bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microclimate buffering varies across forest types during an extreme heat event
Authors: John Aji , Pradhan Kavya , Case Michael J. , Ettinger Ailene K. , Hille Ris Lambers Janneke 
Published: October 2023

AbstractIncreasing temperatures and extreme heat episodes have become more common with climate change. While forests are known to be buffered from increasing temperatures compared to non-forested areas, whether this buffering is maintained under extreme temperature events, how such events influence forests, and how forest organisms respond to extreme heat is relatively unknown. Here we assess the effects of an extreme heat event (the Pacific Northwest (PNW) heatdome in June 2021) on forest microclimates, forests, and the organisms living within them. We first asked how the PNW heatdome affected microclimates in forests with differing canopy cover (including non-forests) and found that the buffering capacity of forests is greater under denser canopies, even under extreme heat events. We then combined this information with organismal temperature tolerance curves for 12 relevant species and found that canopy buffering can minimize the negative impacts of even extreme heat events on understory organisms, with greater canopy density providing greater microclimate moderation. Finally, we analyzed seasonal NDVI trends in recent years, and found signs of canopy stress following the extreme 2021 heat event. In all, this suggests that although forest canopies may buffer the negative effects of extreme heat events on understory organisms, a greater frequency of extreme heat events may threaten this capacity by damaging forest canopies.
Ranking of cell clusters in a single-cell RNA-sequencing analysis framework using prior knowledge
Authors: Oulas Anastasis , Savva Kyriaki , Karathanasis Nestoras , Spyrou George M 
Published: October 2023

AbstractPrioritization or ranking of different cell types in a scRNA-Seq framework can be performed in a variety of ways, some of these include: i) obtaining an indication of the proportion of cell types between the different conditions under study, ii) counting the number of differentially expressed genes (DEGs) between cell types and conditions in the experiment or, iii) prioritizing cell types based on prior knowledge about the conditions under study (i.e., a specific disease). These methods have drawbacks and limitations thus novel methods for improving cell ranking are required. Here we present a novel methodology that exploits prior knowledge in combination with expert-user information to accentuate cell types from a scRNA-seq analysis that yield the most biologically meaningful results. Prior knowledge is incorporated in a standardized, structured manner, whereby a checklist is attained by querying MalaCards human disease database with a disease of interest. The checklist is comprised of pathways and drugs and, optionally, drug mode of actions (MOAs), associated with the disease. The user is prompted to “edit” this checklist by removing or adding terms (in the form of keywords) from the list of predefined terms. Our methodology has substantial advantages to more traditional cell ranking techniques and provides an informative complementary methodology that utilizes prior knowledge in a rapid and automated manner, that has previously not been attempted by other studies. The current methodology is also implemented as an R package entitled Single Cell Ranking Analysis Toolkit (scRANK) and is available for download and installation via GitHub (https://#hub.com/aoulas/scRANK)Author SummarySingle-cell RNA Sequencing (scRNA-Seq) provides an additive resolution down to the cellular level that was previously not available from traditional “Bulk” RNA sequencing experiments. However, it is often difficult to prioritize the specific cell-types which are primarily responsible for the cause of a disease. This work presents a novel methodology that exploits prior knowledge for a disease in combination with expert-user information to accentuate cell types from a scRNA-seq analysis that are most closely related to the molecular mechanism of a disease of interest. Prior knowledge is incorporated in a standardized, structured manner, whereby a checklist is attained by querying a human disease database called MalaCards. This checklist comes in the form of pathways and drugs and, optionally, drug mode of actions (MOAs), associated with the disease. The expert-user is prompted to “edit” the prior knowledge checklist by removing or adding terms from the list of predefined terms.This methodology has substantial advantages to more traditional cell prioritizing or ranking techniques and provides an informative complementary methodology that utilizes prior knowledge in a rapid and automated manner.
Branching architecture affects genetic diversity within an individual tree
Authors: Tomimoto Sou , Iwasa Yoh , Satake Akiko 
Published: October 2023

