bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ensemble Clustering Combined with Clustering Optimization – A Novel Workflow for Analyzing Metabolomics Data
Authors: Hislop Brady D. , Heveran Chelsea M. , June Ronald K. 
Published: November 2022

AbstractMetabolomic studies have improved the understanding of a broad range of biological tissues, fluids, and systems. Typically, metabolomic analyses employ a workflow that starts with detecting peaks from mass spectrometry data and is followed by a series of statistical analysis aimed at identifying dysregulated metabolites, group differences, and group similarities in dysregulated metabolites and pathways. Generating these group similarities relies on clustering analyses. However, current clustering methods are highly subjective and can be prone to errors, indicating the need for an updated workflow that improves upon these issues. Here we present a novel metabolomics workflow that can produce unbiased, reproducible clustering results: ensemble clustering combined with cluster optimization (ECCO). The first step, clustering optimization, is used to identify an optimal number of clusters without bias. The second step, ensemble clustering, is then performed by finding the consensus clustering solution across thirteen distance algorithms. This step improves the repeatability of analyses and eliminates bias through eliminating the need to choose one distance algorithm in clustering solutions. We employ ECCO to analyze synovial fluid metabolites from patients with early and late osteoarthritis (OA). This method improves upon the detection of distinct metabolomic endotypes compared with conventional analyses. Furthermore, novel pathways were identified corresponding with different stages of OA. These results demonstrate the utility of ECCO in metabolomics workflows that involve clustering data. ECCO, which we provide as an open-source tool, can improve the repeatability, reliability, and ease-of-use of metabolomics analyses, and is therefore expected to increase the confidence of biological interpretation from these data.
Ancient dolphin genomes reveal rapid repeated adaptation to coastal waters
Authors: Louis Marie , Korlević Petra , Nykänen Milaja , Archer Frederick , Berrow Simon , Brownlow Andrew , Lorenzen Eline D. , O’Brien Joanne , Post Klaas , Racimo Fernando , Rogan Emer , Rosel Patricia E. , Sinding Mikkel H. S. , van der Es Henry , Wales Nathan , Fontaine Michael C. , Gaggiotti Oscar , Foote Andrew D. 
Published: November 2022

AbstractParallel evolution provides among the strongest evidence of the role of natural selection in shaping adaptation to the local environment. Yet, the chronology, mode and tempo of the process of parallel evolution remains broadly debated and discussed in the field of evolutionary biology. In this study, we harness the temporal resolution of paleogenomics to understand the tempo and independence of parallel coastal ecotype adaptation in common bottlenose dolphins (Tursiops truncatus). For this, we generated whole genome resequencing data from subfossil dolphins (8,610-5,626 years BP) originating from around the formation time of new coastal habitat and compared them with data from contemporary populations. Genomic data revealed a shift in genetic affinity, with the oldest ancient sample being closer to the pelagic populations, while the younger samples had intermediate ancestry that showed greater affinity with the local contemporary coastal populations. We found coastal-associated genotypes in the genome of our highest coverage ancient sample, SP1060, providing rare evidence of rapid adaptation from standing genetic variation. Lastly, using admixture graph analyses, we found a reticulate evolutionary history between pelagic and coastal populations. Ancestral gene flow from coastal populations was the probable source of standing genetic variation present in the pelagic populations that enabled rapid adaptation to newly emerged coastal habitat. The genetic response to past climatic warming provides an understanding of how bottlenose dolphins will respond to ongoing directional climate change and shifting coastlines.
Description ofGloeomargarita ahousahtiaesp. nov., a thermophilic member of the order Gloeomargaritales with intracellular carbonate inclusions
Authors: Bacchetta Thomas , López-García Purificación , Gutiérrez-Preciado Ana , Mehta Neha , Skouri-Panet Feriel , Benzerara Karim , Ciobanu Maria , Yubuki Naoji , Tavera Rosaluz , Moreira David 
Published: November 2022

