Limb proportions show developmental plasticity in response to embryo movement

Probing the glioma micro-environment: analysis using biopsy in combination with ultra-fast cyclic immunolabeling

The interaction between gliomas and the immune system is poorly understood and thus hindering development of effective immunotherapies for glioma patients. The immune response is highly variable during tumor development, and affected by therapies such as surgery, radiation, and chemotherapy. Currently, analysis of these local changes is difficult due to poor accessibility of the tumor and high-morbidity of sampling. In this study, we developed a model for repeat-biopsy in mice to study these local immunological changes over time. Using fine needle biopsy we were able to safely and repeatedly collect cells from intracranial tumors in mice. Ultra-fast cycling technology (FAST) was used for multi-cycle immunofluorescence of retrieved cells, and provided insights in the changing immune response over time. The combination of these techniques can be utilized to study changes in the immune response in glioma or other intracranial diseases over time, and in response to treatment within the same animal.

Teaser

Fine-needle biopsy and ultra-fast cycling technology techniques were developed to allow for repeat sampling and analysis of glial tumors in mice.

Towards a standard benchmark for variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework

Background

Computational approaches to support rare disease diagnosis are challenging to build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species data into variant and gene prioritisation algorithms (VGPAs). However, the performance of VGPAs has been difficult to measure and is impacted by many factors, for example, ontology structure, annotation completeness or changes to the underlying algorithm. Assertions of the capabilities of VGPAs are often not reproducible, in part because there is no standardised, empirical framework and openly available patient data to assess the efficacy of VGPAs - ultimately hindering the development of effective prioritisation tools.

Results

In this paper, we present our benchmarking tool, PhEval, which aims to provide a standardised and empirical framework to evaluate phenotype-driven VGPAs. The inclusion of standardised test corpora and test corpus generation tools in the PhEval suite of tools allows open benchmarking and comparison of methods on standardised data sets.

Conclusions

PhEval and the standardised test corpora solve the issues of patient data availability and experimental tooling configuration when benchmarking and comparing rare disease VGPAs. By providing standardised data on patient cohorts from real-world case-reports and controlling the configuration of evaluated VGPAs, PhEval enables transparent, portable, comparable and reproducible benchmarking of VGPAs. As these tools are often a key component of many rare disease diagnostic pipelines, a thorough and standardised method of assessment is essential for improving patient diagnosis and care.

Regeneration-specific promoter switching facilitates Mest expression in the mouse digit tip to modulate neutrophil response

The mouse digit tip regenerates following amputation, a process mediated by a cellularly heterogeneous blastema. We previously found the gene Mest to be highly expressed in mesenchymal cells of the blastema and a strong candidate pro-regenerative gene. We now show Mest digit expression is regeneration-specific and not upregulated in post-amputation fibrosing proximal digits. Mest homozygous knockout mice exhibit delayed bone regeneration though no phenotype is found in paternal knockout mice, inconsistent with the defined maternal genomic imprinting of Mest. We demonstrate that promoter switching, not loss of imprinting, regulates biallelic Mest expression in the blastema and does not occur during embryogenesis, indicating a regeneration-specific mechanism. Requirement for Mest expression is tied to modulating neutrophil response, as revealed by scRNAseq and FACS comparing wildtype and knockout blastemas. Collectively, the imprinted gene Mest is required for proper digit tip regeneration and its blastema expression is facilitated by promoter switching for biallelic expression.

The Capicua C1 Domain is Required for Full Activity of the CIC::DUX4 Fusion Oncoprotein

Rearrangements between genes can yield neomorphic fusions that drive oncogenesis. Fusion oncogenes are made up of fractional segments of the partner genes that comprise them, with each partner potentially contributing some of its own function to the nascent fusion oncoprotein. Clinically, fusion oncoproteins driving one diagnostic entity are typically clustered into a single molecular subset and are often treated a similar fashion. However, knowledge of where specific fusion breakpoints occur in partner genes, and the resulting retention of functional domains in the fusion, is an important determinant of fusion oncoprotein activity and may differ between patients. This study investigates this phenomena through the example of CIC::DUX4, a fusion between the transcriptional repressor capicua (CIC) and the double homeobox 4 gene (DUX4), which drives an aggressive subset of undifferentiated round cell sarcoma. Using a harmonized dataset of over 100 patient fusion breakpoints from the literature, we show that most bona fide CIC::DUX4 fusions retain the C1 domain, which is known to contribute to DNA binding by wild type CIC. Mechanistically, deletion or mutation of the C1 domain reduces, but does not eliminate, activation of CIC target genes by CIC::DUX4. We also find that expression of C1-deleted CIC::DUX4 is capable of exerting intermediate transformation-related phenotypes compared with those imparted by full-length CIC::DUX4, but was not sufficient for tumorigenesis in a subcutaneous mouse model. In summary, our results suggest a supercharging role for the C1 domain in the activity of CIC::DUX4.

Transfer learning predicts species-specific drug interactions in emerging pathogens

Machine learning (ML) algorithms are necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However, existing ML approaches cannot be applied to emerging and under-studied pathogens with limited training data. To address this, we developed a transfer learning and crowdsourcing framework (TACTIC) to train ML models on data from multiple bacteria. TACTIC was built using 2,965 drug interactions from 12 bacterial strains and outperformed traditional ML models in predicting drug interaction outcomes for species that lack training data. Top TACTIC model features revealed genetic and metabolic factors that influence cross-species and species-specific drug interaction outcomes. Upon analyzing ~600,000 predicted drug interactions across 9 metabolic environments and 18 bacterial strains, we identified a small set of drug interactions that are selectively synergistic against Gram-negative (e.g., A. baumannii) and non-tuberculous mycobacteria (NTM) pathogens. We experimentally validated synergistic drug combinations containing clarithromycin, ampicillin, and mecillinam against M. abscessus, an emerging pathogen with growing levels of antibiotic resistance. Lastly, we leveraged TACTIC to propose selectively synergistic drug combinations to treat bacterial eye infections (endophthalmitis).

Piximi - An Images to Discovery web tool for bioimages and beyond

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

Automated classification of cellular expression in multiplexed imaging data with Nimbus

Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use at https://github.com/angelolab/Nimbus-Inference.

Capillary interactions drive the self-organization of bacterial colonies

Many bacteria inhabit thin layers of water on solid surfaces both naturally in soils or on hosts or textiles and in the lab on agar hydrogels. In these environments, cells experience capillary forces, yet an understanding of how these forces shape bacterial collective behaviors remains elusive. Here, we show that the water menisci formed around bacteria lead to capillary attraction between cells while still allowing them to slide past one another. We develop an experimental apparatus that allows us to control bacterial collective behaviors by varying the strength and range of capillary forces. Combining 3D imaging and cell tracking with agent-based modeling, we demonstrate that capillary attraction organizes rod-shaped bacteria into densely packed, nematic groups, and profoundly influences their collective dynamics and morphologies. Our results suggest that capillary forces may be a ubiquitous physical ingredient in shaping microbial communities in partially hydrated environments.

