bluuebunny/crossref_metadata_2025 huggingface dataset:
Significantly amplified photoacoustic effect for silica-coated gold nanoparticles by interface heat transfer mechanisms
Authors: Youn Jonghae , Kang Peiyuan , Wilson Blake A. , Xie Chen , Basavarajappa Lokesh , Wang Qingxiao , Kim Moon , Hoyt Kenneth , Qin Zhenpeng
Published: September 2022

Plasmonic gold nanoparticles (AuNPs) are effective photoacoustic (PA) signal agents and have found important biomedical applications. The silica coating on the surface of AuNPs showed enhanced PA efficiency, however, the PA amplification mechanism remains unclear. Here, we systematically studied the silica coating effect on PA generation of AuNPs under different laser pulse durations. We experimentally demonstrated up to 4-fold PA amplification under thin silica coating (<5 nm) and a picosecond laser excitation. The theoretical model further suggests that the PA amplification originates from two interface heat transfer mechanisms including 1) the enhanced interface thermal conductance on the silica-water interface and 2) the electron-phonon energy transfer channel on the gold/silica interface. This study discovers a regime of large PA amplification and provides a new rationale for plasmonic nanoparticle design to achieve better PA efficiency.
Multi-modal digital pathology for colorectal cancer diagnosis by high-plex immunofluorescence imaging and traditional histology of the same tissue section
Authors: Lin Jia-Ren , Chen Yu-An , Campton Daniel , Cooper Jeremy , Coy Shannon , Yapp Clarence , Tefft Juliann B. , McCarty Erin , Ligon Keith L. , Rodig Scott J. , Reese Steven , George Tad , Santagata Sandro , Sorger Peter K.
Published: September 2022

Precision medicine is critically dependent on better methods for diagnosing and staging disease and predicting drug response. Histopathology using Hematoxylin and Eosin (H&E) stained tissue - not genomics – remains the primary diagnostic method in cancer. Recently developed highly-multiplexed tissue imaging methods promise to enhance research studies and clinical practice with precise, spatially-resolved, single-cell data. Here we describe the “Orion” platform for collecting and analyzing H&E and high-plex immunofluorescence (IF) images from the same cells in a whole-slide format suitable for diagnosis. Using a retrospective cohort of 74 colorectal cancer resections, we show that IF and H&E images provide human experts and machine learning algorithms with complementary information that can be used to generate interpretable, multiplexed image-based models predictive of progression-free survival. Combining models of immune infiltration and tumor-intrinsic features achieves a hazard ratio of ∼0.05, demonstrating the ability of multi-modal Orion imaging to generate high-performance biomarkers.
Determining the Role of Environmental Covariates on Planktivorous Elasmobranch Population Trends within an Isolated Marine Protected Area
Authors: Saltzman Julia , White Easton R.
Published: September 2022

Several studies have found predictable relationships between the behavior of planktivores and environmental conditions, suggesting that planktivores may be especially sensitive to environmental change. However, many studies to date are based on limited observations, include few of the many environmental covariates which could influence planktivores, and do not occur over long enough time periods to make inferences about the potential effects of environmental change. As such, long term datasets on planktivores are necessary to disentangle the potential impacts of oceanographic and environmental variability. In this study, to elucidate the relationship between plankivores and environmental variability, we use data obtained over the last 28 years by a small group of divemasters at Cocos Island, Costa Rica, one of the oldest marine reserves in the world. We found that, in general, for planktivorous elasmobranchs, several environmental variables, such as, chlorophyll A, lunar cycle, and salinity have clear influences on their occurrence and relative abundances. We found that in the phases of lower illuminations, there were significant increases in abundance of mobula rays. Specifically, a 0.10 mg/m3increase in Chlorophyll A correlated with 26% decrease in whale sharks. We found that increases in salinity correlated with increases in mobula abundance but did not correlate with observations of mantas or whale sharks. We also found that omission of environmental covariates can lead to overprediction and underprediction of relative abundances. Our findings highlight the need to take environmental conditions into account when evaluating the efficacy of marine protection.
Prediction and Classification of the Uptake and Disposition of Antidepressants and New CNS-Active Drugs in the Human Brain using the ANDROMEDA by Prosilico Software and Brainavailability-Matrix
Authors: Fagerholm Urban , Hellberg Sven , Alvarsson Jonathan , Spjuth Ola
Published: September 2022

Abstract

Background

Passive blood-brain barrier permeability (BBB Pe), fraction bound to brain tissue (fb,brain) and efflux by transport proteins MDR-1 and BCRP are essential determinants for the brain uptake and disposition of drugs.

Methods

The main objective of the study was to use the software ANDROMEDA by Prosilico to predict passive BBB Pe- and fb,brain-classes and MDR-1- and BCRP-specificities for various classes of antidepressants and for CNS-active small drugs marketed during 2020 and 2021, and then to position them according to a new 2-dimensional Brainavailability-Matrix (8 passive BBB Pex 4 fb,brainclasses, where class 11 has highest and 84 lowest values/brainavailability). Predicted estimates were used, except for cases where measured values were available.

