bluuebunny/crossref_metadata_2025 huggingface dataset:
An accessible and versatile deep learning-based sleep stage classifier
Authors: Hanna Jevri , Flöel Agnes
Published: August 2022

Manual sleep analysis for research purposes and for the diagnosis of sleep disorders is labor-intensive and often produces unreliable results, which has motivated many attempts to design automatic sleep stage classifiers. With the recent introduction of large, publicly available hand-scored polysomnographic data, and concomitant advances in machine learning methods to solve complex classification problems with supervised learning, the problem has received new attention, and a number of new classifiers that provide excellent accuracy. Most of these however have non-trivial barriers to use. We introduce the Greifswald Sleep Stage Classifier (GSSC), which is free, open source, and can be relatively easily installed and used on any moderately powered computer. In addition, the GSSC has been trained to perform well on a large variety of electrode set-ups, allowing high performance sleep staging with portable systems. The GSSC can also be readily integrated into brain-computer interfaces for real-time inference. These innovations were achieved while simultaneously reaching a level of accuracy equal to, or exceeding, recent state of the art classifiers and human experts, making the GSSC an excellent choice for researchers in need of reliable, automatic sleep staging.
Single-nuclear RNA sequencing of endomyocardial biopsies identifies persistence of donor-recipient chimerism with distinct signatures in severe cardiac allograft vasculopathy
Authors: Amancherla Kaushik , Qin Juan , Hulke Michelle L , Pfeiffer Ryan D , Agrawal Vineet , Sheng Quanhu , Xu Yaomin , Schlendorf Kelly H , Lindenfeld JoAnn , Shah Ravi V , Freedman Jane E , Tucker Nathan R , Moslehi Javid
Published: August 2022

Cardiac allograft vasculopathy (CAV) is the leading cause of late allograft failure and mortality after heart transplantation. As current standards of diagnosis and treatment of CAV have significant limitations, understanding cell-specific responses may prove critical for developing improved detection strategies and novel therapeutics. This study is the first to successfully utilize human endomyocardial biopsy (EMB) samples to isolate large numbers of intact nuclei for single-nuclear transcriptomics. These data also lay the groundwork for ongoing experiments to study serial, routinely-collected EMB specimens after heart transplantation to identify novel biomarkers and pathways through which early CAV pathogenesis can be interrupted, thereby prolonging allograft survival.
HepaCAM Suppresses Glioblastoma Stem Cell Invasion in the Brain
Authors: De Arpan , Lattier John M. , Morales John E. , Kelly Jack R. , Zheng Xiaofeng , Chen Zhihua , Sebastian Sumod , Huse Jason T. , Lang Frederick F. , McCarty Joseph H.
Published: August 2022

Glioblastoma (GBM) is a malignant brain cancer that contains sub-populations of highly invasive tumor cells that drive progression and recurrence after surgery and radiochemotherapy. The exact mechanisms that enable GBM cells to disperse from the main tumor mass and navigate throughout the brain microenvironment remain largely unknown. As a result, there is a lack of effective strategies to block cancer cell invasive growth in primary and recurrent GBM. Here we report that hepatocyte cell adhesion molecule (hepaCAM), which is normally expressed in perivascular astrocytes, plays central roles in controlling the invasive growth features of GBM cells. Genetically targeting HEPACAM induces a transition from GBM cell proliferation/self-renewal to invasion. Increased invasion is due, in part, to an activation of focal adhesion signaling pathways and enhanced GBM cell adhesion to the extracellular matrix (ECM) in the brain microenvironment. Transcriptional profiling of GBM cells reveals various HEPACAM-regulated genes with links to polarity and invasion. Collectively, these data show that hepaCAM balances ECM adhesion and signaling pathways to control cancer cell proliferation versus invasion in the brain parenchyma. Targeting select components of the hepaCAM pathway may be an effective way to block tumor progression and recurrence in patients with GBM.
The effect of selective logging on microclimates, arthropod abundance and the foraging behaviour of Eastern Himalayan birds
Authors: Aggarwal Kanika , Chanda Ritobroto , Rai Shambu , Rai Mangal , Pradhan D.K. , Munda Binod , Tamang Bharat , Biswakarma Aman , Srinivasan Umesh
Published: August 2022

1. Selective logging—the practice of removing a subset of commercially important trees from a forest—is a globally pervasive form of forest degradation. Selective logging alters both the structure and function of forests and the composition of ecological communities.

2. Tropical insectivorous birds are highly vulnerable to microhabitat alterations in logged forest. Such altered microhabitats might affect the foraging of forest birds by altering (a) resource availability, and (b) foraging behaviour.

3. We investigated the effect of selective logging on microclimates, prey availability, foraging behaviour and the foraging success of eastern Himalayan birds in the breeding season.

4. Selective logging alters temperature-humidity microclimates and the composition of arthropod communities, both of which are likely to then collectively alter foraging behaviour by birds. We show that birds spent a lower proportion of their time foraging in primary compared with logged forest. Further, selective logging interacts with species traits such as body mass, preferred foraging stratum (understorey, midstorey or canopy) and foraging manoeuvre to influence foraging success. Gleaners generally foraged more successfully in primary forest and salliers in logged forest, although these patterns were modified by body mass and foraging stratum.