A non-adaptationist hypothesis of play behaviour

Play is a suite of apparently non-functional, pleasurable behaviours observed in human and non-human animals. Although the phenomenon has been studied extensively, no adaptationist behavioural theory of how play evolved can be supported by the available evidence. However, the advancement of the extended evolutionary synthesis and developments in systems biology offer alternative avenues for non-adaptationist physiological hypotheses. I therefore propose a hypothesis of play, based upon a complex ACh activity that is under agential control of the organism, whereby play initiates ACh-mediated feedforward and feedback processes which act to: (i) regulate metabolic processes; (ii) form new ACh receptors via ACh mRNA activity; (iii) mediate attention, memory consolidation and learning; and (iv) mediate social behaviours, reproduction and embryonic development. However, play occurs across taxa, but does not occur across all taxonomic groups or within all species of a taxonomic group. Thus, to support the validity of the proposed hypothesis, I further propose potential explanations for this anomaly, which include sampling and observer biases, altricial versus precocial juvenile development, and the influence of habitat niche and environmental conditions on behaviour. The proposed hypothesis thus offers new avenues for study in both the biological and social sciences, in addition to having potential applications in applied sciences, such as animal welfare and biomedical research. Crucially, it is hoped that this hypothesis will promote further study of a valid and behaviourally significant, yet currently enigmatic, biological phenomenon.

Decoding the Best Automated Segmentation Tools for Vascular White Matter Hyperintensities in the Aging Brain: A Clinician's Guide to Precision and Purpose

Cerebrovascular damage from small vessel disease (SVD) occurs in healthy and pathological aging. SVD markers, such as white matter hyperintensities (WMH), are commonly found in individuals over 60 and increase in prevalence with age. WMHs are detectable on standard MRI by adhering to the STRIVE criteria. Currently, visual assessment scales are used in clinical and research scenarios but is time-consuming and has rater variability, limiting its practicality. Addressing this issue, our study aimed to determine the most precise WMH segmentation software, offering insights into methodology and usability to balance clinical precision with practical application. This study employed a dataset comprising T1, FLAIR, and DWI images from 300 cognitively healthy older adults. WMHs in this cohort were evaluated using four automated neuroimaging tools: Lesion Prediction Algorithm (LPA) and Lesion Growth Algorithm (LGA) from Lesion Segmentation Tool (LST), Sequence Adaptive Multimodal Segmentation (SAMSEG), and Brain Intensity Abnormalities Classification Algorithm (BIANCA). Additionally, clinicians manually segmented WMHs in a subsample of 45 participants to establish a gold standard. The study assessed correlations with the Fazekas scale, algorithm performance, and the influence of WMH volume on reliability. Results indicated that supervised algorithms were superior, particularly in detecting small WMHs, and can improve their consistency when used in parallel with unsupervised tools. The research also proposed a biomarker for moderate vascular damage, derived from the top 95th percentile of WMH volume in healthy individuals aged 50 to 60. This biomarker effectively differentiated subgroups within the cohort, correlating with variations in brain structure and behavior.

The killifish germline regulates longevity and somatic repair in a sex-specific manner

Classical evolutionary theories propose tradeoffs between reproduction, damage repair, and lifespan. However, the specific role of the germline in shaping vertebrate aging remains largely unknown. Here, we use the turquoise killifish ( N. furzeri ) to genetically arrest germline development at discrete stages, and examine how different modes of infertility impact life-history. We first construct a comprehensive single-cell gonadal atlas, providing cell-type-specific markers for downstream phenotypic analysis. Next, we show that germline depletion - but not arresting germline differentiation - enhances damage repair in female killifish. Conversely, germline-depleted males instead showed an extension in lifespan and rejuvenated metabolic functions. Through further transcriptomic analysis, we highlight enrichment of pro-longevity pathways and genes in germline-depleted male killifish and demonstrate functional conservation of how these factors may regulate longevity in germline-depleted C. elegans . Our results therefore demonstrate that different germline manipulation paradigms can yield pronounced sexually dimorphic phenotypes, implying alternative responses to classical evolutionary tradeoffs.

Chondrocyte hypertrophy in the growth plate promotes stress anisotropy affecting long bone development through chondrocyte column formation

The length of long bones is determined by column formation of proliferative chondrocytes and subsequent chondrocyte hypertrophy in the growth plate during bone development. Despite the importance of mechanical loading in long bone development, the mechanical conditions of the cells within the growth plate, such as the stress field, remain unclear owing to the difficulty in investigating spatiotemporal changes within dynamically growing tissues. In this study, the mechanisms of longitudinal bone growth were investigated from a mechanical perspective through column formation of proliferative chondrocytes within the growth plate before secondary ossification center formation using continuum-based particle models (CbPMs). A one-factor model, which simply describes essential aspects of a biological signaling cascade regulating cell activities within the growth plate, was developed and incorporated into CbPM. Subsequently, the developmental process and maintenance of the growth plate structure and resulting bone morphogenesis were simulated. Thus, stress anisotropy in the proliferative zone that affects bone elongation through chondrocyte column formation was identified and found to be promoted by chondrocyte hypertrophy. These results provide further insights into the mechanical regulation of multicellular dynamics during bone development.

Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration

In neurological conditions affecting the brain, early-stage neural circuit adaption is key for long-term preservation of normal behaviour. We tested if motoneurons and respective microcircuits also adapt in the initial stages of disease progression in a mouse model of progressive motoneuron degeneration. Using a combination of in vitro and in vivo electrophysiology and super-resolution microscopy, we found that, preceding muscle denervation and motoneuron death, recurrent inhibition mediated by Renshaw cells is reduced in half due to impaired quantal size associated with decreased glycine receptor density. Additionally, higher probability of release from proprioceptive Ia terminals leads to increased monosynaptic excitation to motoneurons. Surprisingly, the initial impairment in recurrent inhibition is not a widespread feature of inhibitory spinal circuits, such as group I inhibitory afferents, and is compensated at later stages of disease progression. We reveal that in disease conditions, spinal microcircuits undergo specific multiphasic homeostatic compensations to preserve force output.

Threat Expectation Does Not Improve Perceptual Discrimination despite Causing Heightened Priority Processing in the Frontoparietal Network

Threat cues have been widely shown to elicit increased sensory and attentional neural processing. However, whether this enhanced recruitment leads to measurable behavioral improvements in perception is still in question. Here, we adjudicate between two opposing theories: that threat cues do or do not enhance perceptual sensitivity. We created threat stimuli by pairing one direction of motion in a random dot kinematogram with an aversive sound. While in the MRI scanner, 46 subjects (both men and women) completed a cued (threat/safe/neutral) perceptual decision-making task where they indicated the perceived motion direction of each moving dot stimulus. We found strong evidence that threat cues did not increase perceptual sensitivity compared with safe and neutral cues. This lack of improvement in perceptual decision-making ability occurred despite the threat cue resulting in widespread increases in frontoparietal BOLD activity, as well as increased connectivity between the right insula and the frontoparietal network. These results call into question the intuitive claim that expectation automatically enhances our perception of threat and highlight the role of the frontoparietal network in prioritizing the processing of threat-related environmental cues.

From the Inside Out: Exposing the Roles of Urea Cycle Enzymes in Tumors and Their Micro and Macro Environments

Catabolic pathways change in anabolic diseases such as cancer to maintain metabolic homeostasis. The liver urea cycle (UC) is the main catabolic pathway for disposing excess nitrogen. Outside the liver, the UC enzymes are differentially expressed based on each tissue's needs for UC intermediates. In tumors, there are changes in the expression of UC enzymes selected for promoting tumorigenesis by increasing the availability of essential UC substrates and products. Consequently, there are compensatory changes in the expression of UC enzymes in the cells that compose the tumor microenvironment. Moreover, extrahepatic tumors induce changes in the expression of the liver UC, which contribute to the systemic manifestations of cancer, such as weight loss. Here, we review the multilayer changes in the expression of UC enzymes throughout carcinogenesis. Understanding the changes in UC expression in the tumor and its micro and macro environment can help identify biomarkers for early cancer diagnosis and vulnerabilities that can be targeted for therapy.