AbstractPremiseWhile a tree grows over many years, somatic mutations accumulate and generate a genetically diverse individual. Trees can transmit such mutations to subsequent generations, potentially enhancing the genetic diversity of the population. We study a mathematical model to understand the relationship between within-individual genetic variation and branching architecture.MethodsWe generate branching architecture by repeatedly adding two new branches (main and lateral daughter branches) to each terminal branch (mother branch). Tree shape is determined by two key parameters: daughter-mother ratio (DM) and main-lateral ratio (ML). During branch elongation, somatic mutations accumulate in the stem cells of a shoot apical meristem (SAM) at the tip of each branch. In branching, all the stem cells are passed on from the mother to the main daughter branch, but only one stem cell is chosen for the lateral daughter branch. We evaluate genetic variation by, the mean genetic differences between all pairs of branches of a tree, and examine howvaries with DM and ML while keeping the total branch length constant.Key results and Conclusions(1)attains the maximum for an intermediate DM, when stem cells in the SAM are genetically homogeneous; (2)decreases monotonically with DM when stem cells are genetically heterogeneous; and (3)increases monotonically with ML. Even though the total branch length remains constant, the within-individual genetic variation differs substantially. The results demonstrate the importance of branching architecture in storing genetic diversity.
Reducing work-load of pathotype and gene detection inKlebsiella pneumoniaeby leveraging machine learning
Authors: Sanikhani Rahimeh , Kiani Kourosh Alizadeh , Soroush Mehdi , Moeinirad Mohammad , Sanikhani Seyed Ahmad , Beheshti Masoumeh , Tavakoli Sajad , Badmasti Farzad , Sadati Seyed Hossein 
Published: October 2023

AbstractBackgroundThe growing prevalence of carbapenem resistance has caused an increasing number of bacterial isolates with multi-drug resistance features, especially in theEnterobacteriaceaefamily.Klebsiella pneumoniae, as one of the important members of theEnterobacteriaceaefamily, causes serious infections, which has attracted the attention of scientists due to the emergence of hypervirulent pathotypes with increasing antibiotic resistance and has been raised as a major concern worldwide. Early detection of this new super bacterium and its antibiotic resistance is of great help in reducing mortality and costs. The lack of new antibiotic options underscores the need to optimize current diagnostics. Therefore, this study was designed to leverage machine-learning approach for optimized selection of crucial antibiotics to reduce the experiments needed for the detection of pathotypes and genes’ presence in two classical and hypervirulentK. pneumoniaepathotypes.Methods341 non-duplicate clinical isolates ofK. pneumoniaewere collected from five university hospitals in Tehran and Qazvin, Iran. Pathotype differentiation of classical (cKp) and hypervirulentK.pneumoniae(hvKp) was done by PCR method by two molecular biomarkers includingiucandiut. After identifying the phenotypic antibiotic resistance, the presence of antibiotic resistance genes was detected by PCR method. Then, the relevance of resistance/susceptibility of the antibiotics and presence of pathotypes, aerobactin, and beta-lactamase genes was investigated and analyzed using five supervised machine learning algorithms by selecting crucial antibiotics through feature selection methods.ResultsAmong the 341K.pneumoniaeisolates, 102 and 239 isolates were hvKpand cKprespectively. The highest rate of antibiotic resistance after ampicillin (100%) was related to cefotaxime (76.2%) and the lowest rate of resistance was found in meropenem (24.3%). Imipenem, Meropenem, Aztreonam, Ceftazidime, Ceftriaxone, and Gentamicin are crucial antibiotics for detection of the pathotypes and the aerobactin genes. Moreover, Cefotaxime, Ciprofloxacin, Cefepime, Meropenem, and Imipenem are essential for detection of the beta-lactamase genes.ConclusionImplementing a machine learning approach including various feature selection methods and algorithms, results in less-required experiments on more limited antibiotics to detect genes and pathotypes. Our findings reveal that using machine learning in the prediction of the presence of genes and pathotypes of clinical isolates was a suitable method in terms of rapidity and cost-efficiency on top of accuracy.
IDR-induced CAR condensation improves the cytotoxicity of CAR-Ts against low-antigen cancers
Authors: Zhang Xinyan , Xiao Qian , Zeng Longhui , Hashmi Fawzaan , Su Xiaolei 
Published: October 2023

SummaryChimeric antigen receptor (CAR)-T cell-based therapies demonstrate remarkable efficacy for the treatment of otherwise intractable cancers, particularly B-cell malignancies. However, existing FDA-approved CAR-Ts are limited by low antigen sensitivity, rendering their insufficient targeting to low antigen-expressing cancers. To improve the antigen sensitivity of CAR-Ts, we engineered CARs targeting CD19, CD22, and HER2 by including intrinsically disordered regions (IDRs) that promote signaling condensation. The “IDR CARs” triggered enhanced membrane-proximal signaling in the CAR-T synapse, which led to an increased release of cytotoxic factors, a higher killing activity towards low antigen-expressing cancer cells in vitro, and an improved anti-tumor efficacy in vivo. No elevated tonic signaling was observed in IDR CAR-Ts. Together, we demonstrated IDRs as a new tool set to enhance CAR-T cytotoxicity and to broaden CAR-T’s application to low antigen-expressing cancers.
Digenic variant interpretation with hypothesis-driven explainable AI
Authors: Paoli Federica De , Nicora Giovanna , Berardelli Silvia , Gazzo Andrea , Bellazzi Riccardo , Magni Paolo , Rizzo Ettore , Limongelli Ivan , Zucca Susanna 
Published: October 2023