5. Synthesis and applications: Our study shows how altered microclimates in anthropogenically modified habitats can influence resource availability and have downstream impacts on the behaviour of species at higher trophic levels.
Antimicrobial peptides do not directly contribute to aging inDrosophila, but improve lifespan by preventing dysbiosis
Authors: Hanson M.A. , Lemaitre B.
Published: August 2022

Antimicrobial peptides (AMPs) are innate immune effectors first studied for their role in host defense against bacterial and fungal infections. Recent studies have implicated these peptides in the clearance of aberrant cells and various neurological processes including neurodegenerative syndromes. InDrosophila, an array of AMPs are produced downstream of the Toll and Imd NF-κB pathways in response to infection. Many studies have suggested a role for the Imd pathway and AMPs in aging in this insect, supported by the upregulation of AMPs with aging (so-called “inflammaging”). However, functional studies using RNAi or over-expression have been inconclusive on whether and how these immune effectors impact aging.

Leveraging a new set of single and compound AMP gene deletions in a controlled genetic background, we have investigated how AMPs contribute to aging. Overall, we found no major effect of individual AMPs on lifespan, with a possible exception ofDefensin. However,ΔAMP14flies lacking 14 AMP genes from seven families display a reduced lifespan. Interestingly, we found an increased bacterial load in the food medium of agedΔAMP14flies, suggesting that the lifespan reduction of these flies was due to a failure in controlling the microbiome. Consistent with this idea, use of germ-free conditions extends the lifespan ofΔAMP14flies. Overall, our results do not point to an overt role of individual AMPs in lifespan. Instead, we find that AMPs collectively impact lifespan by preventing dysbiosis over aging. This is consistent with our previous study showing that AMPs control the gut microbiome, and many works showing that dysbiosis is detrimental upon aging. In the course of our experiments, we also uncovered a strong impact of aDrosophila nora virusinfection on lifespan, and share our experience in reconciling our data given this confounding cryptic factor.
Zika virus-induces metabolic alterations in fetal neuronal progenitors that could influence in neurodevelopment during early pregnancy
Authors: Gilbert-Jaramillo Javier , Purnama Ujang , Molnár Zoltán , James William S.
Published: August 2022

Neuronal progenitor subtypes have distinct fate restrictions regulated by time-dependent activation of energetic pathways. Thus, the hijacking of cellular metabolism by Zika virus (ZIKV) to support its replication may contribute to damage in the developing fetal brain. Here, we showed that ZIKV replicates differently in two glycolytically distinct hiPSC-derived neuronal progenitors that correspond to early and late progenitors in the forebrain. This differential replication alters the transcription of metabolic genes and upregulates the glycolytic capacity of progenitor subtypes. Analysis using Imagestream® revealed that, during early stages of infection, ZIKV replication in early progenitors increases lipid droplet abundance and decreases mitochondrial size and membrane potential. During later stages infection, early progenitors show increased subcellular distribution of lipid droplets, whilst late progenitors show decreased mitochondria size. The finding that there are hi-NPC subtype-specific alterations of cellular metabolism during ZIKV infection may help to explain the differences in brain damage over each trimester.
MicroRNA-218 instructs proper assembly of hippocampal networks
Authors: Taylor Seth R. , Kobayashi Mariko , Vilella Antonietta , Tiwari Durgesh , Zolboot Norjin , Hartzell Andrea , Girgiss Carol , Abaci Yusuf , De Sanctis Claudia , Bellenchi Gian Carlo , Darnell Robert B. , Gross Christina , Zoli Michele , Berg Darwin K. , Lippi Giordano
Published: August 2022

The assembly of the mammalian brain is orchestrated by temporally coordinated waves of gene expression. A key aspect of this developmental program is mediated at the post-transcriptional level by microRNAs (miRNAs). Deletion of neuronal enriched miRNAs induces strong developmental phenotypes, and multiple reports have found altered levels of miRNAs in patients with neurodevelopmental disorders. However, cellular and molecular mechanisms used by miRNAs to instruct proper brain development remain largely unexplored.

Here, through multiple screens, we identified miR-218 as a critical regulator of hippocampal assembly in mice. MiR-218 is highly expressed in the hippocampus and enriched in both excitatory principal neurons and GABAergic inhibitory interneurons. Transient inhibition of miR-218 in early life results in an adult brain with heightened network activity and a predisposition to seizures. We used RNA-seq and FACS-seq (fluorescence-activated cell sorting followed by RNA-seq) to identify global and cell type-specific changes in gene expression in the absence of miR-218 and narrow down which altered developmental processes would lead to long-term network instability. We find that miR-218 inhibition results in the disruption of early depolarizing GABAergic signaling, structural defects in dendritic spines, and altered intrinsic membrane excitability. Finally, conditional knockout of miR-218 in interneurons, but not pyramidal neurons is sufficient to recapitulate the effects on long-term stability. Taken together, the data suggest that miR-218 orchestrates hippocampal network assembly to produce a stable network in the adult, primarily by regulating interneuron function in early postnatal life.
Sex separation unveils the functional plasticity of the vomeronasal organ in rabbits
Authors: Villamayor PR , Gullón J , Quintela L , Sánchez-Quinteiro P , Martínez P , Robledo D
Published: August 2022