Climate change and its effects on body size and shape: the role of endocrine mechanisms

In many organisms, rapidly changing environmental conditions are inducing dramatic shifts in diverse phenotypic traits with consequences for fitness and population viability. However, the mechanisms that underlie these responses remain poorly understood. Endocrine signalling systems often influence suites of traits and are sensitive to changes in environmental conditions; they are thus ideal candidates for uncovering both plastic and evolved consequences of climate change. Here, we use body size and shape, a set of integrated traits predicted to shift in response to rising temperatures with effects on fitness, and insulin-like growth factor-1 as a case study to explore these ideas. We review what is known about changes in body size and shape in response to rising temperatures and then illustrate why endocrine signalling systems are likely to be critical in mediating these effects. Lastly, we discuss research approaches that will advance understanding of the processes that underlie rapid responses to climate change and the role endocrine systems will have. Knowledge of the mechanisms involved in phenotypic responses to climate change will be essential for predicting both the ecological and the long-term evolutionary consequences of a warming climate. This article is part of the theme issue 'Endocrine responses to environmental variation: conceptual approaches and recent developments'.

The L-lactate dehydrogenases of Pseudomonas aeruginosa are conditionally regulated but both contribute to survival during macrophage infection

Pseudomonas aeruginosa is an opportunistic pathogen that thrives in environments associated with human activity, including soil and water altered by agriculture or pollution. Because L-lactate is a significant product of plant and animal metabolism, it is available to serve as a carbon source for P. aeruginosa in the diverse settings it inhabits. Here, we evaluate P. aeruginosa's production and use of its redundant L-lactate dehydrogenases, termed LldD and LldA. We confirm that the protein LldR represses lldD and identify a new transcription factor, called LldS, that activates lldA; these distinct regulators and the genomic contexts of lldD and lldA contribute to their differential expression. We demonstrate that the lldD and lldA genes are conditionally controlled in response to lactate isomers as well as to glycolate and - hydroxybutyrate, which, like lactate, are -hydroxycarboxylates. We also show that lldA is induced when iron availability is low. Our examination of lldD and lldA expression across depth in biofilms indicates a complex pattern that is consistent with the effects of glycolate production, iron availability, and cross-regulation on enzyme preference. Finally, macrophage infection assays revealed that both lldD and lldA contribute to persistence within host cells, underscoring the potential role of L-lactate as a carbon source during P. aeruginosa-eukaryote interactions. Together, these findings help us understand the metabolism of a key resource that may promote P. aeruginosa's success as a resident of contaminated environments and animal hosts.

Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures

Deep learning methods are increasingly being applied to raw electroencephalogram (EEG) data. However, if these models are to be used in clinical or research contexts, methods to explain them must be developed, and if these models are to be used in research contexts, methods for combining explanations across large numbers of models must be developed to counteract the inherent randomness of existing training approaches. Model visualization-based explainability methods for EEG involve structuring a model architecture such that its extracted features can be characterized and have the potential to offer highly useful insights into the patterns that they uncover. Nevertheless, model visualization-based explainability methods have been underexplored within the context of multichannel EEG, and methods to combine their explanations across folds have not yet been developed. In this study, we present two novel convolutional neural network-based architectures and apply them for automated major depressive disorder diagnosis. Our models obtain slightly lower classification performance than a baseline architecture. However, across 50 training folds, they find that individuals with MDD exhibit higher β power, potentially higher δ power, and higher brain-wide correlation that is most strongly represented within the right hemisphere. This study provides multiple key insights into MDD and represents a significant step forward for the domain of explainable deep learning applied to raw EEG. We hope that it will inspire future efforts that will eventually enable the development of explainable EEG deep learning models that can contribute both to clinical care and novel medical research discoveries.

MOB rules: Antibiotic Exposure Reprograms Metabolism to Mobilize Bacillus subtilis in Competitive Interactions

Antibiotics have dose-dependent effects on exposed bacteria. The medicinal use of antibiotics relies on their growth-inhibitory activities at sufficient concentrations. At subinhibitory concentrations, exposure effects vary widely among different antibiotics and bacteria. Bacillus subtilis responds to bacteriostatic translation inhibitors by mobilizing a population of cells (MOB-Mobilized Bacillus) to spread across a surface. How B. subtilis regulates the antibiotic-induced mobilization is not known. In this study, we used chloramphenicol to identify regulatory functions that B. subtilis requires to coordinate cell mobilization following subinhibitory exposure. We measured changes in gene expression and metabolism and mapped the results to a network of regulatory proteins that direct the mobile response. Our data reveal that several transcriptional regulators coordinately control the reprogramming of metabolism to support mobilization. The network regulates changes in glycolysis, nucleotide metabolism, and amino acid metabolism that are signature features of the mobilized population. Among the hundreds of genes with changing expression, we identified two, pdhA and pucA, where the magnitudes of their changes in expression, and in the abundance of associated metabolites, reveal hallmark metabolic features of the mobilized population. Using reporters of pdhA and pucA expression, we visualized the separation of major branches of metabolism in different regions of the mobilized population. Our results reveal a regulated response to chloramphenicol exposure that enables a population of bacteria in different metabolic states to mount a coordinated mobile response.

Electrical Impedance Spectroscopy Quantifies Skin Barrier Function in Organotypic In Vitro Epidermis Models

3 D human epidermal equivalents (HEEs) are a state-of-the-art organotypic culture model in pre-clinical investigative dermatology and regulatory toxicology. Here, we investigated the utility of electrical impedance spectroscopy (EIS) for non-invasive measurement of HEE epidermal barrier function. Our setup comprised a custom-made lid fit with 12 electrode pairs aligned on the standard 24-transwell cell culture system. Serial EIS measurements for seven consecutive days did not impact epidermal morphology and readouts showed comparable trends to HEEs measured only once. We determined two frequency ranges in the resulting impedance spectra: a lower frequency range termed EISdiff correlated with keratinocyte terminal differentiation independent of epidermal thickness and a higher frequency range termed EISSC correlated with stratum corneum thickness. HEEs generated from CRISPR/Cas9 engineered keratinocytes that lack key differentiation genes FLG, TFAP2A, AHR or CLDN1 confirmed that keratinocyte terminal differentiation is the major parameter defining EISdiff. Exposure to pro-inflammatory psoriasis- or atopic dermatitis-associated cytokine cocktails lowered the expression of keratinocyte differentiation markers and reduced EISdiff. This cytokine-associated decrease in EISdiff was normalized after stimulation with therapeutic molecules. In conclusion, EIS provides a non-invasive system to consecutively and quantitatively assess HEE barrier function and to sensitively and objectively measure barrier development, defects and repair.

Multiple paralogues and recombination mechanisms drive the high incidence of 22q11.2 Deletion Syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is the most common microdeletion disorder. Why the incidence of 22q11.2DS is much greater than that of other genomic disorders remains unknown. Short read sequencing cannot resolve the complex segmental duplicon structure to provide direct confirmation of the hypothesis that the rearrangements are caused by non-allelic homologous recombination between the low copy repeats on chromosome 22 (LCR22s). To enable haplotype-specific assembly and rearrangement mapping in LCR22 regions, we combined fiber-FISH optical mapping with whole genome (ultra-)long read sequencing or rearrangement-specific long-range PCR on 24 duos (22q11.2DS patient and parent-of-origin) comprising several different LCR22-mediated rearrangements. Unexpectedly, we demonstrate that not only different paralogous segmental duplicon but also palindromic AT-rich repeats (PATRR) are driving 22q11.2 rearrangements. In addition, we show the existence of two different inversion polymorphisms preceding rearrangement, and somatic mosaicism. The existence of different recombination sites and mechanisms in paralogues and PATRRs which are copy number expanding in the human population are a likely explanation for the high 22q11.2DS incidence.