Results and Conclusion

Results for 53 drugs show that adequate CNS uptake and disposition are achieved for compounds placed in the zones for low, moderate and high brainavailability, despite efflux. They also show that high brainavailability and efflux are common for CNS-active drugs and that modern CNS-active drugs generally have lower brainavailability than older antidepressive drugs. Furthermore, they demonstrate that ANDROMEDA by Prosilico and the new Brainavailability-Matrix are applicable for prediction, optimization and positioning of CNS uptake and disposition of drugs and drug candidates in man.
Multifactorial heterogeneity of the human mutation landscape related to DNA replication dynamics
Authors: Caballero Madison , Boos Dominik , Koren Amnon
Published: September 2022

Mutations do not occur uniformly across genomes but instead show biased associations with various genomic features, most notably late replication timing. However, it remains contested which mutation types in human cells relate to DNA replication dynamics and to what extents. Previous studies have been limited by the absence of cell-type-specific replication timing profiles and lack of consideration of inter-individual variation. To overcome these limitations, we performed high-resolution comparisons of mutational landscapes between and within lymphoblastoid cell lines from 1662 individuals, 151 chronic lymphocytic leukemia patients, and three colon adenocarcinoma cell lines including two with mismatch repair deficiency. Using cell type-matched replication timing profiles, we demonstrate how mutational pathways can exhibit heterogeneous replication timing associations. We further identified global mutation load as a novel, pervasive determinant of mutational landscape heterogeneity across individuals. Specifically, elevated mutation load corresponded to increased late replication timing bias as well as replicative strand asymmetries of clock-like mutations and off-target somatic hypermutation. The association of somatic hypermutation with DNA replication timing was further influenced by mutational clustering. Considering these multivariate factors, and by incorporating mutation phasing at an unprecedented scale, we identified a unique mutational landscape on the inactive X-chromosome. Overall, we report underappreciated complexity of mutational pathways and their relationship to replication timing and identify specific factors underlying differential mutation landscapes among cell types and individuals.
Predicting enzyme substrate chemical structure with protein language models
Authors: Jinich Adrian , Nazia Sakila Z. , Tellez Andrea V. , Rappoport Dmitrij , AlQuraishi Mohammed , Rhee Kyu
Published: September 2022

The number of unannotated or orphan enzymes vastly outnumber those for which the chemical structure of the substrates are known. While a number of enzyme function prediction algorithms exist, these often predict Enzyme Commission (EC) numbers or enzyme family, which limits their ability to generate experimentally testable hypotheses. Here, we harness protein language models, cheminformatics, and machine learning classification techniques to accelerate the annotation of orphan enzymes by predicting their substrate’s chemical structural class. We use the orphan enzymes ofMycobacterium tuberculosisas a case study, focusing on two protein families that are highly abundant in its proteome: the short-chain dehydrogenase/reductases (SDRs) and the S-adenosylmethionine (SAM)-dependent methyltransferases. Training machine learning classification models that take as input the protein sequence embeddings obtained from a pre-trained, self-supervised protein language model results in excellent accuracy for a wide variety of prediction tasks. These include redox cofactor preference for SDRs; small-molecule vs. polymer (i.e. protein, DNA or RNA) substrate preference for SAM-dependent methyltransferases; as well as more detailed chemical structural predictions for the preferred substrates of both enzyme families. We then use these trained classifiers to generate predictions for the full set of unannotated SDRs and SAM-methyltransferases in the proteomes ofM. tuberculosisand other mycobacteria, generating a set of biochemically testable hypotheses. Our approach can be extended and generalized to other enzyme families and organisms, and we envision it will help accelerate the annotation of a large number of orphan enzymes.

Graphical abstract
Genetically Encoded RNA-based Bioluminescence Resonance Energy Transfer (BRET) Sensors
Authors: Mi Lan , Yu Qikun , Mudiyanselage Aruni P.K.K. Karunanayake , Wu Rigumula , Sun Zhining , Zheng Ru , Ren Kewei , You Mingxu
Published: September 2022

RNA-based nanostructures and molecular devices have become popular for developing biosensors and genetic regulators. These programmable RNA nanodevices can be genetically encoded and modularly engineered to detect various cellular targets and then induce output signals, most often a fluorescence readout. Although powerful, the high reliance of fluorescence on the external excitation light raises concerns on its high background, photobleaching, and phototoxicity. Bioluminescence signals can be an ideal complementary readout for these genetically encoded RNA nanodevices. However, RNA-based real-time bioluminescent reporters have been rarely developed. In this study, we reported the first type of genetically encoded RNA-based bioluminescence resonance energy transfer (BRET) sensors that can be used for real-time target detection in living cells. By coupling a luciferase bioluminescence donor with a fluorogenic RNA-based acceptor, our BRET system can be modularly designed to image and detect various cellular analytes. We expect this novel RNA-based bioluminescent system can be potentially used broadly in bioanalysis and nanomedicine for engineering biosensors, characterizing cellular RNA–protein interactions, as well as high-throughput screening or in vivo imaging.
Kinetic relaxation of giant vesicles validates diffusional softening in a binary lipid mixture
Authors: Sapp Kayla , Aleksanyan Mina , Kerr Kaitlyn , Dimova Rumiana , Sodt Alexander
Published: September 2022