ABSTRACTA unicellular cyanobacterium, strain VI4D9, was isolated from thermophilic microbial mats thriving in a hot spring of the Ahousaht territory of Vancouver Island, Canada. The cells were elongated rods (5.1 μm in length and 1.2 μm in width on average). Their UV-visible absorption spectra revealed that they contain chlorophylla, phycocyanin, and carotenoids. Transmission electron microscopy showed the presence of thylakoids concentrated on one side of the cells. The strain grew within a temperature range of 37–50°C, with an optimum at 45°C. Its genome had a size of 3,049,282 bp and a DNA G+C content of 51.8 mol%. The cells contained numerous intracellular spherical granules easily visible under scanning electron microscopy. Energy-dispersive x-ray spectroscopy revealed that these granules were made of Ca-, Ba- and Sr-containing carbonates. A phylogenetic 16S rRNA gene tree robustly placed this strain as sister to several environmental sequences and the described speciesGloeomargarita lithophora, also characterized by the possession of intracellular carbonate inclusions. We consider strain VI4D9 to represent a newGloeomargaritaspecies based on its marked phenotypic differences withG. lithophora, notably, its thermophilic nature and different thylakoid organization. We propose the nameGloeomargarita ahousahtiaesp. nov. for this newly isolated thermophilic cyanobacterium. The type strain is VI4D9 (Culture Collection of Algae and Protozoa strain 1472/1; Laboratorio de Algas Continentales Mexico strain LAC 140).G. ahousahtiaeis the second species described within the recently discovered order Gloeomargaritales.
Chromosome-scale scaffolding of the fungus gnat genome (Diptera:Bradysia coprophila)
Authors: Urban John M. , Gerbi Susan A. , Spradling Allan C. 
Published: November 2022

ABSTRACTBackgroundThe fungus gnat,Bradysia(Sciara)coprophila, has compelling chromosome biology. Paternal chromosomes are eliminated during spermatogenesis whereas both maternal X sister chromatids are retained. Embryos start with three copies of the X chromosome, but 1-2 copies are eliminated from somatic cells as part of sex determination, and one is eliminated in the germline to restore diploidy. These developmentally normal events present opportunities to study chromosome movements that are unusual in other systems. To support such studies, we previously generated a highly contiguous optical-map-scaffolded long-read assembly (Bcop_v1) of the male somatic genome. However, the scaffolds were not chromosome-scale, the majority of the assembly lacked chromosome assignments, and the order and orientation of the contigs along chromosomes remained unknown.FindingsMale pupae Hi-C data was used to correct, order, and orient the contigs from Bcop_v1 into chromosome-scale scaffolds, producing the updated assembly, Bcop_v2. Several orthogonal analyses allowed us to (i) identify the corresponding chromosome for each scaffold, (ii) orient them with respect to polytene maps, and (iii) determine that they were highly concordant with the chromosomes they represent. Gene annotations produced for Bcop_v1 were lifted over to Bcop_v2. Chromosomal repeat distributions highlight a potential telomeric sequence. Finally, the Hi-C data shed new light on three “fold-back regions” seen to physically interact in images of polytene X chromosomes.ConclusionsStudies of the unusual chromosome movements inBradysia coprophilawill benefit from the updated assembly (Bcop_v2) where each somatic chromosome is represented by a single scaffold.
Adapting protein language models for rapid DTI prediction
Authors: Sledzieski Samuel , Singh Rohit , Cowen Lenore , Berger Bonnie 
Published: November 2022

AbstractWe consider the problem of sequence-based drug-target interaction (DTI) prediction, showing that a straightforward deep learning architecture that leverages pre-trained protein language models (PLMs) for protein embedding outperforms state of the art approaches, achieving higher accuracy, expanded generalizability, and an order of magnitude faster training. PLM embeddings are found to contain general information that is especially useful in few-shot (small training data set) and zero-shot instances (unseen proteins or drugs). Additionally, the PLM embeddings can be augmented with features tuned by task-specific pre-training, and we find that these task-specific features are more informative than baseline PLM features. We anticipate such transfer learning approaches will facilitate rapid prototyping of DTI models, especially in low-N scenarios.
Contrasting drugs from decoys
Authors: Sledzieski Samuel , Singh Rohit , Cowen Lenore , Berger Bonnie 
Published: November 2022