Inhibition of Acyl-CoA Synthetase Long Chain Isozymes Decreases Multiple Myeloma Cell Proliferation and Causes Mitochondrial Dysfunction

Multiple myeloma (MM) is an incurable cancer of plasma cells with a 5-year survival rate of 59%. Dysregulation of fatty acid (FA) metabolism is associated with MM development and progression; however, the underlying mechanisms remain unclear. Acyl-CoA synthetase long-chain family members (ACSLs) convert free long-chain fatty acids into fatty acyl-CoA esters and play key roles in catabolic and anabolic fatty acid metabolism. The Cancer Dependency Map data suggested that ACSL3 and ACSL4 were among the top 25% Hallmark Fatty Acid Metabolism genes that support MM fitness. Here, we show that inhibition of ACSLs in human myeloma cell lines using the pharmacological inhibitor Triascin C (TriC) causes apoptosis and decreases proliferation in a dose- and time-dependent manner. RNA-seq of MM.1S cells treated with TriC for 24 h showed a significant enrichment in apoptosis, ferroptosis, and ER stress. Proteomics of MM.1S cells treated with TriC for 48 h revealed that mitochondrial dysfunction and oxidative phosphorylation were significantly enriched pathways of interest, consistent with our observations of decreased mitochondrial membrane potential and increased mitochondrial superoxide levels. Interestingly, MM.1S cells treated with TriC for 24 h also showed decreased mitochondrial ATP production rates and overall lower cellular respiration.

Integrative Co-Registration of Elemental Imaging and Histopathology for Enhanced Spatial Multimodal Analysis of Tissue Sections through TRACE

Summary

Elemental imaging provides detailed profiling of metal bioaccumulation, offering more precision than bulk analysis by targeting specific tissue areas. However, accurately identifying comparable tissue regions from elemental maps is challenging, requiring the integration of hematoxylin and eosin (H&E) slides for effective comparison. Facilitating the streamlined co-registration of Whole Slide Images (WSI) and elemental maps, TRACE enhances the analysis of tissue regions and elemental abundance in various pathological conditions. Through an interactive containerized web application, TRACE features real-time annotation editing, advanced statistical tools, and data export, supporting comprehensive spatial analysis. Notably, it allows for comparison of elemental abundances across annotated tissue structures and enables integration with other spatial data types through WSI co-registration.

Availability and Implementation

Available on the following platforms- GitHub: jlevy44/trace_app , PyPI: trace_app , Docker: joshualevy44/trace_app , Singularity: joshualevy44/trace_app .

Contact

joshua.levy@cshs.org.

Supplementary information

Supplementary data are available.

Deep segmentation of OCTA for evaluation and association of changes of retinal microvasculature with Alzheimer's disease and mild cognitive impairment

BACKGROUND

Optical coherence tomography angiography (OCTA) enables fast and non-invasive high-resolution imaging of retinal microvasculature and is suggested as a potential tool in the early detection of retinal microvascular changes in Alzheimer's Disease (AD). We developed a standardised OCTA analysis framework and compared their extracted parameters among controls and AD/mild cognitive impairment (MCI) in a cross-section study.

METHODS

We defined and extracted geometrical parameters of retinal microvasculature at different retinal layers and in the foveal avascular zone (FAZ) from segmented OCTA images obtained using well-validated state-of-the-art deep learning models. We studied these parameters in 158 subjects (62 healthy control, 55 AD and 41 MCI) using logistic regression to determine their potential in predicting the status of our subjects.

RESULTS

In the AD group, there was a significant decrease in vessel area and length densities in the inner vascular complexes (IVC) compared with controls. The number of vascular bifurcations in AD is also significantly lower than that of healthy people. The MCI group demonstrated a decrease in vascular area, length densities, vascular fractal dimension and the number of bifurcations in both the superficial vascular complexes (SVC) and the IVC compared with controls. A larger vascular tortuosity in the IVC, and a larger roundness of FAZ in the SVC, can also be observed in MCI compared with controls.

CONCLUSION

Our study demonstrates the applicability of OCTA for the diagnosis of AD and MCI, and provides a standard tool for future clinical service and research. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of AD and MCI.

Infant and Adult Human Intestinal Enteroids are Morphologically and Functionally Distinct

Background & Aims

Human intestinal enteroids (HIEs) are gaining recognition as physiologically relevant models of the intestinal epithelium. While HIEs from adults are used extensively in biomedical research, few studies have used HIEs from infants. Considering the dramatic developmental changes that occur during infancy, it is important to establish models that represent infant intestinal characteristics and physiological responses.

Methods

We established jejunal HIEs from infant surgical samples and performed comparisons to jejunal HIEs from adults using RNA sequencing (RNA-Seq) and morphologic analyses. We validated differences in key pathways through functional studies and determined if these cultures recapitulate known features of the infant intestinal epithelium.

Results

RNA-Seq analysis showed significant differences in the transcriptome of infant and adult HIEs, including differences in genes and pathways associated with cell differentiation and proliferation, tissue development, lipid metabolism, innate immunity, and biological adhesion. Validating these results, we observed a higher abundance of cells expressing specific enterocyte, goblet cell and enteroendocrine cell markers in differentiated infant HIE monolayers, and greater numbers of proliferative cells in undifferentiated 3D cultures. Compared to adult HIEs, infant HIEs portray characteristics of an immature gastrointestinal epithelium including significantly shorter cell height, lower epithelial barrier integrity, and lower innate immune responses to infection with an oral poliovirus vaccine.

Conclusions

HIEs established from infant intestinal tissues reflect characteristics of the infant gut and are distinct from adult cultures. Our data support the use of infant HIEs as an ex-vivo model to advance studies of infant-specific diseases and drug discovery for this population.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

Greater reliance on model-free learning in adolescent anorexia nervosa: An examination of dual-system reinforcement learning

Alterations in learning and decision-making systems are thought to contribute to core features of anorexia nervosa (AN), a psychiatric disorder characterized by persistent dietary restriction and weight loss. Instrumental learning theory identifies a dual-system of habit and goal-directed decision-making, linked to model-free and model-based reinforcement learning algorithms. Difficulty arbitrating between these systems, resulting in an over-reliance on one strategy over the other, has been implicated in compulsivity and extreme goal pursuit, both of which are observed in AN. Characterizing alterations in model-free and model-based systems, and their neural correlates, in AN may clarify mechanisms contributing to symptom heterogeneity (e.g., binge/purge symptoms). This study tested whether adolescents with restricting AN (AN-R; n = 36) and binge/purge AN (AN-BP; n = 20) differentially utilized model-based and model-free learning systems compared to a healthy control group (HC; n = 28) during a Markov two-step decision-making task under conditions of reward and punishment. Associations between model-free and model-based learning and resting-state functional connectivity between neural regions of interest, including orbitofrontal cortex (OFC), nucleus accumbens (NAcc), putamen, and sensory motor cortex (SMC) were examined. AN-R showed higher utilization of model-free learning compared to HC for reward, but attenuated model-free and model-based learning for punishment. In AN-R only, higher model-based learning was associated with stronger OFC-to-left NAcc functional connectivity, regions linked to goal-directed behavior. Greater utilization of model-free learning for reward in AN-R may differentiate this group, particularly during adolescence, and facilitate dietary restriction by prioritizing habitual control in rewarding contexts.