Background

Chemosensory cues are vital for social and sexual behaviours and are primarily detected and processed by the vomeronasal system (VNS), whose plastic capacity has been investigated in mice. However, studying chemosensory plasticity outside of laboratory conditions may give a more realistic picture of how the VNS adapts to a changing environment. Rabbits are a well-described model of chemocommunication since the discovery of the rabbit mammary pheromone and their vomeronasal organ (VNO) transcriptome was recently characterized, a first step to further study plasticity-mediated transcriptional changes. In this study, we assess the plastic capacity of the rabbit male and female VNO under sex-separation vs sex-combined scenarios, including adults and juveniles, to determine whether the rabbit VNO is plastic and, if so, whether such plasticity is already established at early stages of life.

Results

First, we characterized the number of differentially expressed genes (DEGs) between the VNO of rabbit male and female under sex-separation and compared it to sex-combined individuals, both in adults and juveniles, finding that differences between male and female were larger in a sex-separated scenario. Secondly, we analyzed the number of DEGs between sex-separated and sex-combined scenarios, both in males and females. In adults, both sexes showed a high number of DEGs while in juveniles only females showed differences. Additionally, the vomeronasal receptor genes were strikingly down-regulated in sex-separated adult females, whereas in juveniles up-regulation was shown for the same condition, suggesting a role of VRs in puberty onset. Finally, we described the environment-modulated plastic capacity of genes involved in reproduction, immunity and VNO functional activity, including G-protein coupled receptors.

Conclusions

Our results show that sex-separation induces sex- and stage- specific gene expression differences in the VNO of male and female rabbit, both in adults and juveniles. These results bring out for the first time the plastic capacity of the rabbit VNO, supporting its functional adaptation to specifically respond to a continuous changing environment. Finally, species-specific differences and individual variability should always be considered in VNO studies and overall chemocommunication research.
Doomed by popularity: The broad use of the Pm8 resistance gene in wheat resulted in hypermutation of the AvrPm8 gene in the powdery mildew pathogen
Authors: Kunz Lukas , Sotiropoulos Alexandros G. , Graf Johannes , Razavi Mohammad , Müller Marion C. , Keller Beat
Published: August 2022

The Pm8 resistance gene against the powdery mildew disease has been introgressed from rye into wheat as part of a large 1BL.1RS chromosomal translocation. Due to its high agronomic value, this translocation has seen continuous global use since the 1960’s on large growth areas, even after Pm8 resistance was overcome. This allows studying the effect of long and widespread resistance gene use on a pathogen population.

Using genome wide association studies in a global population of wheat mildew isolates, we identified the avirulence effector AvrPm8 specifically recognized by Pm8.

Haplovariant mining in the global population revealed 17 virulent haplotypes of the AvrPm8 gene that grouped into two categories. The first one from geographically diverse regions comprised two single amino acid polymorphisms at the same position in the AvrPm8 protein, which we confirmed to be crucial for recognition by Pm8. The second category consisted of numerous destructive mutations to the AvrPm8 open reading frame.

Most individual gain-of-virulence mutations were found in geographically restricted regions, indicating they occurred recently as a consequence of the frequent Pm8 use. We conclude that both standing genetic variation as well as locally occurring new mutations contributed to the global breakdown of the Pm8 resistance gene introgression.
Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins
Authors: Gandarilla-Pérez Carlos A. , Pinilla Sergio , Bitbol Anne-Florence , Weigt Martin
Published: August 2022

Predicting protein-protein interactions from sequences is an important goal of computational biology. Various sources of information can be used to this end. Starting from the sequences of two interacting protein families, one can use phylogeny or residue coevolution to infer which paralogs are specific interaction partners within each species. We show that these two signals can be combined to improve the performance of the inference of interaction partners among paralogs. For this, we first align the sequence-similarity graphs of the two families through simulated annealing, yielding a robust partial pairing. We next use this partial pairing to seed a coevolution-based iterative pairing algorithm. This combined method improves performance over either separate method. The improvement obtained is striking in the difficult cases where the average number of paralogs per species is large or where the total number of sequences is modest.

Author summary

When two protein families interact, their sequences feature statistical dependencies. First, interacting proteins tend to share a common evolutionary history. Second, maintaining structure and interactions through the course of evolution yields coevolution, detectable via correlations in the amino-acid usage at contacting sites. Both signals can be used to computationally predict which proteins are specific interaction partners among the paralogs of two interacting protein families, starting just from their sequences. We show that combining them improves the performance of interaction partner inference, especially when the average number of potential partners is large and when the total data set size is modest. The resulting paired multiple-sequence alignments might be used as input to machine-learning algorithms to improve protein-complex structure prediction, as well as to understand interaction specificity in signaling pathways.
Increasing quantitation in spatial single-cell metabolomics by using fluorescence as ground truth
Authors: Molenaar Martijn R. , Shahraz Mohammed , Delafiori Jeany , Eisenbarth Andreas , Ekelöf Måns , Rappez Luca , Alexandrov Theodore
Published: August 2022

Imaging mass spectrometry (MS) is becoming increasingly applied for single-cell analyses. Multiple methods for imaging MS-based single-cell metabolomics were proposed, including our recent method SpaceM. An important step in imaging MS-based single-cell metabolomics is the assignment of MS intensities from individual pixels to single cells. In this process, referred to as pixel-cell deconvolution, the MS intensities of regions sampled by the imaging MS laser are assigned to the segmented single cells. The complexity of the contributions from multiple cells and the background, as well as lack of full understanding of how input from molecularly-heterogeneous areas translates into mass spectrometry intensities make the cell-pixel deconvolution a challenging problem.

