARSr-CoVs) were discovered in horseshoe bats and a Chinese water myotis bat by pan-CoV detection and Illumina sequencing. Our findings facilitate an understanding of the fundamental features of the distribution and circulation of CoVs in nature as well as zoonotic spillover risk in the One health framework.

microbiology↗

bioRxiv2024

Tonotopy is not preserved in a descending stage of auditory cortex

Previous studies based on layer specificity suggest that ascending signals from the thalamus to the sensory neocortex preserve spatially organized information, but it remains unknown whether sensory information descending from sensory neocortex to the thalamus also maintains such spatial organization pattern. By focusing on projection specificity, we mapped the tone response properties of two groups of cortical neurons in the primary auditory cortex (A1), based on the relationship between their specific connections to other regions and their function in ascending (thalamocortical recipient, TR neurons) or descending (corticothalamic, CT neurons) auditory information. A clear tonotopic gradient was observed among TR neurons, but not CT neurons. Additionally, CT neurons exhibited markedly higher heterogeneity in their frequency tuning and had broader bandwidth than TR neurons. These results reveal that the information flow descending from A1 to the thalamus via CT neurons is not arrange tonotopically, suggesting that the descending information flow possibly contributes to higher-order feedback processing of diverse auditory inputs.

neuroscience↗

bioRxiv2024

Rational design of HER2-targeted combination therapies to reverse drug resistance in fibroblast-protected HER2+ breast cancer cells.

IntroductionFibroblasts, an abundant cell type in the breast tumor microenvironment, interact with cancer cells and orchestrate tumor progression and drug resistance. However, the mechanisms by which fibroblast-derived factors impact drug sensitivity remain poorly understood. Here, we develop rational combination therapies that are informed by proteomic profiling to overcome fibroblast-mediated therapeutic resistance in HER2+ breast cancer cells. MethodsDrug sensitivity to the HER2 kinase inhibitor lapatinib was characterized under conditions of monoculture and exposure to breast fibroblast-conditioned medium. Protein expression was measured using reverse phase protein arrays. Candidate targets for combination therapy were identified using differential expression and multivariate regression modeling. Follow-up experiments were performed to evaluate the effects of HER2 kinase combination therapies in fibroblast-protected cancer cell lines and fibroblasts. ResultsCompared to monoculture, fibroblast-conditioned medium increased the expression of plasminogen activator inhibitor-1 (PAI1) and cell cycle regulator polo like kinase 1 (PLK1) in lapatinib-treated breast cancer cells. Combination therapy of lapatinib with inhibitors targeting either PAI1 or PLK1, eliminated fibroblast-protected cancer cells, under both conditions of direct coculture with fibroblasts and protection by fibroblast-conditioned medium. Analysis of publicly available, clinical transcriptomic datasets revealed that HER2-targeted therapy fails to suppress PLK1 expression in stroma-rich HER2+ breast tumors and that high PAI1 gene expression associates with high stroma density. Furthermore, we showed that an epigenetics-directed approach using a bromodomain and extraterminal inhibitor to globally target fibroblast-induced proteomic adaptions in cancer cells, also restored lapatinib sensitivity. ConclusionsOur data-driven framework of proteomic profiling in breast cancer cells identified the proteolytic degradation regulator PAI1 and the cell cycle regulator PLK1 as predictors of fibroblast-mediated treatment resistance. Combination therapies targeting HER2 kinase and these fibroblast-induced signaling adaptations eliminates fibroblast-protected HER2+ breast cancer cells.

bioengineering↗

bioRxiv2024

Expanding the Triangle of U: The genome assembly of Hirschfeldia incana provides insights into chromosomal evolution, phylogenomics and high photosynthesis-related traits

The Brassiceae tribe encompasses many economically important crops and exhibits high intraspecific and interspecific phenotypic variation. After a shared whole-genome triplication (WGT) event (Br-, [~]15.9 million years ago), different lineages and species underwent differential chromosomal rearrangements (diploidization) leading to diverse patterns of gene retention and loss (fractionation). Lineage diversification and genomic changes contributed to an array of divergence in morphology, biochemistry, and physiology underlying photosynthesis-related traits. The C3 species Hirschfeldia incana is studied as it displays high photosynthetic rates under high-light conditions. We present an improved chromosome-level genome assembly for H. incana (Nijmegen, v2.0) using nanopore and chromosome conformation capture (Hi-C) technologies, with 409Mb in size and an N50 of 52Mb (a 10x improvement over the previously published scaffold-level v1.0 assembly). The updated assembly and annotation allowed to investigate the WGT history of H. incana in a comparative phylogenomic framework from the Brassiceae ancestral genomic blocks and related diploidized crops. Hirschfeldia incana (x=7) shares extensive genome collinearity with Raphanus sativus (x=9). These two species share some commonalities with Brassica rapa and B. oleracea (A genome, x=10 and C genome, x=9, respectively) and other similarities with B. nigra (B genome, x=8). Phylogenetic analysis revealed that H. incana and R. sativus form a monophyletic clade in between the Brassica A/C and B genomes. We postulate that H. incana and R. sativus genomes are results of reciprocal hybridization combinations of the Brassica A/C and B genome types. Our results might explain the discrepancy observed in published studies regarding phylogenetic placement of H. incana and R. sativus in relation to the "Triangle of U" species. Expression analysis of WGT retained gene copies revealed sub-genome expression divergence, likely due to neo- or sub-functionalization. Finally, we highlighted genes associated with physio-biochemical-anatomical adaptive changes observed in H. incana which likely facilitate its high-photosynthesis traits under high light.

plant biology↗

bioRxiv2024

Giraffe: a tool for comprehensive processing andvisualization of multiple long-read sequencing data