Canine and Feline Models of Inherited Retinal Diseases

Naturally occurring inherited retinal diseases (IRDs) in cats and dogs provide a rich source of potential models for human IRDs. In many cases, the phenotypes between the species with mutations of the homologous genes are very similar. Both cats and dogs have a high-acuity retinal region, the area centralis, an equivalent to the human macula, with tightly packed photoreceptors and higher cone density. This and the similarity in globe size to that of humans means these large animal models provide information not obtainable from rodent models. The established cat and dog models include those for Leber congenital amaurosis, retinitis pigmentosa (including recessive, dominant, and X-linked forms), achromatopsia, Best disease, congenital stationary night blindness and other synaptic dysfunctions, RDH5-associated retinopathy, and Stargardt disease. Several of these models have proven to be important in the development of translational therapies such as gene-augmentation therapies. Advances have been made in editing the canine genome, which necessitated overcoming challenges presented by the specifics of canine reproduction. Feline genome editing presents fewer challenges. We can anticipate the generation of specific cat and dog IRD models by genome editing in the future.

The Mef2c Gene Dose-Dependently Controls Hippocampal Neurogenesis and the Expression of Autism-Like Behaviors

Mutations in the activity-dependent transcription factor MEF2C have been associated with several neuropsychiatric disorders. Among these, autism spectrum disorder (ASD)-related behavioral deficits are manifested. Multiple animal models that harbor mutations in Mef2c have provided compelling evidence that Mef2c is indeed an ASD gene. However, studies in mice with germline or global brain knock-out of Mef2c are limited in their ability to identify the precise neural substrates and cell types that are required for the expression of Mef2c-mediated ASD behaviors. Given the role of hippocampal neurogenesis in cognitive and social behaviors, in this study we aimed to investigate the role of Mef2c in the structure and function of newly generated dentate granule cells (DGCs) in the postnatal hippocampus and to determine whether disrupted Mef2c function is responsible for manifesting ASD behaviors. Overexpression of Mef2c (Mef2cOE ) arrested the transition of neurogenesis at progenitor stages, as indicated by sustained expression of Sox2+ in Mef2cOE DGCs. Conditional knock-out of Mef2c (Mef2ccko ) allowed neuronal commitment of Mef2ccko cells; however, Mef2ccko impaired not only dendritic arborization and spine formation but also synaptic transmission onto Mef2ccko DGCs. Moreover, the abnormal structure and function of Mef2ccko DGCs led to deficits in social interaction and social novelty recognition, which are key characteristics of ASD behaviors. Thus, our study revealed a dose-dependent requirement of Mef2c in the control of distinct steps of neurogenesis, as well as a critical cell-autonomous function of Mef2c in newborn DGCs in the expression of proper social behavior in both sexes.

BDNF signaling requires Matrix Metalloproteinase-9 during structural synaptic plasticity

Synaptic plasticity underlies learning and memory processes as well as contributes, in its aberrant form, to neuropsychiatric disorders. One of its major forms is structural long-term potentiation (sLTP), an activity-dependent growth of dendritic spines that harbor excitatory synapses. The process depends on the release of brain-derived neurotrophic factor (BDNF), and activation of its receptor, TrkB. Matrix metalloproteinase-9 (MMP-9), an extracellular protease is essential for many forms of neuronal plasticity engaged in physiological as well as pathological processes. Here, we utilized two-photon microscopy and two-photon glutamate uncaging to demonstrate that MMP-9 activity is essential for sLTP and is rapidly (~seconds) released from dendritic spines in response to synaptic stimulation. Moreover, we show that either chemical or genetic inhibition of MMP-9 impairs TrkB activation, as measured by fluorescence lifetime imaging microscopy of FRET sensor. Furthermore, we provide evidence for a cell-free cleavage of proBDNF into mature BDNF by MMP-9. Our findings point to the autocrine mechanism of action of MMP-9 through BDNF maturation and TrkB activation during sLTP.

Multi-omic integration of microbiome data for identifying disease-associated modules

The human gut microbiome is a complex ecosystem with profound implications for health and disease. This recognition has led to a surge in multi-omic microbiome studies, employing various molecular assays to elucidate the microbiome's role in diseases across multiple functional layers. However, despite the clear value of these multi-omic datasets, rigorous integrative analysis of such data poses significant challenges, hindering a comprehensive understanding of microbiome-disease interactions. Perhaps most notably, multiple approaches, including univariate and multivariate analyses, as well as machine learning, have been applied to such data to identify disease-associated markers, namely, specific features (e.g., species, pathways, metabolites) that are significantly altered in disease state. These methods, however, often yield extensive lists of features associated with the disease without effectively capturing the multi-layered structure of multi-omic data or offering clear, interpretable hypotheses about underlying microbiome-disease mechanisms. Here, we address this challenge by introducing MintTea - an intermediate integration-based method for analyzing multi-omic microbiome data. MintTea combines a canonical correlation analysis (CCA) extension, consensus analysis, and an evaluation protocol to robustly identify disease-associated multi-omic modules. Each such module consists of a set of features from the various omics that both shift in concord, and collectively associate with the disease. Applying MintTea to diverse case-control cohorts with multi-omic data, we show that this framework is able to capture modules with high predictive power for disease, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome (MS) study, we found a MS-associated module comprising of a highly correlated cluster of serum glutamate- and TCA cycle-related metabolites, as well as bacterial species previously implicated in insulin resistance. In another cohort, we identified a module associated with late-stage colorectal cancer, featuring Peptostreptococcus and Gemella species and several fecal amino acids, in agreement with these species' reported role in the metabolism of these amino acids and their coordinated increase in abundance during disease development. Finally, comparing modules identified in different datasets, we detected multiple significant overlaps, suggesting common interactions between microbiome features. Combined, this work serves as a proof of concept for the potential benefits of advanced integration methods in generating integrated multi-omic hypotheses underlying microbiome-disease interactions and a promising avenue for researchers seeking systems-level insights into coherent mechanisms governing microbiome-related diseases.

Nationwide surveillance identifies yellow fever and chikungunya viruses transmitted by various species of Aedes mosquitoes in Nigeria

Background

Since its reemergence in 2017, yellow fever (YF) has been active in Nigeria. The Nigeria Centre for Disease Control (NCDC) has coordinated responses to the outbreaks with the support of the World Health Organization (WHO). The National Arbovirus and Vectors Research Centre (NAVRC) handles the vector component of these responses. This study sought to identify the vectors driving YF transmission and any of the targeted arboviruses and their distribution across states.

Methods

Eggs, larvae and pupae as well as adult mosquitoes were collected in observational, analytical, and cross-sectional surveys conducted in sixteen YF outbreak states between 2017 and 2020. Adult mosquitoes (field-collected or reared from immature stages) were morphologically identified, and arboviruses were detected using RT-qPCR at the African Centre of Excellence for Genomics of Infectious Diseases (ACEGID).

Results

Aedes mosquitoes were collected in eleven of the sixteen states surveyed and the mosquitoes in nine states were found infected with arboviruses. A total of seven Aedes species were collected from different parts of the country. Aedes aegypti was the most dominant (51%) species, whereas Aedes africanus was the least (0.2%). Yellow fever virus (YFV) was discovered in 33 (~26%) out of the 127 Aedes mosquito pools. In addition to YFV, the Chikungunya virus (CHIKV) was found in nine pools. Except for Ae. africanus, all the Aedes species tested positive for at least one arbovirus. YFV-positive pools were found in six (6) Aedes species while CHIKV-positive pools were only recorded in two Aedes species. Edo State had the most positive pools (16), while Nasarawa, Imo, and Anambra states had the least (1 positive pool). Breteau and house indices were higher than normal transmission thresholds in all but one state.