Here, we propose a novel approach to evaluate pixel-cell deconvolution methods by using a molecule detectable both by mass spectrometry and fluorescent microscopy, namely fluorescein diacetate (FDA). FDA is a cell-permeable small molecule that becomes fluorescent after internalisation in the cell and subsequent cleavage of the acetate groups. Intracellular fluorescein can be easily imaged using fluorescence microscopy. Additionally, it is detectable by matrix-assisted laser desorption/ionisation (MALDI) imaging MS. The key idea of our approach is to use the fluorescent levels of fluorescein as the ground truth to evaluate the impact of using various pixel-cell deconvolution methods onto single-cell fluorescein intensities obtained by the SpaceM method.

Following this approach, we evaluated multiple pixel-cell deconvolution methods, the ‘weighted average’ method originally proposed in the SpaceM method as well as the novel ‘linear inverse modelling’ method. Despite the potential of the latter method in resolving contributions from individual cells, this method was outperformed by the weighted average approach. Using the ground truth approach, we demonstrate the extent of the ion suppression effect which considerably worsens the pixel-cell deconvolution quality. For compensating the ion suppression, we propose a novel data-driven approach. We show that compensating the ion suppression effect in a single-cell metabolomics dataset of co-cultured HeLa and NIH3T3 cells considerably improved the separation between both cell types. Finally, using the same ground truth, we evaluate the impact of drop-outs in the measurements and discuss the optimal filtering parameters of SpaceM processing steps before pixel-cell deconvolution.
Data Fusion by Matrix Completion for Exposome Target Interaction Prediction
Authors: Wang Kai , Kim Nicole , Bagherian Maryam , Li Kai , Chou Elysia , Colacino Justin A. , Dolinoy Dana C. , Sartor Maureen A.
Published: August 2022

Human exposure to toxic chemicals presents a huge health burden and disease risk. Key to understanding chemical toxicity is knowledge of the molecular target(s) of the chemicals. Because a comprehensive safety assessment for all chemicals is infeasible due to limited resources, a robust computational method for discovering targets of environmental exposures is a promising direction for public health research. In this study, we implemented a novel matrix completion algorithm named coupled matrix-matrix completion (CMMC) for predicting exposome-target interactions, which exploits the vast amount of accumulated data regarding chemical exposures and their molecular targets. Our approach achieved an AUC of 0.89 on a benchmark dataset generated using data from the Comparative Toxicogenomics Database. Our case study with bisphenol A (BPA) and its analogues shows that CMMC can be used to accurately predict molecular targets of novel chemicals without any prior bioactivity knowledge. Overall, our results demonstrate the feasibility and promise of computational predicting environmental chemical-target interactions to efficiently prioritize chemicals for further study.
On the therapeutic potential of MAPK4 in triple-negative breast cancer
Authors: Boudghene-Stambouli Fadia , Soulez Mathilde , Ronkina Natalia , Doerrie Anneke , Kotlyarov Alexey , Seternes Ole-Morten , Gaestel Matthias , Meloche Sylvain
Published: August 2022

ERK3/MAPK6 (MAPK6 gene) along with its paralog ERK4/MAPK4 (MAPK4 gene) define a distinct subfamily of atypical mitogen-activated protein kinases (MAPKs). Much remains to be learned about the substrates and biological functions of these signaling enzymes. Interestingly, recent work has suggested that ERK4 promotes prostate cancer progression via the non-canonical activation of AKT/mTOR signaling. In their recent study, Wang et al. report that ERK4 is expressed in a subset of triple-negative breast cancer (TNBC) cell lines and that this expression is critical for AKT activation and for sustaining TNBC cell proliferation in vitro and tumor growth in mice. They also show that depletion of ERK4 sensitizes TNBC cells to phosphatidylinositol-3-kinase (PI3K) inhibitors. They conclude that ERK4 is a promising therapeutic target for TNBC and has potential for combination therapy with PI3K inhibitors. Here, we raise concerns about the cellular models and experimental approaches used in this study, which compromises the conclusions on the oncogenic role of ERK4 in TNBC.
Patterns and predictors of human-sloth bear conflict in Nepal: Implications for coexistence in unprotected forest landscapes
Authors: Pokharel Manoj , Aryal Chandramani , Adhikary Bidhan , Rai Jeevan
Published: August 2022

