bluuebunny/crossref_metadata_2025 huggingface dataset:
A latent clinical-anatomical dimension relating metabolic syndrome to brain structure and cognition
Authors: Petersen Marvin , Hoffstaedter Felix , Nägele Felix L. , Mayer Carola , Schell Maximilian , Rimmele D. Leander , Zyriax Birgit-Christiane , Zeller Tanja , Kühn Simone , Gallinat Jürgen , Fiehler Jens , Twerenbold Raphael , Omidvarnia Amir , Patil Kaustubh R. , Eickhoff Simon B. , Thomalla Götz , Cheng Bastian
Published: February 2023

The link between metabolic syndrome (MetS) and neurodegenerative as well cerebrovascular conditions holds substantial implications for brain health in at-risk populations. This study elucidates the complex relationship between MetS and brain health by conducting a comprehensive examination of cardiometabolic risk factors, cortical morphology, and cognitive function in 40,087 individuals. Multivariate, data-driven statistics identified a latent dimension linking more severe MetS to widespread brain morphological abnormalities, accounting for up to 71% of shared variance in the data. This dimension was replicable across sub-samples. In a mediation analysis we could demonstrate that MetS-related brain morphological abnormalities mediated the link between MetS severity and cognitive performance in multiple domains. Employing imaging transcriptomics and connectomics, our results also suggest that MetS-related morphological abnormalities are linked to the regional cellular composition and macroscopic brain network organization. By leveraging extensive, multi-domain data combined with a dimensional stratification approach, our analysis provides profound insights into the association of MetS and brain health. These findings can inform effective therapeutic and risk mitigation strategies aimed at maintaining brain integrity.
A Systematic Review and Large-Scale tES and TMS Electric Field Modeling Study Reveals How Outcome Measure Selection Alters Results in a Person- and Montage-Specific Manner
Authors: Van Hoornweder Sybren , Nuyts Marten , Frieske Joana , Verstraelen Stefanie , Meesen Raf L.J. , Caulfield Kevin A.
Published: February 2023

Background

Electric field (E-field) modeling is a potent tool to examine the cortical effects of transcranial magnetic and electrical stimulation (TMS and tES, respectively) and to address the high variability in efficacy observed in the literature. However, outcome measures used to report E-field magnitude vary considerably and have not yet been compared in detail.

Objectives

The goal of this two-part study, encompassing a systematic review and modeling experiment, was to provide an overview of the different outcome measures used to report the magnitude of tES and TMS E-fields, and to conduct a direct comparison of these measures across different stimulation montages.

Methods

Three electronic databases were searched for tES and/or TMS studies reporting E-field magnitude. We extracted and discussed outcome measures in studies meeting the inclusion criteria. Additionally, outcome measures were compared via models of four common tES and two TMS modalities in 100 healthy younger adults.

Results

In the systematic review, we included 118 studies using 151 outcome measures related to E-field magnitude. Structural and spherical regions of interest (ROI) analyses and percentile-based whole-brain analyses were used most often. In the modeling analyses, we found that there was an average of only 6% overlap between ROI and percentile-based whole-brain analyses in the investigated volumes within the same person. The overlap between ROI and whole-brain percentiles was montage- and person-specific, with more focal montages such as 4×1 and APPS-tES, and figure-of-eight TMS showing up to 73%, 60%, and 52% overlap between ROI and percentile approaches respectively. However, even in these cases, 27% or more of the analyzed volume still differed between outcome measures in every analyses.

Conclusions

The choice of outcome measures meaningfully alters the interpretation of tES and TMS E-field models. Well-considered outcome measure selection is imperative for accurate interpretation of results, valid between-study comparisons, and depends on stimulation focality and study goals. We formulated four recommendations to increase the quality and rigor of E-field modeling outcome measures. With these data and recommendations, we hope to guide future studies towards informed outcome measure selection, and improve the comparability of studies.
In-silico testing of new pharmacology for restoring inhibition and human cortical function in depression
Authors: Guet-McCreight Alexandre , Chameh Homeira Moradi , Mazza Frank , Prevot Thomas D. , Valiante Taufik A. , Sibille Etienne , Hay Etay
Published: February 2023

Reduced inhibition by somatostatin-expressing interneurons is associated with depression. Administration of positive allosteric modulators of α5 subunit-containing GABAAreceptor (α5-PAM) that selectively target this lost inhibition exhibit antidepressant and pro-cognitive effects in rodent models of chronic stress. However, the functional effects of α5-PAM on the human brainin vivoare unknown, and currently cannot be assessed experimentally. We modeled the effects of α5-PAM on tonic inhibition as measured in human neurons, and testedin silicoα5-PAM effects on detailed models of human cortical microcircuits in health and depression. We found that α5-PAM effectively recovered impaired cortical processing as quantified by stimulus detection metrics, and also recovered the power spectral density profile of the microcircuit EEG signals. We performed an α5-PAM dose response and identified simulated EEG biomarker candidates. Our results serve to de-risk and facilitate α5-PAM translation and provide biomarkers in non-invasive brain signals for monitoring target engagement and drug efficacy.
Concerning the eXclusion in human genomics: The choice of sex chromosome representation in the human genome drastically affects number of identified variants
Authors: Pinto Brendan J. , O’Connor Brian , Schatz Michael C. , Zarate Samantha , Wilson Melissa A.
Published: February 2023