The stiffness of biological membranes determines the work required by cellular machinery to form and dismantle vesicles and other lipidic shapes. Model membrane stiffness can be determined from the equilibrium distribution of giant unilamellar vesicle surface undulations observable by phase contrast microscopy. With two or more components, lateral fluctuations of composition will couple to surface undulations depending on the curvature sensitivity of the constituent lipids. The result is a broader distribution of undulations whose complete relaxation is partially determined by lipid diffusion. In this work, kinetic anaysis of the undulations of giant unilamellar vesicles made of phospatidylcholine-phosphatidylethanolamine mixtures validates the molecular mechanism by which the membrane is made 25% softer than a single-component one. The mechanism is relevant to biological membranes, which have diverse and curvature-sensitive lipids.
Decoding of the speech envelope from EEG using the VLAAI deep neural network
Authors: Accou Bernd , Vanthornhout Jonas , Van hamme Hugo , Francart Tom
Published: September 2022

To investigate the processing of speech in the brain, commonly simple linear models are used to establish a relationship between brain signals and speech features. However, these linear models are ill-equipped to model a highly-dynamic, complex non-linear system like the brain, and they often require a substantial amount of subject-specific training data. This work introduces a novel speech decoder architecture: the Very Large Augmented Auditory Inference (VLAAI) network.

The VLAAI network outperformed state-of-the-art subject-independent models (median Pearson correlation of 0.19, p < 0.001), yielding an increase over the well-established linear model by 52%. Using ablation techniques we identified the relative importance of each part of the VLAAI network and found that the non-linear components and output context module influenced model performance the most (10% relative performance increase). Subsequently, the VLAAI network was evaluated on a holdout dataset of 26 subjects and publicly available unseen dataset to test generalization for unseen subjects and stimuli. No significant difference was found between the holdout subjects and the default test set, and only a small difference between the default test set and the public dataset was found. Compared to the baseline models, the VLAAI network still significantly outperformed all baseline models on the public dataset. We evaluated the effect of training set size by training the VLAAI network on data from 1 up to 80 subjects and evaluated on 26 holdout subjects, revealing a logarithmic relationship between the number of subjects in the training set and the performance on unseen subjects. Finally, the subject-independent VLAAI network was fine-tuned for 26 holdout subjects to obtain subject-specific VLAAI models. With 5 minutes of data or more, a significant performance improvement was found, up to 34% (from 0.18 to 0.25 median Pearson correlation) with regards to the subject-independent VLAAI network.
30-Minute Highly Multiplexed VaxArray Immunoassay for Pneumococcal Vaccine Antigen Characterization
Authors: Hu Tianjing , Miller David F. , Taylor Amber W. , Riley Christine , McCormick Caitlin , Thomas Keely N. , Gao Rachel Y. , Rowlen Kathy L. , Byrne Emilia B. , Kumar Pardeep , Kim Soo Kyung , Dawson Erica D.
Published: September 2022

Pneumonia accounts for over 20% of deaths worldwide in children aged 1 to 5 years, disproportionately affecting lower- and middle-income countries. Effective, highly multivalent pneumococcal vaccines are available to decrease disease burden, with numerous new vaccines currently under development to serve a variety of worldwide markets. However, pneumococcal conjugate vaccines are among the hardest biologics to manufacture and characterize due to their complexity and heterogeneity. Current characterization methods are often inherently singleplex, requiring separate tests for each serotype present. In addition, identity and quantity are often determined with separate methods. We have developed the VaxArray Pneumococcal Assay for applications in identity, quantity, and stability testing of pneumococcal polysaccharide and pneumococcal conjugate vaccines. The VaxArray Pneumococcal Assay has a time to result of less than 30 minutes and is an off-the-shelf multiplexed, microarray-based immunoassay kit that can identify and simultaneously quantify 23 pneumococcal polysaccharide serotypes common to many on-market and in-development vaccines. Here, we highlight the potential of the assay for identity testing by showing high reactivity and serotype-specificity to a wide variety of native polysaccharides, CRM197-conjugated polysaccharides, and drug product. The assay also has vaccine-relevant lower limits of quantification in the low to mid ng/mL range and can be used for accurate quantification even in adjuvanted vaccines. Excellent correlation to the anthrone assay is demonstrated, with VaxArray resulting in significantly improved precision over this antiquated chemical method.
Atypical B cells consist of subsets with distinct effector functions
Authors: Reyes Raphael A. , Batugedara Gayani , Dutta Paramita , Reers Ashley B. , Garza Rolando , Ssewanyana Isaac , Jagannathan Prasanna , Feeney Margaret E. , Greenhouse Bryan , Bol Sebastiaan , Ay Ferhat , Bunnik Evelien M.
Published: September 2022

Atypical B cells are a population of activated B cells that are commonly enriched in individuals with chronic immune activation, but are also part of a normal immune response to infection or vaccination. Prior studies to determine the function of these cells have yielded conflicting results, possibly due to functional heterogeneity among this B cell population. To better define the role(s) of atypical B cells in the host adaptive immune response, we performed single-cell sequencing of transcriptomes, cell surface markers, and B cell receptors in individuals with chronicPlasmodium falciparumexposure, a condition known to lead to accumulation of circulating atypical B cells. Our studies identified three previously uncharacterized populations of atypical B cells with distinct transcriptional and functional profiles, that separate into two differentiation pathways. We identified a set of cell surface markers to distinguish these atypical B cell subsets and confirmed their presence in malaria-experienced children and adults using flow cytometry.Plasmodium falciparum-specific cells were present in equal proportions within each of these atypical B cell populations, indicating that all three subsets develop in response to antigen stimulation. However, we observed marked differences among the three subsets in their ability to produce IgG upon T-cell-dependent activation. Collectively, our findings help explain the conflicting observations in prior studies on the functions of atypical B cells and provide a better understanding of their role in the adaptive immune response in chronic inflammatory conditions.

One sentence summary

Atypical B cells consist of three subsets that may play distinct roles in the host adaptive immune response.
Using Machine Learning Enabled Phenotyping To Characterize Nodulation In Three Early Vegetative Stages In Soybean
Authors: Carley Clayton N. , Zubrod Melinda , Dutta Somak , Singh Asheesh K.
Published: September 2022

The symbiotic relationship between soybean [Glycine max L. (Merr.)] roots and bacteria (Bradyrhizobium japonicum) lead to the development of nodules, important legume root structures where atmospheric nitrogen (N2) is fixed into bio-available ammonia (NH3) for plant growth and development. With the recent development of the Soybean Nodule Acquisition Pipeline (SNAP), nodules can more easily be quantified and evaluated for genetic diversity and growth patterns across unique soybean root system architectures. We explored six diverse soybean genotypes across three field year combinations in three early vegetative stages of development and report the unique relationships between soybean nodules in the taproot and non-taproot growth zones of diverse root system architectures of these genotypes. We found unique growth patterns in the nodules of taproots showing genotypic differences in how nodules grew in count, size, and total nodule area per genotype compared to non-taproot nodules. We propose that nodulation should be defined as a function of both nodule count and individual nodule area resulting in a total nodule area per root or growth regions of the root. We also report on the relationships between the nodules and total nitrogen in the seed at maturity, finding a strong correlation between the taproot nodules and final seed nitrogen at maturity. The applications of these findings could lead to an enhanced understanding of the plant-Bradyrhizobium relationship, and exploring these relationships could lead to leveraging greater nitrogen use efficiency and nodulation carbon to nitrogen production efficiency across the soybean germplasm.

Core Ideas

The growth and development of soybean nodules on the taproot and non-taproots have unique growth and development patterns.

In general, taproot nodules increase in area, while non-taproot nodules increase in count and area.

Nodulation should be defined by the total nodule area as a function of both nodule count and individual nodule size.

Genotypes adjust their nodulation through either increasing nodule count or nodule size to increase the total nodule area per root between each growth stage.

There is a strong correlation between early growth stage taproot nodules and final seed nitrogen content.
Electrophile scanning by chemical proteomics reveals a potent pan-active DUB probe for investigation of deubiquitinase activity in live cells
Authors: Conole Daniel , Cao Fangyuan , Am Ende Christopher W. , Xue Liang , Kantesaria Sheila , Kang Dahye , Jin Jun , Owen Dafydd , Lohr Linda , Schenone Monica , Majmudar Jaimeen D. , Tate Edward W.
Published: September 2022

Deubiquitinases (DUBs) are proteases that hydrolyze isopeptide bonds linking ubiquitin to protein substrates, which can lead to reduced substrate degradation through the ubiquitin proteasome system. Deregulation of DUB activity has been implicated in many disease states, including cancer, neurodegeneration and inflammation, making them potentially attractive targets for therapeutic intervention. The >100 known DUB enzymes have been classified primarily by their conserved active sites, but we are still building our understanding of their substrate profiles, localization and regulation of DUB activity in diverse contexts. Ubiquitin-derived covalent activity-based probes (ABPs) are the premier tool for DUB activity profiling, but their large recognition element impedes cellular permeability and presents an unmet need for small molecule ABPs which account for local DUB concentration, protein interactions, complexes, and organelle compartmentalization in intact cells or organisms. Here, through comprehensive warhead profiling we identify cyanopyrrolidine (CNPy) probe IMP-2373 (12), a small molecule pan-DUB ABP to monitor DUB activity in physiologically relevant live cell systems. Through chemical proteomics and targeted assays we demonstrate that IMP-2373 quantitatively engages more than 35 DUBs in live cells across a range of non-toxic concentrations, and in diverse cell lines and disease models, and we demonstrate its application to quantification of changes in intracellular DUB activity during MYC deregulation in a model of B cell lymphoma. IMP-2373 thus offers a complementary tool to ubiquitin ABPs to monitor dynamic DUB activity in the context of disease-relevant phenotypes.

SYNOPSIS TOC

Graphical Abstract
Enteroviral 2C protein is an RNA-stimulated ATPase and uses a two-step mechanism for binding to RNA and ATP
Authors: Yeager Calvin , Carter Griffin , Gohara David W , Yennawar Neela H , Enemark Eric J , Arnold Jamie J , Cameron Craig E
Published: September 2022

The enteroviral 2C protein is a therapeutic target, but the absence of a mechanistic framework for this enzyme limits our understanding of inhibitor mechanisms. Here we use poliovirus 2C and a derivative thereof to elucidate the first biochemical mechanism for this enzyme and confirm the applicability of this mechanism to other members of the enterovirus genus. Our biochemical data are consistent with a dimer forming in solution, binding to RNA, which stimulates ATPase activity by increasing the rate of hydrolysis without impacting affinity for ATP substantially. Both RNA and DNA bind to the same or overlapping site on 2C, driven by the phosphodiester backbone, but only RNA stimulates ATP hydrolysis. We propose that RNA binds to 2C driven by the backbone, with reorientation of the ribose hydroxyls occurring in a second step to form the catalytically competent state. 2C also uses a two-step mechanism for binding to ATP. Initial binding is driven by the α and ß phosphates of ATP. In the second step, the adenine base and other substituents of ATP are used to organize the active site for catalysis. These studies provide the first biochemical description of determinants driving specificity and catalytic efficiency of a picornaviral 2C ATPase.
Strong positive allometry of bite force in leaf-cutter ants increases the range of cuttable plant tissues
Authors: Püffel Frederik , Roces Flavio , Labonte David
Published: September 2022

Attaleaf-cutter ants are the prime herbivore in the Neotropics: differently-sized foragers harvest plant material to grow a fungus as crop. Efficient foraging involves complex interactions between worker-size, task-preferences and plant-fungus-suitability; it is, however, ultimately constrained by the ability of differently-sized workers to generate forces large enough to cut vegetation. In order to quantify this ability, we measured bite forces ofA. vollenweiderileaf-cutter ants spanning more than one order of magnitude in body mass. Maximum bite force scaled almost in direct proportion to mass; the largest workers generated peak bite forces 2.5 times higher than expected from isometry. This remarkable positive allometry can be explained via a biomechanical model that links bite forces with substantial size-specific changes in the morphology of the musculoskeletal bite apparatus. In addition to these morphological changes, we show that bite forces of smaller ants peak at larger mandibular opening angles, suggesting a size-dependent physiological adaptation, likely reflecting the need to cut leaves with a thickness that corresponds to a larger fraction of the maximum possible gape. Via direct comparison of maximum bite forces with leaf-mechanical properties, we demonstrate (i) that bite forces in leaf-cutter ants need to be exceptionally large compared to body mass to enable them to cut leaves; and (ii), that the positive allometry enables colonies to forage on a wider range of plant species without the need for extreme investment into even larger workers. Our results thus provide strong quantitative arguments for the adaptive value of a positively allometric bite force.
A novel CLAVATA1 mutation causes multilocularity in Brassica rapa
Authors: Chow Hiu Tung , Kendall Timmy , Mosher Rebecca A.
Published: September 2022

Locules are the seed-bearing structure of fruits. Multiple locules are associated with increased fruit size and seed set, and therefore control of locule number is an important agronomic trait. Locule number is controlled in part by the CLAVATA-WUSCHEL pathway. Disruption of either the CLAVATA1 receptor-like kinase or its ligand CLAVATA3 can cause larger floral meristems and an increased number of locules. In an EMS mutagenized population of Brassica rapa, we identified a mutant allele that raises the number of locules from 4 to a range of from 6 to 8. Linkage mapping and genetic analysis support that the mutant phenotype is due to a missense mutation in a CLAVATA 1 (CLV1) homolog. In addition to increased locule number, brclv1 individuals fail to terminate their floral meristems, resulting in internal gynoecia that negatively impact seed production.
Treenome Browser: co-visualization of enormous phylogenies and millions of genomes
Authors: Kramer Alexander M. , Sanderson Theo , Corbett-Detig Russell
Published: September 2022

Treenome Browser is a web browser tool to interactively visualize millions of genomes alongside huge phylogenetic trees.

Availability and Implementation

Treenome Browser for SARS-CoV-2 can be accessed at cov2tree.org, or at taxonium.org for user-provided trees. Source code and documentation are available at github.com/theosanderson/taxonium and docs.taxonium.org/en/latest/treenome.html.

Contact

alex.kramer@ucsc.edu, rucorbet@ucsc.edu
Coinfection with chytrid genotypes drives divergent infection dynamics reflecting broad epidemiological patterns
Authors: Carvalho Tamilie , Medina Daniel , Ribeiro Luisa P. , Rodriguez David , Jenkinson Thomas S. , Becker C. Guilherme , Toledo Luís Felipe , Hite Jessica
Published: September 2022

By altering the abundance, diversity, and distribution of species — and their pathogens — globalization may inadvertently select for more virulent pathogens. In Brazil’s Atlantic Forest, a hotspot of amphibian biodiversity, the pet trade has facilitated the co-occurrence of previously isolated enzootic and panzootic lineages of the pathogenic amphibian-chytrid (‘Bd’) and generated new virulent recombinant genotypes (‘hybrid’). Epidemiological data indicate that amphibian declines are most severe in hybrid zones, suggesting that coinfections are causing more severe infections or selecting for higher virulence. We investigated how coinfections involving these genotypes shaped virulence and transmission. Overall, coinfection favored the more virulent and competitively superior panzootic genotype, despite dampening its virulence and transmission. However, for the least virulent and least competitive genotype, coinfection increased both pathogen virulence and transmission. Thus, by integrating experimental and epidemiological data, our results provide mechanistic insight into how globalization can select for, and propel, the emergence of introduced hypervirulent lineages, such as the globally distributed panzootic lineage of Bd.
Polygenic scoring accuracy varies across the genetic ancestry continuum in all human populations
Authors: Ding Yi , Hou Kangcheng , Xu Ziqi , Pimplaskar Aditya , Petter Ella , Boulier Kristin , Privé Florian , Vilhjálmsson Bjarni J. , Loohuis Loes Olde , Pasaniuc Bogdan
Published: September 2022

Polygenic scores (PGS) have limited portability across different groupings of individuals (e.g., by genetic ancestries and/or social determinants of health), preventing their equitable use. PGS portability has typically been assessed using a single aggregate population-level statistic (e.g., R2), ignoring inter-individual variation within the population. Here we evaluate PGS accuracy at individual-level resolution, independent of its annotated genetic ancestries. We show that PGS accuracy varies between individuals across the genetic ancestry continuum in all ancestries, even within traditionally “homogeneous” genetic ancestry clusters. Using a large and diverse Los Angeles biobank (ATLAS, N= 36,778) along with the UK Biobank (UKBB, N= 487,409), we show that PGS accuracy decreases along a continuum of genetic ancestries in all considered populations and the trend is well-captured by a continuous measure of genetic distance (GD) from the PGS training data; Pearson correlation of −0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained in UKBB “white British” individuals to European-ancestry individuals of ATLAS, individuals in the highest GD decile have 14% lower accuracy relative to the lowest decile; notably the lowest GD decile of Hispanic/Latino American ancestry individuals showed similar PGS performance as the highest GD decile of European ancestry ATLAS individuals. GD is significantly correlated with PGS estimates themselves for 82 out of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestry in PGS interpretation. Our results highlight the need for moving away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGS and their applications.
Chromosome-scale reference genome and RAD-based genetic map of yellow starthistle (Centaurea solstitialis) reveal putative structural variation and QTL associated with invader traits
Authors: Reatini Bryan , Pelosi Jessie A. , Cang F. Alice , Jiang Qiuyu , McKibben Michael T. W. , Barker Michael S. , Rieseberg Loren H. , Dlugosch Katrina M.
Published: September 2022

Invasive species offer outstanding opportunities to identify the genomic sources of variation that contribute to rapid adaptation, as well as the genetic mechanisms facilitating invasions. The Eurasian plant yellow starthistle (Centaurea solstitialis) is highly invasive in North and South American grasslands and known to have evolved increased growth and reproduction during invasion. Here we develop new genomic resources forC. solstitialisand map the genetic basis of invasiveness traits. We present a chromosome-scale (1N = 8) reference genome using PacBio CLR and Dovetail Omni-C technologies, and functional gene annotation using RNAseq. We find repeat structure typical of the family Asteraceae, with over 25% of gene content derived from ancestral whole genome duplications (paleologs). Using an F2 mapping population derived from a cross between native and invading parents, with a restriction site-associated DNA (RAD)-based genetic map, we validate the assembly and identify 13 QTL underpinning size traits that have evolved during invasion. We find evidence that large effect QTL may be associated with structural variants between native and invading genotypes, including a variant with an overdominant and pleiotropic effect on key invader traits. We also find evidence of significant paleolog enrichment under two QTL. Our results add to growing evidence of the importance of structural variants in evolution, and to understanding of the rapid evolution of invaders.

Significance Statement

Invasive species often evolve rapidly in new environments, potentially informing our understanding of the genomic basis of adaptation, but genomic studies of these non-model systems are limited. We provide a chromosome-scale reference genome, annotation, and genetic map for the invasive plant yellow starthistle, and we investigate the genetic basis of invader trait evolution in this system. We find regions of the genome with large effects on traits that differ between native and invading genotypes, and evidence suggesting genome structural variants and past genome duplications could play a role in rapid adaptation of invading populations. These genomic resources and evolutionary insights aid in our understanding of the sources of genomic variation for adaptation, and how their evolution facilitates invasion.
TIVAN-indel: A computational framework for annotating and predicting noncoding regulatory small insertion and deletion
Authors: Agarwal Aman , Chen Li
Published: September 2022

Motivation

Small insertion and deletion (sindel) of human genome has an important implication for human disease. One important mechanism for noncoding sindel to have an impact on human diseases and phenotypes is through the regulation of gene expression. Nevertheless, current sequencing technology may lack statistical power and resolution to pinpoint the causal sindel due to lower minor allele frequency or small effect. As an alternative solution, a supervised machine learning method can identify the otherwise missing causal sindels by predicting the regulatory potential of sindels directly. However, computational methods for annotating and predicting the regulatory sindels, especially in the noncoding regions, are underdeveloped.

Results

By leveraging recognized sindels incis-expression quantitative trait loci (cis-eQTLs) across 44 tissues and cell types in GTEx, and a compilation of both generic functional annotations and tissue/cell typespecific multi-omics features generated by a sequence-based deep learning model, we developed TIVAN-indel, which is an XGBoost-based supervised framework for scoring noncoding sindels based their potential to regulate the nearby gene expression. As a result, we demonstrate that TIVAN-indel achieves the best prediction performance in both cross-validation with-tissue prediction and independent cross-tissue evaluation. As an independent evaluation, we train TIVAN-indel from “Whole Blood” tissue in GTEx data and test the model using 15 immune cell types from an independent study DICE. Lastly, we perform an enrichment analysis for both recognized and predicted sindels in key regulatory regions such as chromatin interactions, open chromatin and histone modification sites, and find biologically meaningful enrichment patterns.

Availability and implementation

https://github.com/lichen-lab/TIVAN-indel

Contact

li.chen1@ufl.edu
King- and queen-specific degradation of uric acid is the key to reproduction in termites
Authors: Konishi Takao , Tasaki Eisuke , Takata Mamoru , Matsuura Kenji
Published: September 2022

Caste-based reproductive division of labour in social insects is built on asymmetries in resource allocation within colonies. Kings and queens dominantly consume limited resources for reproduction, while non-reproductive castes such as workers and soldiers help reproductive castes. Studying the regulation of such asymmetries in resource allocation is crucial for understanding the maintenance of sociality in insects, although the molecular background is poorly understood. We focused on uric acid, which is reserved and utilized as a valuable nitrogen source in wood-eating termites. We found that king- and queen-specific degradation of uric acid is the key to reproduction in the subterranean termite Reticulitermes speratus. The urate oxidase gene (RsUAOX), which catalyses the first step of nitrogen recycling from stored uric acid, was highly expressed in mature kings and queens, and upregulated with differentiation into neotenic kings/queens. Suppression of uric acid degradation decreased the number of eggs laid per queen. Uric acid was shown to be provided by workers to reproductive castes. Our results suggest that the capacity to use nitrogen, which is essential for the protein synthesis required for reproduction, contributes to colony cohesion expressed as the reproductive monopoly held by kings and queens.
Assessment of pre-clinical liver models based on their ability to predict the liver-tropism of AAV vectors
Authors: Westhaus Adrian , Cabanes-Creus Marti , Dilworth Kimberley L. , Zhu Erhua , Gómez David Salas , Navarro Renina G. , Amaya Anais K. , Scott Suzanne , Kwiatek Magdalena , McCorkindale Alexandra L. , Hayman Tara E. , Frahm Silke , Perocheau Dany P. , Tran Bang Manh , Vincan Elizabeth , Wong Sharon L. , Waters Shafagh A. , Wilson Laurence O. W. , Baruteau Julien , Diecke Sebastian , González-Aseguinolaza Gloria , Santilli Giorgia , Thrasher Adrian J. , Alexander Ian E. , Lisowski Leszek
Published: September 2022

The liver is a prime target for in vivo gene therapies using recombinant adeno-associated viral vectors (rAAV). Multiple clinical trials have been undertaken for this target in the past 15 years, however we are still to see market approval of the first liver-targeted AAV-based gene therapy. Inefficient expression of the therapeutic transgene, vector-induced liver toxicity and capsid, and/or transgene-mediated immune responses reported at high vector doses are the main challenges to date. One of the contributing factors to the insufficient clinical outcomes, despite highly encouraging preclinical data, is the lack of robust, biologically- and clinically-predictive preclinical models. To this end, this study reports findings of a functional evaluation of six AAV vectors in twelve preclinical models of the human liver, with the aim to uncover which model is the most relevant for the selection of AAV capsid variant for safe and efficient transgene delivery to primary human hepatocytes. The results, generated by studies in models ranging from immortalized cells, iPSC-derived and primary hepatocytes, and primary human hepatic organoids to in vivo models, increased our understanding of the strengths and weaknesses of each system. This should allow the development of novel gene therapies targeting the human liver.
Prediction of heart transplant rejection from routine pathology slides with self-supervised Deep Learning
Authors: Seraphin Tobias Paul , Luedde Mark , Roderburg Christoph , van Treeck Marko , Scheider Pascal , Buelow Roman D. , Boor Peter , Loosen Sven H. , Provaznik Zdenek , Mendelsohn Daniel , Berisha Filip , Magnussen Christina , Westermann Dirk , Luedde Tom , Brochhausen Christoph , Sossalla Samuel , Kather Jakob Nikolas
Published: September 2022

Background and Aims

One of the most important complications of heart transplantation is organ rejection, which is diagnosed on endomyocardial biopsies by pathologists. Computer-based systems could assist in the diagnostic process and potentially improve reproducibility. Here, we evaluated the feasibility of using deep learning in predicting the degree of cellular rejection from pathology slides as defined by the International Society for Heart and Lung Transplantation (ISHLT) grading system.

Methods

We collected 1079 histopathology slides from 325 patients from three transplant centers in Germany. We trained an attention-based deep neural network to predict rejection in the primary cohort and evaluated its performance using cross validation and by deploying it to three cohorts.

Results

For binary prediction (rejection yes/no) the mean Area Under the Receiver Operating Curve (AUROC) was 0.849 in the cross-validated experiment and 0.734, 0.729 and 0.716 in external validation cohorts. For a prediction of the ISHLT grade (0R, 1R, 2/3R), AUROCs were 0.835, 0.633 and 0.905 in the cross-validated experiment and 0.764, 0.597, 0.913, and 0.631, 0.633, 0.682, and 0.722, 0.601, 0.805 in the validation cohorts, respectively. The predictions of the AI model were interpretable by human experts and highlighted plausible morphological patterns.

Conclusions

We conclude that artificial intelligence can detect patterns of cellular transplant rejection in routine pathology, even when trained on small cohorts.
Smartphone videos of the sit-to-stand test predict osteoarthritis and health outcomes in a nationwide study
Authors: Boswell Melissa , Kidziński Łukasz , Hicks Jennifer , Uhlrich Scott , Falisse Antoine , Delp Scott
Published: September 2022

Physical function decline due to aging or disease can be assessed with quantitative motion analysis, but this currently requires expensive laboratory equipment. We introduce a self-guided quantitative motion analysis of the widely used five-repetition sit-to-stand test using a smartphone. Across 35 US states, 405 participants recorded a video performing the test in their homes. We found novel relationships not detectable in a clinical implementation of this test. Trunk angle during the sit-to-stand transition was greater in individuals with osteoarthritis and differed across ethnicities. In individuals 50 years of age or older, those with greater trunk angular acceleration had a higher mental health score. We also detected known associations between longer time to complete the five repetitions and lower physical health scores, higher BMI, and older age. Our findings demonstrate that at-home movement analysis goes beyond established clinical metrics to provide objective and inexpensive digital outcome metrics for nationwide studies.
Retrospective and prospective studies evaluating the performance of the SARS-Cov-2 “AQ+ COVID-19 Ag Rapid Test” from InTec on symptomatic and non-symptomatic patients
Authors: Prazuck Thierry , Serreau Raphael , Theillay Aurelie , Pallay Sandra , Pires-Roteia Daniela , Prazuck Fanny , Lesne Fabien
Published: September 2022

For the last two years, the SARS-CoV-2 virus spread all around the world and led to the COVID-19 pandemic. The need of methods to control the pandemic and to propose rapid and efficient diagnostic tools has emerged. In this perspective, SARS-CoV-2 rapid antigen detection tests (RADT) have been developed. We performed a retrospective study on 638 collected nasopharyngeal samples used for reference RT-qPCR diagnosis to compare the AQ+ COVID-19 Ag Rapid Test” from InTec (AQ+ InTec test) performance with other commercially available RADT. We analysed the sensitivity and specificity of the different tests and showed a better overall performance of the AQ+ InTec test, which was confirmed on the SARS-Cov-2 Omicron variant. We then conducted a prospective study on 1428 patients, to evaluate the sensitivity and specificity of the AQ+ InTec test on nasal and nasopharyngeal samples in a point of care setting. We showed that sensitivity and specificity reach acceptable criteria regarding the official recommendations of the MDCG 2021-21 in both symptomatic and asymptomatic patients. Overall, the results of these two studies confirm that the AQ+ InTec test is a valuable tool for testing in a pandemic context with a high proportion of asymptomatic patients who are potential carriers for the SARS-CoV-2 virus and is performant on the most current circulating variant Omicron.

Highlights

The sensitivity of the AQ+ COVID-19 Ag Rapid Test from InTec reaches 94.4% on nasal samples and 97.4% on nasopharyngeal samples.

The performance of the test remains high on asymptomatic patients with a sensitivity of 89.2% on nasal samples and 97.0% on nasopharyngeal samples.

Prospective study in a point of care setting revealed a better sensitivity compared with other commercially available rapid antigen detection tests
Falls Efficacy Scale International (FES-I) as a predictor of gait and balance abnormalities in community dwelling older people
Authors: McColl Lewis , Strassheim Victoria , Linsley Matthew , Green David , Dunkel Charlotte , Trundle Heidi , Gibbon Jake R , Parry Steve W
Published: September 2022

Background

Fear of falling (FoF) is common amongst community-dwelling older adults and is associated with higher falls risk. FoF is common amongst those with gait and balance abnormalities (GABAb), yet the ability of FoF measures to predict GABAb has not been assessed.

Methods

Data were reviewed from attendees of the North Tyneside Community Falls Prevention Service. The Falls Efficacy Scale International (FES-I) was used to measure falls efficacy, with a score larger than 23.5 indicating a concern for falling. Gait and balance measures were assessed, with cut-offs used to indicate poor and non-poor results for timed up and go (TUG) (>14s), five times sit to stand (FTSS) (>15s) and gait speed (GS) (<1 m/s). Receiver operating characteristic curves were generated for sensitivity and specificity analysis.

Results

FES-I score had good to excellent sensitivity when predicting TUG (87.1%), FTSS (82.9%) and GS results (73.0%) indicative of significant GABAb. Moderate specificity was also observed when predicting GS (62%) and FTSS (62.3%); a low to moderate specificity was observed when predicting TUG (50.0%).

Conclusion

A FES-I score of 23.5 or more showed high specificity in identifying those with prolonged TUG and FTSS and slower GS, with moderate specificity.