Conclusion

In Nigeria, there is a substantial risk of arbovirus transmission by Aedes mosquitoes, with YFV posing the largest threat at the moment. This risk is heightened by the fact that YFV and CHIKV have been detected in vectors across outbreak locations. Hence, there is an urgent need to step up arbovirus surveillance and control activities in the country.

Proteome profiling of cutaneous leishmaniasis lesions due to dermotropic Leishmania donovani in Sri Lanka

Characterization of the host response in cutaneous leishmaniasis (CL) through proteome profiling has gained limited insights in leishmaniasis research, in comparison to that of the parasite. The primary objective of this study was to comprehensively analyze the proteomic profile of the skin lesions tissues in patients with CL, by mass spectrometry, and subsequent validation of these findings through immunohistochemical methods. Sixty-seven proteins exhibited significant differential expression between tissues of CL lesions and healthy controls (p<0.01), representing numerous enriched biological processes within the lesion tissue, as evident by both the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Among these, the integrated endoplasmic reticulum stress response (IERSR) emerges as a pathway characterized by the up-regulated proteins in CL tissues compared to healthy skin. Expression of endoplasmic reticulum (ER) stress sensors, inositol-requiring enzyme-1 (IRE1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6) in lesion tissue was validated by immunohistochemistry. In conclusion, proteomic profiling of skin lesions carried out as a discovery phase study revealed a multitude of probable immunological and pathological mechanisms operating in patients with CL in Sri Lanka, which needs to be further elaborated using more in-depth and targeted investigations.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Association of gut microbiome with COPD in Japanese male residents: the SESSA study

Background

Altered gut microbiota may contribute to COPD development or progression. Herein, we investigated the association of gut microorganisms with COPD, taking into account the impact of smoking status.

Methods

This cross-sectional observational study was a part of the Shiga Epidemiological Study of Subclinical Atherosclerosis, a population-based cohort study of Japanese men aged 46-76 years, conducted from 2010 to 2016. The gut microbiome, determined using 16S rRNA gene sequencing, was compared among 99 never-smokers, 306 non-COPD ever-smokers and 76 patients with COPD while adjusting for age, body mass index, ethanol consumption and treatment for type 2 diabetes mellitus.

Results

The abundance of phylum Firmicutes was comparable between patients with COPD and non-COPD ever-smokers but tended to be higher in never-smokers. Similarly, the α- and β-diversity analysis showed similarity between patients with COPD and non-COPD ever-smokers, which tended to differ from never-smokers. Discriminant analysis identified the genus [Prevotella] to be more prevalent in patients with COPD than in never-smokers or non-COPD ever-smokers. Post hoc analysis confirmed similarity of gut microbiome between COPD Global Initiative for Chronic Obstructive Lung Disease (GOLD) I and non-COPD ever-smokers, which was different from GOLD II.

Conclusion

Smoking may alter the overall gut microbial composition, but gut microbial composition itself may not play a role in the development of COPD. Rather, specific gut bacteria, such as [Prevotella], could be a risk factor for the development of COPD; this may be a potential therapeutic target.

Breakage fusion bridge cycles drive high oncogene copy number, but not intratumoral genetic heterogeneity or rapid cancer genome change

Oncogene amplification is a major driver of cancer pathogenesis. Breakage fusion bridge (BFB) cycles, like extrachromosomal DNA (ecDNA), can lead to high copy numbers of oncogenes, but their impact on intratumoral heterogeneity, treatment response, and patient survival are not well understood due to difficulty in detecting them by DNA sequencing. We describe a novel algorithm that detects and reconstructs BFB amplifications using optical genome maps (OGMs), called OM2BFB. OM2BFB showed high precision (>93%) and recall (92%) in detecting BFB amplifications in cancer cell lines, PDX models and primary tumors. OM-based comparisons demonstrated that short-read BFB detection using our AmpliconSuite (AS) toolkit also achieved high precision, albeit with reduced sensitivity. We detected 371 BFB events using whole genome sequences from 2,557 primary tumors and cancer lines. BFB amplifications were preferentially found in cervical, head and neck, lung, and esophageal cancers, but rarely in brain cancers. BFB amplified genes show lower variance of gene expression, with fewer options for regulatory rewiring relative to ecDNA amplified genes. BFB positive (BFB (+)) tumors showed reduced heterogeneity of amplicon structures, and delayed onset of resistance, relative to ecDNA(+) tumors. EcDNA and BFB amplifications represent contrasting mechanisms to increase the copy numbers of oncogene with markedly different characteristics that suggest different routes for intervention.

In situ lipidomics of Staphylococcus aureus osteomyelitis using imaging mass spectrometry

Osteomyelitis occurs when Staphylococcus aureus invades the bone microenvironment, resulting in a bone marrow abscess with a spatially defined architecture of cells and biomolecules. Imaging mass spectrometry and microscopy are invaluable tools that can be employed to interrogate the lipidome of S. aureus-infected murine femurs to reveal metabolic and signaling consequences of infection. Here, nearly 250 lipids were spatially mapped to healthy and infection-associated morphological features throughout the femur, establishing composition profiles for tissue types. Ether lipids and arachidonoyl lipids were significantly altered between cells and tissue structures in abscesses, suggesting their roles in abscess formation and inflammatory signaling. Sterols, triglycerides, bis(monoacylglycero)phosphates, and gangliosides possessed ring-like distributions throughout the abscess, indicating dysregulated lipid metabolism in a subpopulation of leukocytes that cannot be discerned with traditional microscopy. These data provide chemical insight into the signaling function and metabolism of cells in the fibrotic border of abscesses, likely characteristic of lipid-laden macrophages.

Improving Seizure Frequency Documentation and Classification

Background and Objectives

Accurate and reliable seizure data are essential for evaluating treatment strategies and tracking the quality of care in epilepsy clinics. This quality improvement project aimed to increase seizure documentation (i.e., documentation of seizure frequency from 80% to 100%, date of last seizure from 35% to 50%, and International League Against Epilepsy (ILAE) seizure classification from 35% to at least 50%) over 6 months.

Methods

We surveyed 7 epileptologists to determine their perceived seizure frequency, ILAE classification, and date of last seizure documentation habits. Baseline data were collected weekly from September to December 2021. Subsequently, we implemented a newly created flowsheet in our Electronic Health Record (EHR) based on the Epilepsy Learning Healthcare System (ELHS) Case Report Forms to increase seizure documentation in a standardized way. Two epileptologists tested this flowsheet tool in their epilepsy clinics between February 2022 and July 2022. Data were collected weekly and compared with documentation from other epileptologists within the same group.

Results

Epileptologists at our center believed they documented seizure frequency for 84%-87% of clinic visits, which aligned with baseline data collection, showing they recorded seizure frequency for 83% of clinic visits. Epileptologists believed they documented ILAE classification for 47%-52% of clinic visits, and baseline data showed this was documented in 33% of clinic visits. They also reported documenting the date of the last seizure for 52%-63% of clinic visits, but this occurred in only 35% of clinic visits. After implementing the new flowsheet, documentation increased to nearly 100% for all fields being completed by the providers who tested the flowsheet.

Discussion

We demonstrated that by implementing an easy-to-use standardized EHR documentation tool, our documentation of critical metrics, as defined by the ELHS, improved dramatically. This shows that simple and practical interventions can substantially improve clinically meaningful documentation.