Over the past 30 years, a community of scientists have pieced together every base pair of the human reference genome from telomere-to-telomere. Interestingly, most human genomics studies omit more than 5% of the genome from their analyses. Under ‘normal’ circumstances, omitting any chromosome(s) from analysis of the human genome would be reason for concern—the exception being the sex chromosomes. Sex chromosomes in eutherians share an evolutionary origin as an ancestral pair of autosomes. In humans, they share three regions of high sequence identity (~98-100%), which—along with the unique transmission patterns of the sex chromosomes—introduce technical artifacts into genomic analyses. However, the human X chromosome bears numerous important genes—including more “immune response” genes than any other chromosome—which makes its exclusion irresponsible when sex differences across human diseases are widespread. To better characterize the effect that including/excluding the X chromosome may have on variants called, we conducted a pilot study on the Terra cloud platform to replicate a subset of standard genomic practices using both the CHM13 reference genome and sex chromosome complement-aware (SCC-aware) reference genome. We compared quality of variant calling, expression quantification, and allele-specific expression using these two reference genome versions across 50 human samples from the Genotype-Tissue-Expression consortium annotated as females. We found that after correction, the whole X chromosome (100%) can generate reliable variant calls—allowing for the inclusion of the whole genome in human genomics analyses as a departure from the status quo of omitting the sex chromosomes from empirical and clinical genomics studies.
Arf6 Regulates Endocytosis and Angiogenesis by Promoting Filamentous Actin Assembly
Authors: Francis Caitlin R. , Bell Makenzie L. , Skripnichuk Marina M. , Kushner Erich J.
Published: February 2023

Clathrin-mediated endocytosis (CME) is a process vital to angiogenesis as well as general vascular homeostasis. In pathologies where supraphysiological growth factor signaling underlies disease etiology, such as in diabetic retinopathy and solid tumors, strategies to limit chronic growth factor signaling by way of CME have been shown to have tremendous clinical value. ADP ribosylation factor 6 (Arf6) is a small GTPase that promotes the assembly of actin necessary for CME. In its absence, growth factor signaling is greatly diminished, which has been shown to ameliorate pathological signaling input in diseased vasculature. However, it is less clear if there are bystander effects related to loss of Arf6 on angiogenic behaviors. Our goal was to provide a analysis of Arf6’s function in angiogenic endothelium, focusing on its role in lumenogenesis as well as its relation to actin and CME. We found that Arf6 localized to both filamentous actin and sites of CME in 2-dimensional culture. Loss of Arf6 distorted both apicobasal polarity and reduced the total cellular filamentous actin content, and this may be the primary driver underlying gross dysmorphogenesis during angiogenic sprouting in its absence. Our findings highlight that endothelial Arf6 is a potent mediator of both actin regulation and CME.
The Boltzmann distributions of folded molecular structures predict likely changes through random mutations
Authors: Martin Nora S. , Ahnert Sebastian E.
Published: February 2023

New folded molecular structures can only evolve after arising through mutations. This aspect is modelled using genotype-phenotype (GP) maps, which connect sequence changes through mutations to changes in molecular structures. Previous work has shown that the likelihood of appearing through mutations can differ by orders of magnitude from structure to structure and that this can affect the outcomes of evolutionary processes. Thus, we focus on the phenotypic mutation probabilitiesϕqp, i.e. the likelihood that a random mutation changes structurepinto structureq. For both RNA secondary structures and the HP protein model, we show that a simple biophysical principle can explain and predict how this likelihood depends on the new structureq:ϕqpis high if sequences that fold intopas the minimum-free-energy structure are likely to haveqas an alternative structure with high Boltzmann frequency. This generalises the existing concept of plastogenetic congruence from individual sequences to the entire neutral spaces of structures. Our result helps us understand why some structural changes are more likely than others, can be used as a basis for estimating these likelihoods via sampling and makes a connection to alternative structures with high Boltzmann frequency, which could be relevant in evolutionary processes.
Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging
Authors: Radhakrishnan Hamsanandini , Zhao Chenying , Sydnor Valerie J. , Baller Erica B. , Cook Philip A. , Fair Damien , Giesbrecht Barry , Larsen Bart , Murtha Kristin , Roalf David R. , Rush-Goebel Sage , Shinohara Russell , Shou Haochang , Tisdall M. Dylan , Vettel Jean , Grafton Scott , Cieslak Matthew , Satterthwaite Theodore
Published: February 2023