AbstractMotivationThe digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing digenic combinations based on the proband’s phenotypic profiles and familial information can provide valuable assistance to clinicians during the diagnostic process.ResultsWe have developed diVas, a hypothesis-driven machine learning approach that can effectively interpret genomic variants across different gene pairs. DiVas demonstrates strong performance both in classifying and prioritizing causative pairs, consistently placing them within the top positions across 11 real cases (achieving 73% sensitivity and a median ranking of 3). Additionally, diVas exploits Explainable Artificial Intelligence (XAI) to dissect the digenic disease mechanism for predicted positive pairs.Availability and ImplementationPrediction results of the diVas method on a high-confidence, comprehensive, manually curated dataset of known digenic combinations are available atoliver.engenome.com.
Aedes aegyptiin Maryland: The need for elevated vector surveillance at the face of a dynamic climate
Authors: Faiman Roy , Goodwin Autumn , Cave-Stevens Jaykob , Schultz Alyssa , Brey Jewell , Ford Tristan 
Published: October 2023

AbstractWe report the collection of threeAedes aegyptiadult female mosquitoes in a Rockville, Maryland backyard in late July, 2023, followed by the emergence of 15 adults collected as larvae in a residential backyard in Baltimore, Maryland in mid-September, 2023.Aedes aegyptiis a species primarily associated with tropical and subtropical regions, known for its significance as a vector of arboviruses, including Yellow Fever, Dengue, Zika, and Chikungunya among others. In the continental United States,Ae. aegyptipopulations are mostly found in the southeast, and in several isolated locations such as southern California and Arizona. This finding raises questions about the potential establishment and survival ofAe. aegyptiin temperate climates, emphasizing the critical importance of robust vector surveillance programs in preventing potential outbreaks of vector-borne diseases in regions not traditionally considered endemic for this species.
Evolution of sex-biased gene expression during transitions to separate sexes in theSilenegenus
Authors: Prentout Djivan , Muyle Aline , Zemp Niklaus , el Filali Adil , Boussau Bastien , Touzet Pascal , Widmer Alex , Käfer Jos , Marais Gabriel A.B. 
Published: October 2023

AbstractSexual dimorphism is widespread among species with separate sexes and its extent is thought to be governed by the differential expression of thousands of genes between males and females (known as Sex-Biased Genes, hereafter SBGs). SBGs have been studied in numerous species, but rarely in a comparative way, which curtails our understanding of their evolution, especially during multiple independent transitions to separate sexes. We sequenced the transcriptomes of nine dioecious species, two gynodioecious species (separate females and hermaphrodites) and two hermaphrodite species from theSilenegenus. Our dataset provides access to three independent transitions to dioecy (dating from less than 1 Myo to about 11 Myo). We demonstrated that male-biased expression emerges first during a transition to separate sexes, later followed by female-biased genes. Furthermore, we showed that, despite a mixture of selective regimes, positive selection significantly affects the evolution of some SBGs. Overall, this study provides new insights on the causes of SBG evolution during transitions to separate sexes.TeaserThis study describes the evolution of sex-biased gene expression during a transition to separate sexes in plants.
Global RNA interactome of nitrogen starvedEscherichia coliuncovers a conserved post-transcriptional regulatory axis required for optimal growth recovery
Authors: McQuail Josh , Matera Gianluca , Gräfenhan Tom , Bischler Thorsten , Haberkant Per , Stein Frank , Vogel Jörg , Wigneshweraraj Sivaramesh 
Published: October 2023

ABSTRACTThe RNA binding protein Hfq has a central role in the post-transcription control of gene expression in many bacteria. Numerous studies have mapped the transcriptome-wide Hfq-mediated RNA-RNA interactions in growing bacteria or bacteria that have entered short-term growth-arrest. To what extent post-transcriptional regulation underpins gene expression in growth-arrested bacteria remains unknown. Here, we used nitrogen (N) starvation as a model to study the Hfq-mediated RNA interactome asEscherichia colienter, experience, and exit long-term growth arrest. We observe that the Hfq-mediated RNA interactome undergoes extensive changes during N starvation, with the conserved SdsR sRNA making the most interactions with different mRNA targets exclusively in long-term N-starvedE. coli. Taking a proteomics approach, we reveal that in growth-arrested cells SdsR influences gene expression far beyond its direct mRNA targets. We demonstrate that the absence of SdsR significantly compromises the ability of the mutant bacteria to recover growth competitively from the long-term N-starved state and uncover a conserved post-transcriptional regulatory axis which underpins this process.
Inhibitory synaptic transmission is impaired in the Kölliker-Fuse of male, but not female, Rett Syndrome Mice
Authors: Whitaker-Fornek Jessica R. , Jenkins Paul M. , Levitt Erica S. 
Published: October 2023