Precision Proteoform Design for 4R Tau Isoform Selective Templated Aggregation

Prion-like spread of disease-specific tau conformers is a hallmark of all tauopathies. A 19-residue probe peptide containing a P301L mutation and spanning the R2/R3 splice junction of tau, folds and stacks into seeding-competent fibrils and induces aggregation of 4R, but not 3R tau. These tau peptide fibrils propagate aggregated intracellular tau over multiple generations, have a high β-sheet content, a colocalized lipid signal, and adopt a well-defined U-shaped fold found in 4R tauopathy brain-derived fibrils. Fully atomistic replica exchange molecular dynamics (MD) simulations were used to compute the free energy landscapes of the conformational ensemble of the peptide monomers. These identified an aggregation-prohibiting β-hairpin structure and an aggregation-competent U-fold unique to 4R tauopathy fibrils. Guided by MD simulations, we identified that the N-terminal-flanking residues to PHF6, which slightly vary between 4R and 3R isoforms, modulate seeding. Strikingly, when a single amino acid switch at position 305 replaced the serine of 4R tau with a lysine from the corresponding position in the first repeat of 3R tau, the seeding induced by the 19-residue peptide was markedly reduced. Conversely, a 4R tau mimic with three repeats, prepared by replacing those amino acids in the first repeat with those amino acids uniquely present in the second repeat, recovered aggregation when exposed to the 19-residue peptide. These peptide fibrils function as partial prions to recruit naïve 4R tau-ten times the length of the peptide-and serve as a critical template for 4R tauopathy propagation. These results hint at opportunities for tau isoform-specific therapeutic interventions.

Characterising collateral vessels in eyes with branch retinal vein occlusions using widefield swept-source optical coherence tomography angiography

BACKGROUND/AIMS

To characterise the morphology, location and functional significance of both macular and extramacular collateral vessels (CVs) in patients with a history of branch retinal vein occlusion (BRVO) using widefield swept-source optical coherence tomography angiography (WF SS OCTA).

METHODS

Patients with a history of BRVO underwent WF SS OCTA testing to acquire 12×12 mm images, which were evaluated for CVs and non-perfusion area (NPA). Region of interest analysis of individual CVs was performed to identify correlations between CV size, depth and retinal location. Mixed effects multivariate regression analyses of factors associated with NPA and visual acuity (VA) were performed.

RESULTS

Fifty-five CVs were identified in 28 BRVO eyes from 27 patients. CVs were identified in 42.9% (12/28) of eyes with a history of BRVO, and of these, 45.5% (25/55) were extramacular. The majority of CVs (87.3%, 48/55) coursed through both the superficial and the deep capillary plexus (DCP), while a subset (12.7%, 7/55) were strictly superficial. No CVs were found to course strictly through the DCP alone. CV depth increased with distance from the optic disc (p=0.011) and CV size increased with distance from the fovea (p=0.005). There were no statistically significant associations between CVs and NPA, or between CVs and VA.

CONCLUSIONS

WF SS OCTA revealed that a large fraction of CVs that form after BRVO are extramacular, and the morphology of CVs varies as a function of retinal location. Depth-resolved study of CVs may offer valuable insights on the pathophysiological mechanisms leading to the development of macular oedema.

Promoter capture drives the emergence of proto-genes in Escherichia coli

The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli Long-Term Evolution Experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time-span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, thereby serving as raw material for new gene emergence. Most proto-genes result either from insertion element activity or chromosomal translocations that fused pre-existing regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, persist stably, and can serve as potential substrates for new gene formation.

Pulsed stimuli entrain p53 to synchronize single cells and modulate cell-fate determination

Entrainment to an external stimulus enables a synchronized oscillatory response across a population of cells, increasing coherent responses by reducing cell-to-cell heterogeneity. It is unclear whether the property of entrainability extends to systems where responses are intrinsic to the individual cell, rather than dependent on coherence across a population of cells. Using a combination of mathematical modeling, time-lapse fluorescence microscopy, and single-cell tracking, we demonstrated that p53 oscillations triggered by DNA double-strand breaks (DSBs) can be entrained with a periodic damage stimulus, despite such synchrony not known to function in effective DNA damage responses. Surprisingly, p53 oscillations were experimentally entrained over a wider range of DSB frequencies than predicted by an established computational model for the system. We determined that recapitulating the increased range of entrainment frequencies required, non-intuitively, a less robust oscillator and wider steady-state valley on the energy landscape. Further, we show that p53 entrainment can lead to altered expression dynamics of downstream targets responsible for cell fate in a manner dependent on target mRNA stability. Overall, this study demonstrates that entrainment can occur in a biological oscillator despite the apparent lack of an evolutionary advantage conferred through synchronized responses and highlights the potential of externally entraining p53 dynamics to reduce cellular variability and synchronize cell-fate responses for therapeutic outcomes.

Directed Evolution of Genetically Encoded LYTACs for Cell-Mediated Delivery

Lysosome-targeting chimeras (LYTACs) are a promising therapeutic modality to drive the degradation of extracellular proteins. However, early versions of LYTAC contain synthetic glycopeptides that cannot be genetically encoded. Here we present our designs for a fully genetically encodable LYTAC (GELYTAC), making our tool compatible with integration into therapeutic cells for targeted delivery at diseased sites. To achieve this, we replaced the glycopeptide portion of LYTACs with the protein insulin like growth factor 2 (IGF2). After showing initial efficacy with wild type IGF2, we increased the potency of GELYTAC using directed evolution. Subsequently, we demonstrated that our engineered GELYTAC construct not only secretes from HEK293T cells but also from human primary T-cells to drive the uptake of various targets into receiver cells. Immune cells engineered to secrete GELYTAC thus represent a promising avenue for spatially-selective targeted protein degradation.

Impact and Role of Hypothalamic Corticotropin Releasing Hormone Neurons in Withdrawal from Chronic Alcohol Consumption in Female and Male Mice

Worldwide, alcohol use and abuse are a leading risk of mortality, causing 5.3% of all deaths (World Health Organization, 2022). The endocrine stress system, initiated by the peripheral release of corticotropin releasing hormone (CRH) from primarily glutamatergic neurons in the paraventricular nucleus of the hypothalamus (PVN), is profoundly linked with alcohol use, abuse, and relapse (Blaine and Sinha, 2017). These PVN CRH-releasing (PVNCRH) neurons are essential for peripheral and central stress responses (Rasiah et al., 2023), but little is known about how alcohol affects these neurons. Here, we show that two-bottle choice alcohol consumption blunts the endocrine-mediated corticosterone response to stress during acute withdrawal in female mice. Conversely, using slice electrophysiology, we demonstrate that acute withdrawal engenders a hyperexcitable phenotype of PVNCRH neurons in females that is accompanied by increased glutamatergic transmission in both male and female mice. GABAergic synaptic transmission was unaffected by alcohol history. We then tested whether chemogenetic inhibition of PVNCRH neurons would restore stress response in female mice with a history of alcohol drinking in the looming disk test, which mimics an approaching predator threat. Accordingly, inhibition of PVNCRH neurons reduced active escape in hM4Di alcohol history mice only. This study indicates that stress-responsive PVNCRH neurons in females are particularly affected by a history of alcohol consumption. Interestingly, women have indicated an increase in heavy alcohol use to cope with stress (Rodriguez et al., 2020), perhaps pointing to a potential underlying mechanism in alcohol-mediated changes to PVNCRH neurons that alter stress response.SIGNIFICANCE STATEMENT Paraventricular nucleus of the hypothalamus neurons that release corticotropin releasing hormone (PVNCRH) are vital for stress response. These neurons have been understudied in relation to alcohol and withdrawal despite profound relations between stress, alcohol use disorders (AUD), and relapse. In this study, we use a variety of techniques to show that acute withdrawal from a history of alcohol impacts peripheral stress response, PVNCRH neurons, and behavior. Specifically, PVNCRH are in a hyperactive state during withdrawal, which drives an increase in active stress coping behaviors in female mice only. Understanding how alcohol use and withdrawal affects stress responding PVNCRH neurons may contribute to finding new potential targets for the treatment of alcohol use disorder.