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling ofq-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling ofq-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of twenty-six participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n=20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineatingin vivowhite matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.
cGLRs are a diverse family of pattern recognition receptors in animal innate immunity
Authors: Li Yao , Slavik Kailey M. , Morehouse Benjamin R. , de Oliveira Mann Carina C. , Mears Kepler , Liu Jingjing , Kashin Dmitry , Schwede Frank , Kranzusch Philip J.
Published: February 2023

cGAS (cyclic GMP-AMP synthase) is an enzyme in human cells that controls an immune response to cytosolic DNA. Upon binding DNA, cGAS synthesizes a nucleotide signal 2′3′-cGAMP that activates the protein STING and downstream immunity. Here we discover cGAS-like receptors (cGLRs) constitute a major family of pattern recognition receptors in animal innate immunity. Building on recent analysis inDrosophila, we use a bioinformatic approach to identify >3,000 cGLRs present in nearly all metazoan phyla. A forward biochemical screen of 140 animal cGLRs reveals a conserved mechanism of signaling including response to dsDNA and dsRNA ligands and synthesis of alternative nucleotide signals including isomers of cGAMP and cUMP-AMP. Using structural biology, we explain how synthesis of distinct nucleotide signals enables cells to control discrete cGLR-STING signaling pathways. Together our results reveal cGLRs as a widespread family of pattern recognition receptors and establish molecular rules that govern nucleotide signaling in animal immunity.
FRET assay for live-cell high-throughput screening of the cardiac SERCA pump yields multiple classes of small-molecule allosteric modulators
Authors: Roopnarine Osha , Yuen Samantha L. , Thompson Andrew R. , Roelike Lauren N. , Rebbeck Robyn T. , Bidwell Philip A. , Aldrich Courtney C. , Cornea Razvan L. , Thomas David D.
Published: February 2023

We have used FRET-based biosensors in live cells, in a robust high-throughput screening (HTS) platform, to identify small-molecules that alter the structure and activity of the cardiac sarco/endoplasmic reticulum calcium ATPase (SERCA2a). Our primary aim is to discover drug-like small-molecule activators that improve SERCA’s function for the treatment of heart failure. We have previously demonstrated the use of an intramolecular FRET biosensor, based on human SERCA2a, by screening a small validation library using novel microplate readers that can detect the fluorescence lifetime or emission spectrum with high speed, precision, and resolution. Here we report results from a 50,000-compound screen using the same biosensor, with hit compounds functionally evaluated using Ca2+-ATPase and Ca2+-transport assays. We focused on 18 hit compounds, from which we identified eight structurally unique compounds and four compound classes as SERCA modulators, approximately half of which are activators and half are inhibitors. While both activators and inhibitors have therapeutic potential, the activators establish the basis for future testing in heart disease models and lead development, toward pharmaceutical therapy for heart failure.
SPA-STOCSY: An Automated Tool for Identification of Annotated and Non-Annotated Metabolites in High-Throughput NMR Spectra
Authors: Han Xu , Wang Wanli , Ma Li-Hua , Al-Ramahi Ismael , Botas Juan , MacKenzie Kevin , Allen Genevera I. , Young Damian W. , Liu Zhandong , Maletic-Savatic Mirjana
Published: February 2023

Nuclear Magnetic Resonance (NMR) spectroscopy is widely used to analyze metabolites in biological samples, but the analysis can be cumbersome and inaccurate. Here, we present a powerful automated tool, SPA-STOCSY (Spatial Clustering Algorithm - Statistical Total Correlation Spectroscopy), which overcomes the challenges by identifying metabolites in each sample with high accuracy. As a data-driven method, SPA-STOCSY estimates all parameters from the input dataset, first investigating the covariance pattern and then calculating the optimal threshold with which to cluster data points belonging to the same structural unit, i.e. metabolite. The generated clusters are then automatically linked to a compound library to identify candidates. To assess SPA-STOCSY’s efficiency and accuracy, we applied it to synthesized and real NMR data obtained fromDrosophila melanogasterbrains and human embryonic stem cells. In the synthesized spectra, SPA outperforms Statistical Recoupling of Variables, an existing method for clustering spectral peaks, by capturing a higher percentage of the signal regions and the close-to-zero noise regions. In the real spectra, SPA-STOCSY performs comparably to operator-based Chenomx analysis but avoids operator bias and performs the analyses in less than seven minutes of total computation time. Overall, SPA-STOCSY is a fast, accurate, and unbiased tool for untargeted analysis of metabolites in the NMR spectra. As such, it might accelerate the utilization of NMR for scientific discoveries, medical diagnostics, and patient-specific decision making.
Matching Variants for functional characterization of genetic variants
Authors: Cevik Sebiha , Zhao Pei , Zorluer Atiyye , Bian Wenyin , Kaplan Oktay I.
Published: February 2023

Rapid and low-cost sequencing, as well as computer analysis, have facilitated the diagnosis of many genetic diseases, resulting in a substantial rise in the number of disease-associated genes. However, genetic diagnosis of many disorders remains problematic due to the lack of interpretation for many genetic variants, especially missenses, the infeasibility of high-throughput experiments on mammals, and the shortcomings of computational prediction technologies. Additionally, the available mutant databases are not well-utilized. Toward this end, we usedCaenorhabditis elegansmutant resources to delineate the functions of eight missense variants (V444I, V517D, E610K, L732F, E817K, H873P, R1105K, and G1205E) and two stop codons (W937stop and Q1434stop), including several matching variants (MatchVar) with human in ciliopathy associated IFT-140 (also called CHE-11)//IFT140 (intraflagellar transport protein 140). Moreover, MatchVars carryingC. elegansmutants, including IFT-140(G680S) and IFT-140(P702A) for the human (G704S) (dbSNP: rs150745099) and P726A (dbSNP: rs1057518064 and a conflicting variation) were created using CRISPR/Cas9. IFT140 is a key component of IFT complex A (IFT-A), which is involved in the retrograde transport of IFT along cilia and the entrance of G protein-coupled receptors (GPCRs) into cilia. Functional analysis of all ten variants revealed that P702A and W937stop, but not others phenocopied the ciliary phenotypes (short cilia, IFT accumulations, mislocalization of membrane proteins, and cilia entry of non-ciliary proteins) of the IFT-140 null mutant, indicating that both P702A and W937stop are phenotypic inC. elegans. Our functional data offered experimental support for interpreting human variants, by using ready-to-use mutants carrying MatchVars and generating MatchVars with CRISPR/Cas9.
Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens
Authors: Hassan Arshia Zernab , Ward Henry N. , Rahman Mahfuzur , Billmann Maximilian , Lee Yoonkyu , Myers Chad L.
Published: February 2023

CRISPR-Cas9 screens facilitate the discovery of gene functional relationships and phenotype-specific dependencies. The Cancer Dependency Map (DepMap) is the largest compendium of whole-genome CRISPR screens aimed at identifying cancer-specific genetic dependencies across human cell lines. A mitochondria-associated bias has been previously reported to mask signals for genes involved in other functions, and thus, methods for normalizing this dominant signal to improve co-essentiality networks are of interest. In this study, we explore three unsupervised dimensionality reduction methods - autoencoders, robust, and classical principal component analyses (PCA) - for normalizing the DepMap to improve functional networks extracted from these data. We propose a novel “onion” normalization technique to combine several normalized data layers into a single network. Benchmarking analyses reveal that robust PCA combined with onion normalization outperforms existing methods for normalizing the DepMap. Our work demonstrates the value of removing low-dimensional signals from the DepMap before constructing functional gene networks and provides generalizable dimensionality reduction-based normalization tools.
DOCK3 regulates normal skeletal muscle regeneration and glucose metabolism
Authors: Samani Adrienne , Karuppasamy Muthukumar , English Katherine G. , Siler Colin A. , Wang Yimin , Widrick Jeffrey J. , Alexander Matthew S.
Published: February 2023

DOCK (dedicator of cytokinesis) is an 11-member family of typical guanine nucleotide exchange factors (GEFs) expressed in the brain, spinal cord, and skeletal muscle. Several DOCK proteins have been implicated in maintaining several myogenic processes such as fusion. We previously identified DOCK3 as being strongly upregulated in Duchenne muscular dystrophy (DMD), specifically in the skeletal muscles of DMD patients and dystrophic mice.Dock3ubiquitous KO mice on the dystrophin-deficient background exacerbated skeletal muscle and cardiac phenotypes. We generatedDock3conditional skeletal muscle knockout mice (Dock3mKO) to characterize the role of DOCK3 protein exclusively in the adult muscle lineage.Dock3mKO mice presented with significant hyperglycemia and increased fat mass, indicating a metabolic role in the maintenance of skeletal muscle health.Dock3mKO mice had impaired muscle architecture, reduced locomotor activity, impaired myofiber regeneration, and metabolic dysfunction. We identified a novel DOCK3 interaction with SORBS1 through the C-terminal domain of DOCK3 that may account for its metabolic dysregulation. Together, these findings demonstrate an essential role for DOCK3 in skeletal muscle independent of DOCK3 function in neuronal lineages.
Neutrophil-specific STAT4 deficiency attenuates atherosclerotic burden and improves plaque stability via reduction in neutrophil activation and recruitment into aortas ofLdlr-/-mice
Authors: Keeter W. Coles , Moriarty Alina K , Akers Rachel , Ma Shelby , Mussbacher Marion , Nadler Jerry L. , Galkina Elena V.
Published: February 2023

Background and Aims

Neutrophils drive atheroprogression and directly contribute to plaque instability. We recently identified signal transducer and activator of transcription 4 (STAT4) as a critical component for bacterial host defense in neutrophils. The STAT4-dependent functions of neutrophils in atherogenesis are unknown. Therefore, we investigated a contributory role of STAT4 in neutrophils during advanced atherosclerosis.

Methods

We generated myeloid-specificStat4ΔLysMLdlr-/-, neutrophil-specificStat4ΔS100A8Ldlr-/-, and controlStat4fl/flLdlr-/-mice. All groups were fed a high-fat/cholesterol diet (HFD-C) for 28 weeks to establish advanced atherosclerosis. Aortic root plaque burden and stability were assessed histologically by Movat Pentachrome staining. Nanostring gene expression analysis was performed on isolated blood neutrophils. Flow cytometry was utilized to analyze hematopoiesis and blood neutrophil activation.In vivohoming of neutrophils to atherosclerotic plaques was performed by adoptively transferring prelabeledStat4ΔLysMLdlr-/-andStat4fl/flLdlr-/-bone marrow cells into aged atheroscleroticApoe-/-mice and detected by flow cytometry.

Results

STAT4 deficiency in both myeloid-specific and neutrophil-specific mice provided similar reductions in aortic root plaque burden and improvements in plaque stability via reduction in necrotic core size, improved fibrous cap area, and increased vascular smooth muscle cell content within the fibrous cap. Myeloid-specific STAT4 deficiency resulted in decreased circulating neutrophils via reduced production of granulocyte-monocyte progenitors in the bone marrow. Neutrophil activation was dampened inStat4ΔLysMLdlr-/-mice via reduced mitochondrial superoxide production, attenuated surface expression of degranulation marker CD63, and reduced frequency of neutrophil-platelet aggregates. Myeloid-specific STAT4 deficiency diminished expression of chemokine receptors CCR1 and CCR2 and impairedin vivoneutrophil trafficking to atherosclerotic aorta.

Conclusions

Our work indicates a pro-atherogenic role for STAT4-dependent neutrophil activation and how it contributes to multiple factors of plaque instability during advanced atherosclerosis in mice.
Machine-learning and mechanistic modeling of primary and metastatic breast cancer growth after neoadjuvant targeted therapy
Authors: Benzekry S. , Mastri M. , Nicolò C. , Ebos J. ML
Published: February 2023

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors prior to surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet such trials are rarely preceded by preclinical testing involving surgery. Here we used a mouse model of spontaneous metastasis after surgical removal to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Longitudinal data consisted of measurements of presurgical primary tumor size and postsurgical metastatic burden in 128 mice (104 for model training, 24 for validation), following variable neoadjuvant treatment schedules over a 14-day period. A nonlinear mixed-effects modeling approach was used to quantify inter-animal variability. Machine learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (CD31 and Ki67). Our simulations showed that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery. Surprisingly, machine-learning algorithms demonstrated only limited predictive power of tested biomarkers on the mathematical parameters. These results suggest that presurgical modeling might be an effective tool to screen biomarkers prior to clinical trial testing. Mathematical modeling combined with artificial intelligence techniques represent a novel platform for integrating preclinical surgical metastasis models in outcome prediction of neoadjuvant treatment.

Major findings

Using simulations from a mechanistic mathematical model compared with preclinical data from surgical metastasis models, we found anti-tumor effects of neoadjuvant RTKI treatment can differ between the primary tumor and metastases in the perioperative setting. Model simulations with variable drug doses and scheduling of neoadjuvant treatment revealed a contrasting impact on initial primary tumor debulking and metastatic outcomes long after treatment has stopped and tumor surgically removed. Using machine-learning algorithms, we identified the limited power of several circulating cellular and molecular biomarkers in predicting metastatic outcome, uncovering a potential fast-track strategy for assessing future clinical biomarkers by paring patient studies with identical studies in mice.
The cryptic step in biogeochemical Tellurium (Te) cycle: Indirect elementary Te oxidation mediated by manganese-oxidizing bacterium (MnOB)
Authors: Liu Yuqing , Ma Huiqing , Li Ang , Yi Xianliang , Liu Yang , Zhan Jingjing , Zhou Hao
Published: February 2023

Tellurium (Te) is a rare element in the chalcogen group, and its biogeochemical cycle has been investigated for decades. As the most soluble Te species, tellurite (Te(IV)) possess the highest toxicity to the organisms. Chemical or biological Te(IV) reduction to elemental tellurium (Te0) is generally considered as an effective detoxification route for Te(IV)-containing wastewater. Here, we reported a previously overlooked Te0oxidation process mediated by manganese-oxidizing bacteriumBacillussp. FF-1. This strain has both Mn(II)-oxidizing and Te(IV)-reducing activities, which could produce manganese oxides (BioMnOx) and Te0(BioTe0) when incubating with Mn(II) and Te(IV), respectively. Te(IV) can co-precipitated with Mn(II) to form highly stable Te(IV)-Mn(II) compounds with low bioavailability. While when 5 mM Mn(II) was added after incubating 0.1 mM or 1 mM Te(IV) with strain FF-1 for 16 hours, the BioTe0were certainly re-oxidized to Te(IV) by BioMnOx according to the results of X-ray photoelectron spectra (XPS) and Transmission electron microscope (TEM). The chemogenic and exogenous biogenic Te0can also be oxidized by the BioMnOx, although with different rates. This study highlights a new transformation process of tellurium species mediated by manganese-oxidizing bacteria, revealing that the environmental fate and ecological risks of Te0needed to be re-evaluated.

Importance

Biogeochemical cycle of Te mediated by bacteria mainly focus on the Tellurite reduction and methylation. In this study, the indirect tellurium (Te0) oxidation driven by manganese-oxidizing bacterium is firstly confirmed. As Te0 usually considered as a stable and safe products during Te(IV)-containing wastewater treatment, we suppose the ecological risks of Te0needed to be re-evaluated due to the possible oxidation by manganese-oxidizing bacterium and its generated manganese oxides.
Ensemble deep learning of embeddings for clustering multimodal single-cell omics data
Authors: Yu Lijia , Liu Chunlei , Yang Jean Yee Hwa , Yang Pengyi
Published: February 2023

Motivation

Recent advances in multimodal single-cell omics technologies enable multiple modalities of molecular attributes, such as gene expression, chromatin accessibility, and protein abundance, to be profiled simultaneously at a global level in individual cells. While the increasing availability of multiple data modalities is expected to provide a more accurate clustering and characterisation of cells, the development of computational methods that are capable of extracting information embedded across data modalities is still in its infancy.

Results

We propose SnapCCESS for clustering cells by integrating data modalities in multimodal singlecell omics data using an unsupervised ensemble deep learning framework. By creating snapshots of embeddings of multimodality using variational autoencoders, SnapCCESS can be coupled with various clustering algorithms for generating consensus clustering of cells. We applied SnapCCESS with several clustering algorithms to various datasets generated from popular multimodal single-cell omics technologies. Our results demonstrate that SnapCCESS is effective and more efficient than conventional ensemble deep learning-based clustering methods and outperforms other state-of-the-art multimodal embedding generation methods in integrating data modalities for clustering cells. The improved clustering of cells from SnapCCESS will pave the way for more accurate characterisation of cell identity and types, an essential step for various downstream analyses of multimodal single-cell omics data.

Availability and implementation

SnapCCESS is implemented as a Python package and is freely available fromhttps://github.com/yulijia/SnapCCESS.
Biological Age Estimation Using Circulating Blood Biomarkers
Authors: Bortz Jordan , Guariglia Andrea , Klaric Lucija , Tang David , Ward Peter , Geer Michael , Chadeau-Hyam Marc , Vuckovic Dragana , Joshi Peter K
Published: February 2023

Biological Age (BA) captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for BA estimation. This study aims to improve BA estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (UKBB) (n = 307,000). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk, which outperforms the well-known blood-biomarker based PhenoAge model, providing a 9.2% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. BA is estimated as the equivalent age within the same-sex population which corresponds to an individual’s mortality risk. Values ranged between 20-years younger and 20-years older than individuals’ chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of BA, available to the general population.
Cannabis use and atherosclerotic cardiovascular disease: a Mendelian randomization study
Authors: de La Harpe Roxane , Schoeler Tabea , Thorball Christian W , Thomas Aurélien , Kutalik Zoltán , Vaucher Julien
Published: February 2023

Background

Research on the link between cannabis use and the development of atherosclerotic cardiovascular disease (ASCVD) is inconsistent and challenging to interpret, given existing study limitations.

Aims

To estimate the effects of genetically indexed cannabis use on the risk of coronary artery disease (CAD) and acute ischemic stroke (IS).

Methods

65 independent single-nucleotide polymorphisms (SNPs), obtained from a genome-wide association study on lifetime cannabis use (n=184,765), were employed as instruments to estimate the association between genetically indexed cannabis use and risk of CAD and IS using a two-sample Mendelian Randomization (MR) approach. Summary statistics on CAD (CARDIoGRAMplusC4D Consortium; 60,801 cases and 123,504 controls) and IS (MEGASTROKE; 34,217 cases and 406,111 controls) were obtained separately. A comprehensive review of the observational literature on cannabis use and CAD or IS was also performed and contrasted with MR results.

Results

There was no causal effect of cannabis use on the risk of CAD (odds ratio (OR) per ever-users vs. never-users 0.93; 95% confidence interval (CI), 0.83 to 1.03) or IS (OR 1.05; 95%CI, 0.93 to 1.19). Sensitivity analyses yielded similar results, and no heterogeneity and directional pleiotropy were observed. Our meta-analysis of observational studies showed no significant association between ever use of cannabis with risk of CAD (k=6 studies; ORpooled=1.23, 95% CI 0.78 to 1.69), nor with IS (k=6 studies; ORpooled=1.22, 95% CI 0.95 to 1.50).

Conclusion

Using a genetic approach approximating a clinical trial revealed no evidence for a causal effect of genetic predisposition to cannabis use on CAD or IS development. These findings are reassuring from a public health perspective, as ever cannabis use is unlikely to contribute to the risk of ASCVD.
Spatial transcriptomics maps molecular and cellular requirements for CD4+T cell-dependent immunity to malaria
Authors: Williams Cameron G. , Moreira Marcela L. , Asatsuma Takahiro , Skinner Oliver P. , Lee Hyun Jae , Li Shihan , Barrera Irving , Murray Evan , Soon Megan S. F. , Engel Jessica A. , Khoury David S. , Asad Saba , Steiner Thiago Mass , Joseph Rainon , Alexandre Yannick , Mueller Scott N. , Chen Fei , Haque Ashraful
Published: February 2023

CD4+T cells orchestrate adaptive immunity to circulating malaria parasites; yet cellular interactions and molecular mechanisms controlling Th1 and Tfh differentiation in the spleen remain to be fully definedin vivo. Here, using a murine model of CD4-dependent immunity, we tested ifSlide-seqV2, a spatial transcriptomic method with near single-cell resolution, could determine the locations of multiple CD4+T cell subsets and potentially interacting cellular partners in the spleen during infection. Firstly,Slide-seqV2readily mapped splenic cellular structure and microanatomical change during infection. Next, computational integration with scRNA-seq reference datasets of splenocytes, stromal cells, and specifically of polyclonal CD4+T cells and B cells, mapped the relative locations of multiple cell-types within this dense tissue. scRNA-seq of B cells over time mapped emergence of germinal centre B cells, red pulp-located plasmablasts and atypical B cells, and uncovered a prolonged CD4+T-cell-independent, follicular bystander B cell response marked by Sca-1 and Ly6C upregulation. scRNA-seq of activated, polyclonal CD4+T cells revealed their similarity to our previous TCR transgenic models. Importantly, spatial analysis revealed polyclonal Th1 cells co-localised with CXCL9/10-producing monocytes in the red pulp, while polyclonal Tfh-like cells were located close to CXCL13-expressing B cell follicles, consistent with our previous CXCR3/CXCR5 competition model of Th1/Tfh bifurcation. CRISPR/Cas9 disruption of either or both CXCR3 and CXCR5 in naïvePlasmodium-specific CD4+T cells had unexpectedly minor effects on Th1 differentiationin vivo. Instead, CXCR5 was essential for maximising clonal expansion, suggesting a role for splenic CXCL13+cells in supporting CD4+T cell proliferation in malaria. Thus, spatial transcriptomics at near single-cell resolution was feasible in densely packed secondary lymphoid tissue, providing multiple insights into mechanisms controlling splenic polyclonal CD4+T cell and B cell differentiation during infection.

Highlights

Slide-seqV2maps splenic microanatomy, including stromal and immune cell location.

Bystander activation of all follicular B cells occurs in malaria, marked by Sca-1/Ly6C upregulation.

Single naïve polyclonal CD4+T cells differentiate mostly into Th1 and Tfh cells in malaria.

Cell-cell colocalization analysis positions Th1 cells with monocytes in red pulp, and Tfh cells withCxcl13+B cell follicles.

CXCR5, but not CXCR3, supports parasite-specific CD4+T cell clonal expansion.
Analysis of the SARS-CoV-2 spike protein revealed that blocked receptor-binding domain antigenicity decreases the production of neutralizing antibodies in vivo
Authors: Mei Ya-Fang , Zhang Qian , Hammond Maria , Song Jie , Fang Zongwei , Zhao Hongxing , Landgren Marene
Published: February 2023

The identification of SARS-CoV-2 spike protein distribution and function in target cells has raised concerns about its possible impacts on vaccine efficacy and pathogenic effect in host cells. Thus, a better understanding of such consequences is necessary. In this study, we studied the biological characteristics of six variants of SARS-CoV-2 in A549 and HEK293 cells using four different technologies. The results showed that compared to the other fragments, the full-length spike protein exhibited the highest expression on the cell surface and was detectable in the cell supernatant, cytoplasm, and nucleus. Except for the cell surface, the S1 subunit generally expressed higher than the full-length spike protein. RBD and S2 subunits were expressed in the cytoskeleton. The SS-RBD peptide, which consists of a 19-amino acid signal peptide sequence (SS)-linked RBD, exhibited the highest expression in the cell supernatant among all other studied peptides. The SS positively enhanced the expression, migration, and secretion of SS-RBD from the cytoskeleton to the supernatant. Importantly, the FACS assay results showed that neutralizing antibodies (NAbs) could recognize SS-RBD but not RBD in the transfected cells, suggesting that RBD was tightly bound by ACE2 in HEK293 cells. In contrast, the antigenicity of the RBD in the spike protein was revealed and efficiently monitored only by 6-His-tag mAbs. Thus, our findings demonstrated that ACE2 blocks crucial immunogenic epitopes of the RBD, and the full-length spike protein mainly induces non-neutralizing antibodies in vivo. Therefore, we suggest that reducing ACE2 binding affinity and exposing the immunogenicity of the RBD on the spike protein is imperative for improving vaccine efficacy and generating new SARS-CoV-2 mRNA vaccines.
Comparative gene regulatory network analysis in Alzheimer’s disease and major depressive disorder identifies shared core regulatory circuits
Authors: Puype Hanne , Deschildre Joke , Vermeirssen Vanessa
Published: February 2023

Alzheimer’s disease and major depressive disorder are prevalent, devastating conditions with limited treatment options. Recent insights suggest that despite distinct phenotypes, these disorders share similar processes such as neuroinflammation. However, the extent of overlapping biological processes and their underlying molecular mechanisms remain to be elucidated. Therefore, we adopted a computational systems biology approach to compare regulatory programs in the prefrontal cortex of both disorders. Leveraging publicly available RNA sequencing data on different human cohorts, both at bulk and single-cell level, and using diverse computational methodologies, we inferred gene regulatory networks, which model the molecular interactions between transcription factors and their target genes, and characterized cell-type-specific regulatory programs and biological pathways. We identified core regulatory circuits shared in both disorders, including transcription factors that play a pivotal role in microglial activation such as IKZF1, IRF8, RUNX1 and SPI1. Most of these transcription factors had a reported role in Alzheimer’s, but not in depression. We found several common pathways such as microglial activation, but also more disease-specific pathways. Through orthogonal data analysis, we were able to validate several of the predicted regulatory interactions in Alzheimer’s disease and major depressive disorder. In summary, our work revealed neuroinflammation and microglial activation in both diseases, under the control of shared core regulatory circuits. The potential relevance of these transcription factors and genes warrants additional investigation, especially in depression, offering possible novel therapeutic opportunities.
New estimates indicate that males are not larger than females in most mammals
Authors: Tombak Kaia J. , Hex Severine B. S. W. , Rubenstein Daniel I.
Published: February 2023

Sexual size dimorphism (SSD) has motivated a large body of research on mammalian mating strategies and sexual selection. Despite some contrary evidence, the narrative that larger males are the norm in mammals – upheld since Darwin’sDescent of Man– still dominates today, supported by meta-analyses that use crude measures of dimorphism and taxonomically-biased data. With newly-available datasets and primary sources reporting sex-segregated means and variances in adult body mass, we estimated statistically-determined rates of SSD in mammals, sampling taxa by their species richness at the family level. Our analyses of >400 species indicate that although males tend to be larger than femaleswhendimorphism occurs, males arenotlarger in most mammals, and suggest a need to revisit other assumptions in sexual selection research.

One-Sentence Summary

Taxonomically-balanced estimates of rates of sexual size dimorphism in mammals refute the ‘larger males’ narrative.
Peak performance singing requires daily vocal exercise in songbirds
Authors: Adam Iris , Riebel Katharina , Stål Per , Wood Neil B. , Previs Michael J. , Elemans Coen P.H.
Published: February 2023

Vocal signals mediate much of human and non-human communication. Key performance traits - such as repertoire size, speed and accuracy of delivery - affect communication efficacy in fitness-decisive contexts such as mate choice and resource competition1. Specialized fast vocal muscles2,3are central to accurate sound production4, but it is unknown whether vocal, like limb muscles5,6, need exercise to gain and maintain peak performance7,8. Here, we show that for song development in juvenile songbirds, the closest analogue to human speech acquisition9, regular vocal muscle exercise is crucial to achieve adult peak muscle performance. Furthermore, adult vocal muscle performance reduces within two days of abolishing exercise, leading to downregulation of critical proteins transforming fast to slower muscle fibre types. Daily vocal exercise is thus required to both gain and maintain peak vocal muscle performance, and if absent changes vocal output. We show that conspecifics can detect these acoustic changes and females prefer the song of exercised males. Song thus contains information on recent exercise status of the sender. Daily investment in vocal exercise to maintain peak performance is an unrecognized cost of singing and could explain why many birds sing daily even under adverse conditions10. Because neural regulation of syringeal and laryngeal muscle plasticity is equivalent, vocal output may reflect recent exercise status in all vocalizing vertebrates.
Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease
Authors: Ramirez Flores Ricardo O. , Lanzer Jan D. , Dimitrov Daniel , Velten Britta , Saez-Rodriguez Julio
Published: February 2023

Single-cell atlases across conditions are essential in the characterization of human disease. In these complex experimental designs, patient samples are profiled across distinct cell-types and clinical conditions to describe disease processes at the cellular level. However, most of the current analysis tools are limited to pairwise cross-condition comparisons, disregarding the multicellular nature of disease processes and the effects of other biological and technical factors in the variation of gene expression. Here we propose a computational framework for an unsupervised analysis of samples from cross-condition single-cell atlases and for the identification of multicellular programs associated with disease. Our strategy, that repurposes multi-omics factor analysis, incorporates the variation of patient samples across cell-types and enables the joint analysis of multiple patient cohorts, facilitating integration of atlases. We applied our analysis to a collection of acute and chronic human heart failure single-cell datasets and described multicellular processes of cardiac remodeling that were conserved in independent spatial and bulk transcriptomics datasets. In sum, our framework serves as an exploratory tool for unsupervised analysis of cross-condition single-cell atlas and allows for the integration of the measurements of patient cohorts across distinct data modalities, facilitating the generation of comprehensive tissue-centric understanding of disease.

Graphical Abstract