AbstractRett Syndrome (RTT) is a severe neurodevelopmental disorder that mainly affects girls and women due to silencing mutations in the X-linkedMECP2gene. One of the most troubling symptoms of RTT is breathing irregularity, including apneas, breath-holds, and hyperventilation. Mice with silencing mutations inMecp2exhibit breathing abnormalities similar to human patients and serve as useful models for studying mechanisms underlying breathing problems in RTT. Previous work implicated the pontine, respiratory-controlling Kölliker-Fuse (KF) in the breathing problems in RTT. The goal of this study was to test the hypothesis that inhibitory synaptic transmission is deficient in KF neurons from symptomatic male and female RTT mice. We performed whole-cell voltage-clamp recordings from KF neurons in acute brain slices to examine pharmacologically isolated, spontaneous and electrically evoked inhibitory post-synaptic currents (IPSCs) in RTT mice and age- and sex-matched wild type mice. The frequency of spontaneous IPSCs was reduced in KF neurons from male RTT mice, but not female RTT mice. In addition, electrically evoked IPSCs were less reliable in KF neurons from male RTT mice, but not female RTT mice. KF neurons from male RTT mice were also more excitable and exhibited shorter duration action potentials. Increased excitability of KF neurons from male mice was not explained by changes in axon initial segment length. These findings indicate impaired inhibitory neurotransmission and increased excitability of KF neurons in male, but not female RTT mice, and suggest that sex-dependent mechanisms contribute to breathing problems in RTT.New and NoteworthyKölliker-Fuse (KF) neurons in acute brain slices from male Rett syndrome (RTT) mice receive reduced inhibitory synaptic inputs compared with wild type littermates. In female RTT mice, inhibitory transmission was not different in KF neurons compared with controls. The results from this study show that sex-specific alterations in synaptic transmission occur in the KF of RTT mice.Graphical Abstract
Parallel nonfunctionalization of CK1δ/ε kinase ohnologs following a whole-genome duplication event
Authors: Evans-Yamamoto Daniel , Dubé Alexandre K , Saha Gourav , Plante Samuel , Bradley David , Gagnon-Arsenault Isabelle , Landry Christian R 
Published: October 2023

AbstractWhole genome duplication (WGD) followed by speciation allows us to examine the parallel evolution of ohnolog pairs. In the yeast familySaccharomycetaceae,HRR25is a rare case of repeated ohnolog maintenance. This gene has reverted to a single copy inS. cerevisiaewhere it is now essential, but has been maintained as pairs in at least 7 species post WGD. InS. cerevisiae,HRR25encodes the casein kinase (CK) 1δ/ε and plays a role in a variety of functions through its kinase activity and protein-protein interactions (PPIs). We hypothesized that the maintenance of duplicatedHRR25ohnologs could be a result of repeated subfunctionalization. We tested this hypothesis through a functional complementation assay inS. cerevisiae, testing all pairwise combinations of 25 orthologs (including 7 ohnolog pairs). Contrary to our expectations, we observed no cases of pair-dependent complementation, which would have supported the subfunctionalization hypothesis. Instead, most post-WGD species have one ohnolog that failed to complement, suggesting their nonfunctionalization or neofunctionalization. The ohnologs incapable of complementation have undergone more rapid protein evolution, lost most PPIs that were observed for their functional counterparts and singletons from post and non-WGD species, and have non-conserved cellular localization, consistent with their ongoing loss of function. The analysis inN. castellishows that the non-complementing ohnolog is expressed at a lower level and has become non-essential. Taken together, our results indicate thatHRR25orthologs are undergoing gradual nonfunctionalization.
Single-fly assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life
Authors: Kim Bernard Y. , Gellert Hannah R. , Church Samuel H. , Suvorov Anton , Anderson Sean S. , Barmina Olga , Beskid Sofia G. , Comeault Aaron A. , Nicole Crown K. , Diamond Sarah E. , Dorus Steve , Fujichika Takako , Hemker James A. , Hrcek Jan , Kankare Maaria , Katoh Toru , Magnacca Karl N. , Martin Ryan A. , Matsunaga Teruyuki , Medeiros Matthew J. , Miller Danny E. , Pitnick Scott , Simoni Sara , Steenwinkel Tessa E. , Schiffer Michele , Syed Zeeshan A. , Takahashi Aya , Wei Kevin H-C. , Yokoyama Tsuya , Eisen Michael B. , Kopp Artyom , Matute Daniel , Obbard Darren J. , O’Grady Patrick M. , Price Donald K. , Toda Masanori J. , Werner Thomas , Petrov Dmitri A. 
Published: October 2023

AbstractLong-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.