Human-sloth bear conflict, generally in the form of human attacks, is common throughout most areas where sloth bears co-occur with humans. The situation is more prevalent in multi-use forest landscapes outside protected areas. Although sloth bears are a conflict-prone species in Nepal, there is a clear lack of systematic studies that can inform human safety and conflict mitigation. We used data from questionnaire-based interviews with conflict-affected people and witnesses to provide detailed information about human-sloth bear conflict (1990– 2021) in the Trijuga forest, an important sloth bear stronghold outside protected areas in Nepal. The data were analyzed using descriptive statistics, chi-square tests, and regression analysis. For the time period, 66 conflict incidents involving 69 human individuals were recorded, with an annual average of 2.06 (SD = 1.48) incidents and 1.75 (SD = 1.34) attacks. Conflicts primarily impacted working-age group (25–55 years old) men, whose primary occupation was farming and who frequented the forest regularly. They typically occurred between 0900 and 1500, inside forests, and in habitats associated with poor land cover visibility. Poor visibility was also a significant positive determinant of bear attacks on humans. Fifty-six conflict incidents resulted in attacks that injured 59 people, with a fatality rate of 8.47%. Victims of bear attacks frequently had serious injuries, especially to the head and neck areas of the body. Serious injuries were more likely to occur to lone individuals than to people who were in groups of two or more. We suggest identification of conflict-risk habitats through a participatory mapping approach and education programs for the local people for effective human-sloth bear conflict management in Nepal’s unprotected forests.
Computational Multiplex Panel Reduction to Maximize Information Retention in Breast Cancer Tissue Microarrays
Authors: Ternes Luke , Gray Joe W. , Chang Young Hwan
Published: August 2022

Recent state-of-the-art multiplex imaging techniques have expanded the depth of information that can be captured within a single tissue sample by allowing for panels with dozens of markers. Despite this increase in capacity, space on the panel is still limited due to technical artifacts, tissue loss, and long imaging acquisition time. As such, selecting which markers to include on a panel is important, since removing important markers will result in a loss of biologically relevant information, but identifying redundant markers will provide a room for other markers. To address this, we propose computational approaches to determine the amount of shared information between markers and select an optimally reduced panel that captures maximum amount of information with the fewest markers. Here we examine several panel selection approaches and evaluate them based on their ability to reconstruct the full panel images and information within breast cancer tissue microarray datasets using cyclic immunofluorescence as a proof of concept. We show that all methods perform adequately and can re-capture cell types using only 18 of 25 markers (72% of the original panel size). The correlation-based selection methods achieved the best single-cell marker mean intensity predictions with a Spearman correlation of 0.90 with the reduced panel. Using the proposed methods shown here, it is possible for researchers to design more efficient multiplex imaging panels that maximize the amount of information retained with the limited number of markers with respect to certain evaluation metrics and architecture biases.

Author Summary

Multiplex tissue imaging techniques utilize large panels of markers that attempt to gather as much information as possible, but increasing the number of stains does come with the downsides of increased autofluorescence and tissue degradation. There exists a theoretical subsampling of markers that is able to recreate the same information as a full panel; therefore, removing the self-correlating information with such a subset would increase the efficiency of the imaging process and maximize the information collected. By selecting an idealized subsample of markers, a deep learning model can be trained to predict the same information as a full dataset with fewer rounds of staining. Here we evaluate several methods of subsample marker selection and demonstrate their ability to reconstruct the full panel’s information.
Lifestyles shape genome size and gene content in fungal pathogens
Authors: Fijarczyk Anna , Hessenauer Pauline , Hamelin Richard C. , Landry Christian R.
Published: August 2022

Fungi display a wide range of lifestyles and hosts. We still know little about the impact of lifestyles, including pathogenicity, on their genome architecture. Here, we combined and annotated 552 fungal genomes from the class Sordariomycetes and examined the association between 12 genomic features and two lifestyle traits: pathogenicity and insect association. We found that pathogens on average tend to have a larger number of protein-coding genes, including effectors, and tRNA genes. In addition, the non-repetitive size of their genomes is larger than that of non-pathogenic species. However, this pattern is not consistent across all groups. Insect endoparasites and symbionts have smaller genome sizes and genes with longer exons; moreover, insect-vectored pathogens possess fewer genes compared to those not transmitted by insects. Our study shows that genes are the main contributors to genome size variation in Sordariomycetes and that seemingly similar pathogens can exhibit distinct genome architectures, depending on their host and vector interactions.
Protein mishandling and impaired lysosomal proteolysis generated through calcium dysregulation in Alzheimer’s disease
Authors: Mustaly-Kalimi Sarah , Marr Robert A. , Gilman-Sachs Alice , Peterson Daniel A. , Sekler Israel , Stutzmann Grace E.
Published: August 2022