AbstractProtein language models (PLMs) have recently been proposed to advance drugtarget interaction (DTI) prediction, and have shown state-of-the-art performance on several standard benchmarks. However, a remaining challenge for all DTI prediction models (including PLM-based ones) is distinguishing true drugs from highly-similar decoys. Leveraging techniques from self-supervised contrastive learning, we introduce a second-generation PLM-based DTI model trained on triplets of proteins, drugs, and decoys (small drug-like molecules that do not bind to the protein). We show that our approach,CON-Plex, improves specificity while maintaining high prediction accuracy and generalizability to new drug classes. CON-Plex maps proteins and drugs to a shared latent space which can be interpreted to identify mutually-compatible classes of proteins and drugs. Data and code are available athttps://zenodo.org/record/7127229.
Extraintestinal survival and host immune response toVibrio cholerae
Authors: Agyei Foster K. , Adade Nana E. , Anabire Nsoh G. , Appiah Vincent , Bediako Yaw , Duodu Samuel 
Published: November 2022

AbstractVibrio choleraeis best known to cause the deadly disease cholera. However, in recent years this bacterial pathogen has been found to invade intestinal layers and translocate into the bloodstream of humans. The aim of this study was to investigate the molecular basis ofV. choleraebacteremia. Nine (9) strains ofV. cholerae; six (6) environmental strains of non-O1/non-O139 serogroup and three (3) clinical strains of O1 serogroup and El-Tor serotype were screened for survival in serum obtained from immunocompromised patients. Serum from immunocompetent individuals with no known underlying conditions were used as healthy controls. Five (5) environmental strains and one (1) clinical strain ofV. choleraewere identified to survive the bactericidal action of serum. Whole genome sequence analysis revealed the cholix toxin (ChxA) and genes encoding for siderophores(FepEandEntD) as possible virulence factors used by the environmental strains to cause invasive bloodstream infection. Peripheral blood mononuclear cells (PBMCs) stimulated withV. choleraerevealed increased expression of some cytokines; IL-1ß and IL-13 and the chemokine; RANTES especially among diabetics. The present study illustrates the potential survival ofV. choleraein blood, which could be aided by scavenging for iron from their host leading to severe infections.
Machine Learning Workflow for Single-Cell Antimicrobial Susceptibility Testing ofKlebsiella pneumoniaeto Meropenem in Sub-Doubling Time
Authors: Tjandra Kristel C. , Ram-Mohan Nikhil , Roshardt Manuel , Zudock Elizabeth , Qu Zhaonan , Mach Kathleen E. , Eminaga Okyaz , Liao Joseph C. , Yang Samuel , Wong Pak Kin 
Published: November 2022

AbstractMultidrug-resistantEnterobacteriaceaeare among the most urgent global public health threats associated with various life-threatening infections. In the absence of a rapid method to identify antimicrobial susceptibility, empirical use of broad-spectrum antimicrobials such as carbapenem monotherapy has led to the spread of resistant organisms. Rapid determination of antimicrobial resistance is urgently needed to overcome this issue. By capturing dynamic single-cell morphological features of over thirty-nine thousand cells from nineteen strains ofKlebsiella pneumoniae, we evaluated strategies based on time and concentration differentials for classifying its susceptibility to a commonly used carbapenem, meropenem, and predicting their minimum inhibitory concentrations (MIC). We report morphometric antimicrobial susceptibility testing (MorphoAST), an image-based machine learning workflow, for rapid determination of antimicrobial susceptibility by single-cell morphological analysis within sub-doubling time. We demonstrated that our algorithm has the ability to predict MIC/antimicrobial susceptibility in a fraction of the bacterial doubling time (<50 min.). The classifiers achieved as high as 97% accuracy in 20 minutes (two-fifths of the doubling time) and reached over 99% accuracy within 50 minutes (one doubling time) in predicting the antimicrobial response. A regression model based on the concentration differential of individual cells from nineteen strains predicted the MIC with 100% categorical agreement and essential agreement for seven unseen strains, including two clinical samples from patients with urinary tract infections with different responsiveness to meropenem. The expansion of this innovation to other drug-bug combinations could have significant implications for future development of rapid antimicrobial susceptibility testing.
Reward prediction error neurons implement an efficient code for reward
Authors: Schütt Heiko H. , Kim Dongjae , