bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ionizing Radiation induces cells with past caspase activity that contribute to the adult organ inDrosophilaand show reduced Loss of Heterozygosity
Authors: Colon Plaza Sarah , Su Tin Tin 
Published: November 2022

AbstractThere is increasing recognition that cells may activate apoptotic caspases but not die, instead displaying various physiologically relevant consequences. We know very little, however, of the mechanisms that underlie the life/death decision in a cell that has activated apoptotic caspases. By optimizing a published reporter for past caspase activity, we were able to visualize cells that survived caspase activation specifically after exposure to ionizing radiation inDrosophilalarval wing discs. We found that cells withX-ray-inducedpastactivecaspases (XPAC) do not arise at random but are born at specific locations within the developing wing imaginal discs ofDrosophilalarvae. We found also that the apoptotic signaling pathway is needed to induce XPAC cells. Yet, XPAC cells appear in stereotypical patterns that do not follow the pattern of IR-induced apoptosis, suggesting additional controls at play. Functional testing identified the contribution ofwingless(DrosophilaWnt1) and Ras signaling to the prevalence of XPAC cells. By following irradiated larvae into adulthood, we found that XPAC cells contribute to the adult wing. To address the relationship between XPAC and genome stability, we combined a reporter for past caspase activity withmwh, an adult marker for Loss of Heterozygosity (LOH). We found a lower incidence of LOH among XPAC compared to cells that did not activate the reporter for past caspase activity. In addition, at time points when wing disc cells are finishing DNA repair, XPAC cells show an anti-correlation with cells with unrepaired IR-induced double-stranded breaks. Our data suggest that non-lethal caspase activity safeguards the genome by facilitating DNA repair and reducing LOH after transient exposure to X-rays. These results identify a physiological role for non-lethal caspase activity during recovery from radiation damage.
HoCoRT: Host contamination removal tool
Authors: Rumbavicius Ignas , Rounge Trine B. , Rognes Torbjørn 
Published: November 2022

AbstractBackgroundShotgun metagenome sequencing data obtained from a host environment will usually be contaminated with sequences from the host organism. Host sequences should be removed before further analysis to avoid biases, to reduce downstream computational load, or for privacy reasons in case of a human host. The tools that we identified as designed specifically to perform host contamination sequence removal were either outdated, not maintained or complicated to use. We have therefore created HoCoRT, a fast and user friendly tool that implements several methods for optimised host sequence removal, and evaluated the speed and accuracy of these methods.ResultsHoCoRT is an open-source command-line tool for host contamination removal. It is designed to be simple to install and use, including a one-step option for genome indexing. HoCoRT uses a range of well-known mapping, classification and alignment methods for the classification of reads. The underlying classification method to be used and its parameters are selectable by the user, enabling adaptation to different circumstances. Based on our investigation of the performance of a range of methods and parameters on artificial human gut and oral microbiomes, recommendations are provided for typical data sets with short and long reads.ConclusionsTo decontaminate a human microbiome with HoCoRT, the best combination of speed and accuracy was found with BioBloom, Bowtie2 in end-to-end mode, or HISAT2 for short reads, while BioBloom performed best for long reads. For the oral microbiome, Bowtie2 was slightly more accurate than the other two, at the expense of speed. HoCoRT using Bowtie2 in end-to-end mode was found to be much faster and slightly more accurate than the dedicated DeconSeq tool. HoCoRT is distributed as a Bioconda package. Source code and documentation are available athttps://github.com/ignasrum/hocortfor Linux and macOS under the MIT licence.
Shear rheology of methyl cellulose based solutions for cell mechanical measurements at high shear rates
Authors: Büyükurgancı Beyza , Basu Santanu Kumar , Neuner Markus , Guck Jochen , Wierschem Andreas , Reichel Felix 
Published: November 2022

AbstractMethyl cellulose (MC) is a widely used material in various microfluidic applications in biology. Due to its biocompatibility, it has become a popular crowding agent for microfluidic cell deformability measurements, which usually operate at high shear rates (> 10,000 s−1). However, a full rheological characterization of methyl cellulose solutions under these conditions has not yet been reported. With this study, we provide a full shear-rheological description for solutions of up to 1% MC dissolved in phosphate-buffered saline (PBS) that are commonly used in real-time deformability cytometry (RT-DC). We characterized three different MC-PBS solutions used for cell mechanical measurements in RT-DC with three different shear rheometer setups to cover a range of shear rates from 0.1 - 150,000 s−1. We report viscosities and normal stress differences in this regime. Viscosity functions can be well described using a Carreau-Yasuda model. Furthermore, we present the temperature dependency of shear viscosity and first normal stress difference of these solutions. Our results show that methyl cellulose solutions behave like power-law liquids in viscosity and first normal stress difference at shear rates between 5,000 - 150,000 s−1. We construct a general viscosity equation for each MC solution at a certain shear rate and temperature. Furthermore, we investigated how MC concentration influences the rheology of the solutions and found the entanglement concentration at around 0.64 w/w%. Our results help to better understand the viscoelastic behavior of MC solutions, which can now be considered when modelling stresses in microfluidic channels.
Identification of genomic regions of dry bean (Phaseolus vulgarisL.) associated with agronomic and physiological traits under drought stressed and well-watered conditions using genome-wide association study
Authors: Mutari Bruce , Sibiya Julia , Shayanowako Admire , Chidzanga Charity , Matova Prince M. , Gasura Edmore 
Published: November 2022