Impairments in neural lysosomal- and autophagic-mediated degradation of cellular debris contribute to neuritic dystrophy and synaptic loss. While these are well-characterized features of neurodegenerative disorders such as Alzheimer’s disease (AD), the upstream cellular processes driving deficits in pathogenic protein mishandling are less understood. Using a series of fluorescent biosensors and optical imaging in model cells, AD mouse models and human neurons derived from AD patients, we reveal a novel cellular signaling cascade underlying protein mishandling mediated by intracellular calcium dysregulation, an early component of AD pathogenesis. Increased Ca2+ release via the endoplasmic reticulum (ER) resident ryanodine receptor (RyR) is associated with reduced expression of the lysosome proton pump vATPase subunits (V1B2 and V0a1), resulting in lysosome deacidification and disrupted proteolytic activity in AD mouse models and human induced neurons (HiN). As a result of impaired lysosome digestive capacity, mature autophagosomes with hyperphosphorylated tau accumulated in AD murine neurons and AD HiN, exacerbating proteinopathy. Normalizing AD-associated aberrant RyR-Ca2+ signaling with the negative allosteric modulator, dantrolene (Ryanodex), restored vATPase levels, lysosomal acidification and proteolytic activity, and autophagic clearance of intracellular protein aggregates in AD neurons. These results highlight that prior to overt AD histopathology or cognitive deficits, aberrant upstream Ca2+ signaling disrupts lysosomal acidification and contributes to pathological accumulation of intracellular protein aggregates. Importantly, this is demonstrated in animal models of AD, and in human iPSC-derived neurons from AD patients. Furthermore, pharmacological suppression of RyR-Ca2+ release rescued proteolytic function, revealing a target for therapeutic intervention that has demonstrated effects in clinically-relevant assays.

Significance Statement

We demonstrate in model cells, murine neuronal cultures, and iPSC-derived human neurons, that AD associated RyR-Ca2+ dyshomeostasis impairs lysosomal acidification, lysosomal proteolytic activity and hinders autophagic-mediated protein aggregate clearance, which are processes vital to neuronal survival. These deficits were reversed by restoring intracellular Ca2+ homeostasis. Notably, this provides a therapeutic target and emphasizes the pathogenic relationship between ER-Ca2+ handling, that is known to be altered in AD, to pathogenic protein accumulation as a critical turning point in early stages of Alzheimer’s disease.
Schizophrenia-associatedNRXN1deletions induce developmental-timing- and cell-type-specific vulnerabilities in human brain organoids
Authors: Sebastian Rebecca , Jin Kang , Pavon Narciso , Bansal Ruby , Potter Andrew , Song Yoonjae , Babu Juliana , Gabriel Rafael , Sun Yubing , Aronow Bruce , Pak ChangHui
Published: August 2022

De novomutations and copy number deletions inNRXN1(2p16.3) pose a significant risk for schizophrenia (SCZ). It is unclear howNRXN1deletions impact cortical development in a cell type-specific manner and disease background modulates these phenotypes. Here, we leveraged human pluripotent stem cell-derived forebrain organoid models carryingNRXN1heterozygous deletions in isogenic and SCZ patient genetic backgrounds and conducted single-cell transcriptomic analysis over the course of brain organoid development from 3 weeks to 3.5 months. Intriguingly, while both deletions similarly impacted molecular pathways associated with ubiquitin-proteasome system, alternative splicing, and synaptic signaling in maturing glutamatergic and GABAergic neurons, SCZ-NRXN1deletions specifically perturbed developmental trajectories of early neural progenitors and accumulated disease-specific transcriptomic signatures. Using calcium imaging, we found that both deletions led to long-lasting changes in spontaneous and synchronous neuronal networks, implicating synaptic dysfunction. Our study reveals developmental-timing- and cell-type-dependent actions ofNRXN1deletions in unique genetic contexts.
Impaired intracellular Ca2+signaling contributes to age-related cerebral small vessel disease inCol4a1mutant mice
Authors: Yamasaki Evan , Thakore Pratish , Ali Sher , Solano Alfredo Sanchez , Wang Xiaowei , Gao Xiao , Labelle-Dumais Cassandre , Chaumeil Myriam M. , Gould Douglas B. , Earley Scott
Published: August 2022

Humans and mice with mutations inCOL4A1andCOL4A2manifest hallmarks of cerebral small vessel disease (cSVD), but the pathogenic mechanisms are largely unknown. Mice with a missense mutation inCol4a1at amino acid 1344 (Col4a1+/G1344D) exhibited age-dependent intracerebral hemorrhage (ICH) and brain lesions. Here we report that this pathology was associated with the loss of myogenic vasoconstriction, an intrinsic vascular response essential for the autoregulation of cerebral blood flow. Electrophysiological analyses showed that the loss of myogenic constriction resulted from blunted pressure-induced smooth muscle cell (SMC) membrane depolarization. Further, we found that dysregulation of membrane potential was associated with impaired Ca2+-dependent activation of large-conductance Ca2+-activated K+(BK) and transient receptor potential melastatin 4 (TRPM4) cation channels linked to disruptions in sarcoplasmic reticulum (SR) Ca2+signaling. TreatingCol4a1+/G1344Dmice with 4-phenylbutyrate, a compound that promotes the trafficking of misfolded proteins and alleviates SR stress, restored SR Ca2+signaling, BK and TRPM4 channel activity, prevented loss of myogenic tone, and reduced ICH. We conclude that alterations in SR Ca2+handling that impair membrane potential regulating ion channel activity result in dysregulation of SMC membrane potential and loss of myogenic tone contributing to age-related cSVD inCol4a1+/G1344Dmice.

Graphical Abstract
Detection of Domestication Signals through the Analysis of the Full Distribution of Fitness Effects
Authors: Castellano David , Vourlaki Ioanna-Theoni , Gutenkunst Ryan N. , Ramos-Onsins Sebastian E.
Published: August 2022

Domestication is a process marked by complex interactions between demographic changes and selective pressures, which together shape genetic diversity. While the phenotypic outcomes of domestication are well documented, its genetic basis—particularly the dynamics of selection— remain less well understood. To investigate these dynamics, we performed simulations designed to approximate the demographic history of large domestic mammals. These simulations used selection coefficients as a modeling tool to represent changes in selection pressures, recognizing that such coefficients are abstractions rather than direct representations of biological reality. Specifically, we analyzed site frequency spectra (SFS) under varying distributions of fitness effects (DFE) and proportions of mutations with divergent selective pressures. Our results show that the discretized deleterious DFE can be reliably inferred from the SFS of a single population, but reconstructing the beneficial DFE and demographic history remains challenging, even when using the joint SFS of both populations. We further developed a novel joint DFE inference model to estimate the proportion of mutations with divergent selection coefficients (pc), although we found that signals of classic hard sweeps can mimic increases inpc, complicating interpretation. These findings underscore both the utility and limitations of DFE inference and highlight the need for caution when interpreting demographic histories in domesticated populations based on such modeling assumptions.
Ecdysone acts through cortex glia to regulate sleep in Drosophila
Authors: Li Yongjun , Haynes Paula , Zhang Shirley L. , Yue Zhifeng , Sehgal Amita
Published: August 2022

Steroid hormones are attractive candidates for transmitting long-range signals to affect behavior. These lipid-soluble molecules derived from dietary cholesterol easily penetrate the brain and act through nuclear hormone receptors (NHRs) that function as transcription factors. To determine the extent to which NHRs affect sleep: wake cycles, we knocked down each of the 18 highly conserved NHRs found in Drosophila adults and report that the ecdysone receptor (EcR) and its direct downstream NHR Eip75B (E75) act in glia to regulate the rhythm and amount of sleep. Halloween genes, a set of ecdysone synthesis genes, have little to no expression in the fly brain, while mRNA levels of the ecdysone target E75 cycle in the fly head, suggesting that glial ecdysone comes from the periphery and may enter the brain more at night. Anti-EcR staining localizes to the cortex glia in the brain and functional screening of glial subtypes revealed that EcR functions in adult cortex glia to affect sleep. Cortex glia are implicated in lipid metabolism, which appears to be relevant for actions of ecdysone as ecdysone treatment reduces lipid droplet size in these cells. In addition, sleep-promoting effects of exogenous ecdysone are diminished in Lsd-2 mutant flies, which are lean and deficient in lipid accumulation. We propose that ecdysone is a systemic secreted factor that modulates sleep by stimulating lipid metabolism in cortex glia.

Graphical Abstract

Highlights

Glial knockdown of ecdysone inducible NHRs reduces sleep.

The ecdysone receptor (EcR) and its downstream target E75 function in cortex glia to modulate sleep.

Ecdysone synthesis genes are not expressed in the fly brain, suggesting that glial ecdysone comes from the periphery.

Ecdysone promotes sleep by mobilizing lipid droplets stored mainly in glia.
langevitour: smooth interactive touring of high dimensions, demonstrated with scRNA-Seq data
Authors: Harrison Paul
Published: August 2022

langevitour displays interactive animated 2D projections of high-dimensional datasets. Langevin Dynamics is used to produce a smooth path of projections. Projections are initially explored at random. A “guide” can be activated to look for an informative projection, or variables can be manually positioned. After a projection of particular interest has been found, continuing small motions provide a channel of visual information not present in a static scatter-plot. langevitour is implemented in Javascript, allowing for a high frame rate and responsive interaction, and can be used directly from the R environment or embedded in HTML documents produced using R. The widget is demonstrated using single-cell RNA sequencing (scRNA-Seq) data. langevitour’s linear projections provide a less distorted view of this data than commonly used non-linear dimensionality reductions such as UMAP.
UltraSEQ: a universal bioinformatic platform for information-based clinical metagenomics and beyond
Authors: Gemler Bryan T , Mukherjee Chiranjit , Howland Carrie , Fullerton Patrick A , Spurbeck Rachel R , Catlin Lindsay A , Smith Anthony , Minard-Smith Angela T , Bartling Craig
Published: August 2022

Applied metagenomics is a powerful emerging capability enabling untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of its kind metagenomics-based clinical diagnostics and biosurveillance tool that is accurate and scalable.

Here we present results for evaluation of our novel UltraSEQ pipeline using anin silicosynthesized metagenome, mock microbial community datasets, and publicly available clinical datasets from samples of different infection types, and both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in thein silicosample and detected all 10 bacterial and fungal species in the mock microbial community dataset. For clinical datasets, even without requiring dataset-specific configuration settings changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Further, we demonstrated UltraSEQ’s ability to provide accurate antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results.

Taken together, the above results demonstrates that the UltraSEQ platform offers a transformative approach to microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infection.
The Iron Content of Human Serum Albumin Modulates the Susceptibility of Acinetobacter baumannii to Cefiderocol
Authors: Escalante Jenny , Nishimura Brent , Tuttobene Marisel R. , Subils Tomás , Mezcord Vyanka , Actis Luis A. , Tolmasky Marcelo E. , Bonomo Robert A. , Ramirez María Soledad
Published: August 2022

Mortality rates of patients infected with Acinetobacter baumannii treated with cefiderocol (CFDC) were not as favorable as the best available treatment for pulmonary and bloodstream infections. Previous studies showed that the presence of human serum albumin (HSA) or HSA-containing fluids like human pleural fluid (HPF) or human serum (HS) in the growth medium is correlated with a decrease in the expression of genes associated with high-efficiency iron uptake systems. These observations may explain the less-than-ideal performance of CFDC in pulmonary and bloodstream infections because ferric siderophore transporters enhance penetration of CFDC into the cell’s cytosol. Removal of HSA from HPF or HS resulted in a reduction of the minimal inhibitory concentration of CFDC. Concomitant with these results, there was an enhancement of the expression of genes associated with high-efficiency iron uptake systems. In addition to inducing modifications in iron-uptake gene expression, removal of HSA also decreased the expression of β-lactam resistance genes. Taken together, these observations indicate that environmental HSA has a role in the expression levels of selected A. baumannii. Furthermore, removal of iron from HSA had the same effect as removal of HSA on the expression of genes associated with high-efficiency iron uptake systems, suggesting that at least one of the mechanisms by which HSA regulates the expression of selected genes is through acting as an iron supplier.

IMPORTANCE

Cefiderocol (CFDC) is a new antibiotic that combines its major bactericidal activity, i.e., inhibition of the Gram-negative bacterial cell wall synthesis, with a first in its class mechanism of cell penetration. The siderophore-like moiety facilitates entry through receptors that recognize ferric-siderophore complexes. Recent trials showed that treating pulmonary and bloodstream Acinetobacter baumannii infections with CFDC did not result in the same outcomes as treating other pathogens. Our studies indicated that exposure to human fluids that contain human serum albumin (HSA) increases the MIC values of CFDC. Results described in this work show that HSA is responsible for a reduction in susceptibility of A. baumannii to CFDC. Furthermore, the presence of HSA in the milieu produces a reduction in levels of expression of proteins associated with high-affinity iron uptake systems and enhanced expression of β-lactam resistance-associated genes. Deferration of HSA was accompanied by a loss of the ability to modify these genes’ expression levels. These results indicate that the microbiological activity of CFDC towards A. baumannii is attenuated in the presence of HSA-containing fluids. This unique insight opens up new avenues of investigation. Understanding this phenomenon’s molecular mechanism will help define methodologies to increase treatment efficiency.
Use of whole genome sequencing to estimate the contribution of immune evasion and waning immunity to decreasing COVID-19 vaccine effectiveness during alpha and delta variant waves
Authors: Lind Margaret L , Copin Richard , McCarthy Shane , Coppi Andreas , Warner Fred , Ferguson David , Duckwall Chelsea , Borg Ryan , Muenker M Catherine , Overton John , Hamon Sara , Zhou Anbo , Cummings Derek AT , Ko Albert I. , Hamilton Jennifer D , Schulz Wade , Hitchings Matt T.
Published: August 2022

Background

The decline in COVID-19 mRNA vaccine effectiveness (VE) is well established, however the impact of variant-specific immune evasion and waning protection remains unclear. Here, we use whole-genome-sequencing (WGS) to tease apart the contribution of these factors on the decline observed following the introduction of the Delta variant. Further, we evaluate the utility of calendar-period-based variant classification as an alternative to WGS.

Methods

We conducted a test-negative-case-control study among people who received SARS-CoV-2 RT-PCR testing in the Yale New Haven Health System between April 1 and August 24, 2021. Variant classification was performed using WGS and secondarily by calendar-period. We estimated VE as one minus the ratio comparing the odds of infection among vaccinated and unvaccinated people.

Results

Overall, 2,029 cases (RT-PCR positive, sequenced samples) and 343,985 controls (negative RT-PCRs) were included. VE 14-89 days after 2nd dose was significantly higher against WGS-classified Alpha infection (84.4%, 95% confidence interval: 75.6-90.0%) than Delta infection (68.9%, CI: 58.0-77.1%, p-value: 0.013). The odds of WGS-classified Delta infection were significantly higher 90-149 than 14-89 days after 2nd dose (Odds ratio: 1.6, CI: 1.2-2.3). While estimates of VE against calendar-period-classified infections approximated estimates against WGS-classified infections, calendar-period-based classification was subject to outcome misclassification (35% during Alpha period, 4% during Delta period).

Conclusions

These findings suggest that both waning protection and variant-specific immune evasion contributed to the lower effectiveness. While estimates of VE against calendar-period-classified infections mirrored that against WGS-classified infections, our analysis highlights the need for WGS when variants are co-circulating and misclassification is likely.

Summary of main points

Using whole genome sequencing, we provide direct evidence of waning vaccine effectiveness and variant-specific immune evasion during the Delta wave. Effectiveness estimates against calendar-period-classified infections approximated estimates against WGS-classified infections, however, calendar-period classification was associated with a variant misclassification.