Third-generation sequencing techniques have become increasingly popular due to their ability to generate long, high-quality reads. Utilizing datasets from various samples and multiple sequencing platforms for comparative and comprehensive analysis is essential for exploring biological mechanisms and establishing benchmark baselines. However, current tools for long reads primarily focus on quality control (QC) and read processing for individual samples, complicating the profiling and comparison of multiple datasets. The lack of tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. Furthermore, developing a comprehensive long-read QC method that facilitates comparative analysis and visualization across multiple samples and platforms is necessary to establish benchmark baselines for selecting appropriate sequencing platforms. We introduce Giraffe, a Python3-based command line tool designed for comparative analysis and visualization across multiple samples and platforms. Giraffe enables the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its usability has been demonstrated in various scenarios, including comparisons of different biological processing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology vs. Pacific Biosciences), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows). Additionally, our findings indicate that Oxford Nanopore duplex reads outperform PacBio HiFi reads in homopolymer identification and GC evenness while maintaining comparable overall read quality.

bioinformatics↗

bioRxiv2024

Natural selection and evolution of mitochondrial genome in terrestrial and aquatic turbellarians

Mitochondrial energy metabolism may be directly influenced by natural selection pressures in response to the energy demands of an organisms specific ecological niche. Here, we hypothesized that the mitochondrial genome of turbellarian animals was influenced by the metabolic requirements of various habitats We used selection pressure and phylogenetic independent contrasts (PIC) analyses to detect the selection pressure of protein-coding genes in the mitochondrial genome of turbellarian living in aquatic and terrestrial habitats. The results indicated turbellarians in aquatic habitats experienced greater selection pressure, resulting in the evolution of several genes at a lower {omega} value compared to their terrestrial counterparts. The NAD4 was identified as having positive selection sites in all site models analyzed. Among all genes, the equilibrium constant (ionization of COOH) was the most frequently detected amino acid characteristic with significant positive selection changes, followed by hydropathy and molecular volume. The equilibrium constant (ionization of COOH) was found to be the amino acid characteristic with the greatest magnitude of change in NAD4. This suggests that it plays a crucial role in the adaptive evolution of turbellarians to varying habitats. The study found a significant positive correlation (R = 0.61, p < 0.05) between the {omega} value of turbellarian and their habitats by PIC analysis. These findings shed light on the adaptive evolution of turbellarian mtDNAs and their influence on the oxidative phosphorylation molecular mechanism. 0. Significance statementThe adaptive evolution of mitochondrial genes is closely related to environmental temperature, high energy metabolism demand, altitude, and oxygen availability. Mitochondrial energy metabolism may be directly influenced by natural selection pressures in response to the energy demands of an organisms specific ecological niche. Here, we investigated the evolution of mtDNA PCGs in turbellarians across different habitats, and identified purifying selection as the main evolutionary pattern of the turbellarian mitochondrial genome. Additionally, we found that NAD4 played an important role in the adaptive evolution of turbellarians to different habitats.

evolutionary biology↗

bioRxiv2024

Targeting of SUMOylation leads to cBAF complex stabilization and disruption of the SS18::SSX transcriptome in Synovial Sarcoma

Synovial Sarcoma (SS) is driven by the SS18::SSX fusion oncoprotein. and is ultimately refractory to therapeutic approaches. SS18::SSX alters ATP-dependent chromatin remodeling BAF (mammalian SWI/SNF) complexes, leading to the degradation of canonical (cBAF) complex and amplified presence of an SS18::SSX-containing non-canonical BAF (ncBAF or GBAF) that drives an SS-specific transcription program and tumorigenesis. We demonstrate that SS18::SSX activates the SUMOylation program and SSs are sensitive to the small molecule SAE1/2 inhibitor, TAK-981. Mechanistically, TAK-981 de-SUMOylates the cBAF subunit SMARCE1, stabilizing and restoring cBAF on chromatin, shifting away from SS18::SSX-ncBAF-driven transcription, associated with DNA damage and cell death and resulting in tumor inhibition across both human and mouse SS tumor models. TAK-981 synergized with cytotoxic chemotherapy through increased DNA damage, leading to tumor regression. Targeting the SUMOylation pathway in SS restores cBAF complexes and blocks the SS18::SSX-ncBAF transcriptome, identifying a therapeutic vulnerability in SS, positioning the in-clinic TAK-981 to treat SS.

cancer biology↗

bioRxiv2024

Reward Circuit Local Field Potential Modulations Precede Risk Taking

Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking. Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient. Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex (p=0.0022), high-gamma in the anterior cingulate (p=0.0004), and high-gamma in the insula (p=0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power (p=2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex (p=2.0E-4), broad frequencies in amygdala (p=2.0E-4), and theta to low-gamma in insula (p=4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal (p=0.0048) and with patient impulsivity (p=0.00478). Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.

neuroscience↗

bioRxiv2024

Single-cell imaging of the lytic phage life cycle dissects the timing and noise in individual infection steps

When a lytic bacteriophage infects a bacterial cell, it commandeers the cells resources to replicate, ultimately causing cell lysis and the release of new virions. As phages function as obligate parasites, each stage of the infection process depends on the physiological parameters of the host cell. Given the inherent physiological variability within a population of genetically identical bacterial cells, we ask how the phage infection dynamic reflects such heterogeneity. Here, we introduce a timelapse imaging assay for investigating the dynamics of individual infection steps by a single T7 phage on a single bacterium. This high-throughput, time-resolved assay enables us to monitor the infection progression simultaneously in multiple cells, uncovering substantial heterogeneity at each step and revealing correlations between infection dynamics and the physiological state of the infected cell. Simulations of competing phage populations with different lysis time distributions reveal that heterogeneity in infection dynamics can significantly impact phage fitness, highlighting it as a potential evolutionary driver of phage-bacteria interactions.

microbiology↗