AbstractUnderstanding the genetic basis of traits of economic importance under drought stress (DS) and well-watered (NS) conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgarisL.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An Andean and Mesoamerican diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stress (DS) and well-watered (NS) conditions for two successive seasons. Agronomic and physiological traits,viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the AMDP was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under DS. Population structure analysis revealed two sub-populations, which correspond to the Andean and Mesoamerican gene pools. Markers explained 0.08 – 0.10, 0.22 – 0.23, 0.29 – 0.32, 0.43 – 0.44, 0.65 – 0.66 and 0.69 – 0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under DS conditions. For NS,R2varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10−03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across DS and NS conditions. Most of the identified genes had known biological functions related to regulating the response to moisture stress. The findings provide new insights into the genetic architecture of moisture stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.
All boreal forest successional stages needed to maintain the full suite of soil biodiversity, community composition, and function following wildfire
Authors: Porter Teresita M. , Smenderovac Emily , Morris Dave , Venier Lisa 
Published: November 2022

AbstractWildfire is a natural disturbance in boreal forest systems that has been predicted to increase in frequency, intensity, and extent due to climate change. Most studies tend to assess the recovery of one component of the community at a time but here we use DNA metabarcoding to simultaneously monitor soil bacteria, fungi, and arthropods along an 85-year chronosequence following wildfire in jack pine-dominated ecosites. We describe soil successional and community assembly processes to better inform sustainable forest management practices. Soil taxa showed different recovery trajectories following wildfire. Bacteria shared a large core community across stand development stages (~ 95-97% of their unique sequences) and appeared to recover relatively quickly by crown closure. By comparison fungi and arthropods shared smaller core communities (64-77% and 68-69%, respectively) and each stage appeared to support unique biodiversity. We show the importance of maintaining a mosaic ecosystem that represents each stand development stage to maintain the full suite of biodiversity in soils following wildfire, especially for fungi and arthropods. These results will provide a useful baseline for comparison when assessing the effects of human disturbance such as harvest or for assessing the effects of more frequent wildfire events due to climate change.
Using Attention-based Deep Learning to Predict ERG:TMPRSS2 Fusion Status in Prostate Cancer from Whole Slide Images
Authors: Omar Mohamed , Xu Zhuoran , Rand Sophie B , Mohammad Mohammad , Salles Daniela C. , Schaeffer Edward M. , Robinson Brian D. , Lotan Tamara L. , Loda Massimo , Marchionni Luigi 
Published: November 2022

AbstractProstate cancer (PCa) is associated with several genetic alterations which play an important role in the disease heterogeneity and clinical outcome including gene fusion between TMPRSS2 and members of the ETS family of transcription factors specially ERG. The expanding wealth of pathology whole slide images (WSIs) and the increasing adoption of deep learning (DL) approaches offer a unique opportunity for pathologists to streamline the detection of ERG:TMPRSS2 fusion status. Here, we used two large cohorts of digitized H&E-stained slides from radical prostatectomy specimens to train and evaluate a DL system capable of detecting the ERG fusion status and also detecting tissue regions of high diagnostic and prognostic relevance. Slides from the PCa TCGA dataset were split into training (n=318), validation (n=59), and testing sets (n=59) with the training and validation sets being used for training the model and optimizing its hyperparameters, respectively while the testing set was used for evaluating the performance. Additionally, we used an internal testing cohort consisting of 314 WSIs for independent assessment of the model’s performance. The ERG prediction model achieved an Area Under the Receiver Operating Characteristic curve (AUC) of 0.72 and 0.73 in the TCGA testing set and the internal testing cohort, respectively. In addition to slide-level classification, we also identified highly attended patches for the cases predicted as either ERG-positive or negative which had distinct morphological features associated with ERG status. We subsequently characterized the cellular composition of these patches using HoVer-Net model trained on the PanNuke dataset to segment and classify the nuclei into five main categories. Notably, a high ratio of neoplastic cells in the highly-attended regions was significantly associated with shorter overall and progression-free survival while high ratios of immune, stromal and stromal to neoplastic cells were all associated with longer overall and metastases-free survival. Our work highlights the utility of deploying deep learning systems on digitized histopathology slides to predict key molecular alteration in cancer together with their associated morphological features which would streamline the diagnostic process.
Strong selection is poorly aligned with genetic variation inIpomoea hederacea: implications for divergence and constraint
Authors: Henry Georgia Alexandria , Stinchcombe John R 
Published: November 2022

AbstractThe multivariate evolution of populations is the result of the interactions between natural selection, drift, and the underlying genetic structure of the traits involved. Covariances among traits bias responses to selection, and the multivariate axis which describes the greatest genetic variation is expected to be aligned with patterns of divergence across populations. An exception to this expectation is when selection acts on trait combinations lacking genetic variance, which limits evolutionary change. Here we used a common garden field experiment of individuals from 57 populations ofIpomoea hederaceato characterize linear and nonlinear selection on five quantitative traits in the field. We then formally compare patterns of selection to previous estimates of within population genetic covariance structure (the G-matrix) and population divergence in these traits. We found that selection is poorly aligned with previous estimates of genetic covariance structure and population divergence. In addition, the trait combinations favoured by selection were generally lacking genetic variation, possessing approximately 15- 30% as much genetic variation as the most variable combination of traits. Our results suggest that patterns of population divergence are likely the result of the interplay between adaptive responses, correlated response, and selection favoring traits lacking genetic variation.
Epigenetic and genetic differentiation betweenCoregonusspecies pairs
Authors: Venney Clare J , Mérot Claire , Normandeau Eric , Rougeux Clément , Laporte Martin , Bernatchez Louis 
Published: November 2022

AbstractPhenotypic diversification is classically associated with genetic differentiation and gene expression variation. However, increasing evidence suggests that DNA methylation is involved in evolutionary processes due to its phenotypic and transcriptional effects. Methylation can increase mutagenesis and could lead to increased genetic divergence between populations experiencing different environmental conditions for many generations, though there has been minimal empirical research on epigenetically induced mutagenesis in diversification and speciation. Whitefish, freshwater members of the salmonid family, are excellent systems to study phenotypic diversification and speciation due to the repeated divergence of benthic-limnetic species pairs serving as natural replicates. Here we investigate whole genome genetic and epigenetic differentiation between sympatric benthic-limnetic species pairs in lake and European whitefish (Coregonus clupeaformisandC. lavaretus) from four lakes (N=64). We found considerable, albeit variable, genetic and epigenetic differences between species pairs. All SNP types were enriched at CpG sites supporting the mutagenic nature of DNA methylation, though C>T SNPs were most common. We also found an enrichment of overlaps between outlier SNPs with the 5% highest FSTbetween species and differentially methylated loci. This could possibly represent differentially methylated sites that have caused divergent genetic mutations between species, or divergent selection leading to both genetic and epigenetic variation at these sites. Our results support the hypothesis that DNA methylation contributes to phenotypic divergence and mutagenesis during whitefish speciation.Significance statementDNA methylation is an epigenetic mark known to change in response to the environment and induce genetic modifications such as point mutations, though its implications for evolution and speciation have not been thoroughly studied. We find considerable but variable genetic and epigenetic variation between whitefish benthic-limnetic species pairs, highlighting the potential for DNA methylation to contribute to mutagenesis and genetic evolution. Our study provides evidence that DNA methylation could have contributed to whitefish speciation, both through initially plastic methylation changes and by driving genetic divergence between species pairs.
A robotic system for automated genetic manipulation and analysis ofCaenorhabditis elegans
Authors: Li Zihao , Fouad Anthony D. , Bowlin Peter D. , Fan Yuying , He Siming , Chang Meng-Chuan , Du Angelica , Teng Christopher , Kassouni Alexander , Ji Hongfei , Raizen David M. , Fang-Yen Christopher 
Published: November 2022

AbstractThe nematodeCaenorhabditis elegansis one of the most widely studied organisms in biology due to its small size, rapid life cycle, and manipulable genetics. Research withC. elegansdepends on labor-intensive and time-consuming manual procedures, imposing a major bottleneck for many studies, especially those involving large numbers of animals. Here we describe the first general-purpose tool, WormPicker, a robotic system capable of performing complex genetic manipulations and other tasks by imaging, phenotyping, and transferringC. eleganson standard agar media. Our system uses a motorized stage to move an imaging system and a robotic arm over an array of plates. Machine vision tools identify animals and assay developmental stage, morphology, sex, expression of fluorescent reporters, and other phenotypes. Based on the results of these assays the robotic arm selectively transfers individual animals using an electrically self-sterilized wire loop, with the aid of machine vision and electrical capacitance sensing. AutomatedC. elegansmanipulation shows reliability and throughput comparable to standard manual methods. We developed software to enable the system to autonomously carry out complex protocols. To validate the effectiveness and versatility of our methods we used the system to perform a collection of commonC. elegansprocedures, including genetic crossing, genetic mapping, and genomic integration of a transgene. Our robotic system will accelerateC. elegansresearch and opens possibilities for performing genetic and pharmacological screens that would be impractical using manual methods.Significance StatementThe nematodeCaenorhabditis elegansis a powerful genetic model organism in life sciences due to its compact anatomy, short life cycle, and optical transparency. Current methods for worm genetics rely on laborious, time-consuming, and error-prone manual work. Here, we describe the first general-purpose automated tool capable of genetically manipulatingC. elegans. Our robotic system will accelerate a broad variety ofC. elegansresearch and opens possibilities for performing genetic and pharmacological screens that would be impractical using manual methods.
Robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing (MGA-Seq)
Authors: Lin Da , Zou Yanyan , Wang Jinyue , Xiao Qin , Lin Fei , Zhang Ningyuan , Teng Zhaowei , Li Shiyi , Wei Yongchang , Zhou Fuling , Yin Rong , Zhang Siheng , Wu Chengchao , Zhang Jing , Hu Sheng , Dong Shuang , Li Xiaoyu , Ye Shengwei , Sun Haixiang , Cao Gang 
Published: November 2022

SUMMARYGenomic abnormalities, including structural variation (SV), copy number variation (CNV), single-nucleotide polymorphism (SNP), homogenously staining regions (HSR) and extrachromosomal DNA (ecDNA), are strongly associated with cancer, rare diseases and infertility. A robust technology to simultaneously detect these genomic abnormalities is highly desired for clinical diagnosis and basic research. In this study, we developed a simple and cost-effective method – multiple genetic abnormality sequencing (MGA-Seq) – to simultaneously detect SNPs, CNVs, SVs, ecDNA and HSRs in a single tube. This method has been successfully applied in both cancer cell lines and clinical tumour samples and revealed that focal amplification in tumour tissue is substantially heterogeneous. Notably, we delineated the architecture of focal amplification and the ecDNA network by MGA-Seq, which facilitated the exploration of the regulation of gene expression in ecDNA. This method could be extensively applied for diagnosis and may greatly facilitate the investigation of the genomic mechanism for genetic diseases.
Engineered molecular sensors of cell surface crowding
Authors: Takatori Sho C. , Son Sungmin , Lee Daniel , Fletcher Daniel A. 
Published: November 2022

AbstractCells mediate interactions with the extracellular environment through a crowded assembly of transmembrane proteins, glycoproteins and glycolipids on their plasma membrane. The extent to which surface crowding modulates the biophysical interactions of ligands, receptors, and other macromolecules is poorly understood due to the lack of methods to quantify surface crowding on native cell membranes. In this work, we demonstrate that physical crowding on reconstituted membranes and live cell surfaces attenuates the effective binding affinity of macromolecules such as IgG antibodies in a surface crowding-dependent manner. We combine experiment and simulation to design a crowding sensor based on this principle that provides a quantitative readout of cell surface crowding. Our measurements reveal that surface crowding decreases IgG antibody binding by 2-20 fold in live cells compared to a bare membrane surface, resulting in a cell surface osmotic pressure opposing binding of 1 - 4 kPa. Our sensors show that sialic acid, a negatively charged monosaccharide, contributes disproportionately to red blood cell surface crowding via electrostatic repulsion, despite occupying only ~1% of the total cell membrane by mass. We also observe significant differences in surface crowding for different cell types and find that expression of single oncogenes can both increase and decrease crowding, suggesting that surface crowding may be an indicator of both cell type and state. Our high-throughput, single-cell measurement of cell surface osmotic pressure may be combined with functional assays to enable further biophysical dissection of the cell surfaceome.Significance StatementCells interact with each other and the extracellular environment through a crowded assembly of polymers on their plasma membranes. The high density of these surface polymers can generate physical crowding that impacts cell function. However, tools to quantify the extent and effect of surface crowding on live cell membranes are lacking. In this work, we design macromolecular sensors that act as direct reporters of cell surface crowding. We combine experiments on reconstituted and live cell surfaces with molecular dynamics simulations to provide a mechanistic understanding of how cell surface crowding reduces binding of soluble molecules, and we show that crowding varies significantly with cell type and is affected by oncogene expression.