Aberrant splicing in Huntington's disease via disrupted TDP-43 activity accompanied by altered m6A RNA modification

Huntington's disease (HD) is a neurodegenerative disorder caused by a CAG repeat expansion in the first exon of the HTT gene encoding huntingtin. Prior reports have established a correlation between CAG expanded HTT and altered gene expression. However, the mechanisms leading to disruption of RNA processing in HD remain unclear. Here, our analysis of the reported HTT protein interactome identifies interactions with known RNA-binding proteins (RBPs). Total, long-read sequencing and targeted RASL-seq of RNAs from cortex and striatum of the HD mouse model R6/2 reveals increased exon skipping which is confirmed in Q150 and Q175 knock-in mice and in HD human brain. We identify the RBP TDP-43 and the N6-methyladenosine (m6A) writer protein methyltransferase 3 (METTL3) to be upstream regulators of exon skipping in HD. Along with this novel mechanistic insight, we observe decreased nuclear localization of TDP-43 and cytoplasmic accumulation of phosphorylated TDP-43 in HD mice and human brain. In addition, TDP-43 co-localizes with HTT in human HD brain forming novel nuclear aggregate-like bodies distinct from mutant HTT inclusions or previously observed TDP-43 pathologies. Binding of TDP-43 onto RNAs encoding HD-associated differentially expressed and aberrantly spliced genes is decreased. Finally, m6A RNA modification is reduced on RNAs abnormally expressed in striatum from HD R6/2 mouse brain, including at clustered sites adjacent to TDP-43 binding sites. Our evidence supports TDP-43 loss of function coupled with altered m6A modification as a novel mechanism underlying alternative splicing/unannotated exon usage in HD and highlights the critical nature of TDP-43 function across multiple neurodegenerative diseases.

The PHB Granule Biogenesis Pathway in Caulobacter

PHB granules are bacterial organelles that store excess carbohydrates in the form of water-insoluble polyhydroxybutyrate (PHB). The PHB polymerase, phasin (a small amphipathic protein), and active PHB synthesis are essential for the formation of mature PHB granules in Caulobacter crescentus. Granule formation was found to be initiated by the condensation of self-associating PHB polymerase-GFP into foci, closely followed by the recruitment and condensation of phasin-mCherry. Following the active synthesis of PHB and granule maturation, the polymerase dissociates from mature granules and the PHB depolymerase is recruited to the granule. The polymerase directly binds phasin in vitro through its intrinsically disordered N-terminal domain. Thus, granule biogenesis is initiated and controlled by the action of a PHB polymerase and an associated helper protein, phasin, that together synthesize the hydrophobic granule's content while forming the granules protein boundary.

Interfacial morphodynamics of proliferating microbial communities

In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.

Mesenchymal-specific Alms1 knockout in mice recapitulates key metabolic features of Alström Syndrome

Background

Alström Syndrome (AS), a multi-system disease caused by mutations in the ALMS1 gene, includes obesity with disproportionately severe insulin resistant diabetes, dyslipidemia, and hepatosteatosis. How loss of ALMS1 causes this phenotype is poorly understood, but prior studies have circumstancially implicated impaired adipose tissue expandability. We set out to test this by comparing the metabolic effects of selective Alms1 knockout in mesenchymal cells including preadipocytes to those of global Alms1 knockout.

Methods

Global Alms1 knockout (KO) mice were generated by crossing floxed Alms1 and CAG-Cre mice. A Pdgfrα -Cre driver was used to abrogate Alms1 function selectively in mesenchymal stem cells (MSCs) and their descendants, including preadipocytes. We combined metabolic phenotyping of global and Pdgfrα + Alms1 -KO mice on a 45% fat diet with measurements of body composition and food intake, and histological analysis of metabolic tissues.

Results

Global Alms1 KO caused hyperphagia, obesity, insulin resistance, dyslipidaemia, and fatty liver. Pdgfrα - cre driven KO of Alms1 (MSC KO) recapitulated insulin resistance, fatty liver, and dyslipidaemia in both sexes. Other phenotypes were sexually dimorphic: increased fat mass was only present in female Alms1 MSC KO mice. Hyperphagia was not evident in male Alms1 MSC KO mice, but was found in MSC KO females, despite no neuronal Pdgfr α expression.

Conclusions

Mesenchymal deletion of Alms1 recapitulates the metabolic features of AS, including severe fatty liver. This confirms a key role for Alms1 in the adipose lineage, where its loss is sufficient to cause systemic metabolic effects and damage to remote organs. AS should be regarded as a forme fruste of lipodystrophy. Therapies should prioritise targeting positive energy balance.

Whole blood mitochondrial copy number in clinical populations with mood disorders: a meta-analysis

Background

Major depressive disorder (MDD) and bipolar disorder (BD), are globally prevalent, contributing to significant disease burden and adverse health outcomes. These mood disorders are associated with changes in many aspects of brain reward pathways, yet cellular and molecular changes in the brain are not readily available in clinical populations. Therefore, the use of biomarkers as proxies for changes in the brain are necessary. The proliferation of mitochondria in blood has emerged as a potentially useful biomarker, yet a clear consensus on how these mood disorders impact mitochondrial DNA copy number (mtDNAcn) has not been reached.

Methods

Following PRISMA guidelines for a systematic search, 22 papers met inclusion criteria for meta-analysis (10 MDD, 10 BD, 2 both MDD and BD). We extracted demographic, disorder, and methodological information with mtDNAcn. Using the metafor package for R, calculated effect sizes were used in random effects or meta regression models for MDD and BD.

Results

Our results show a trending increase in mtDNAcn in patients with MDD, which reaches significance when one study with outlying demographic characteristics is excluded. Overall, there was no effect of BD on mtDNAcn, however, further subgroup and meta-regression analysis indicated the effects on mtDNAcn are dependent on BD type.

Conclusions

Together our data suggest whole blood/leukocyte mtDNAcn may be a useful biomarker for mood disorders, with MDD and BD Type II associated with higher mtDNAcn, and BD Type I associated with lower mtDNAcn. Further study of blood mtDNAcn could predict downstream health outcomes or treatment responsivity in individuals with mood disorders.

Photoswitchable binders enable temporal dissection of endogenous protein function

General methods for spatiotemporal control of specific endogenous proteins would be broadly useful for probing protein function in living cells. Synthetic protein binders that bind and inhibit endogenous protein targets can be obtained from nanobodies, designed ankyrin repeat proteins (DARPins), and other small protein scaffolds, but generalizable methods to control their binding activity are lacking. Here, we report robust single-chain photoswitchable DARPins (psDARPins) for bidirectional optical control of endogenous proteins. We created topological variants of the DARPin scaffold by computer-aided design so fusion of photodissociable dimeric Dronpa (pdDronpa) results in occlusion of target binding at baseline. Cyan light induces pdDronpa dissociation to expose the binding surface (paratope), while violet light restores pdDronpa dimerization and paratope caging. Since the DARPin redesign leaves the paratope intact, the approach was easily applied to existing DARPins for GFP, ERK, and Ras, as demonstrated by relocalizing GFP-family proteins and inhibiting endogenous ERK and Ras with optical control. Finally, a Ras-targeted psDARPin was used to determine that, following EGF-activation of EGFR, Ras is required for sustained EGFR to ERK signaling. In summary, psDARPins provide a generalizable strategy for precise spatiotemporal dissection of endogenous protein function.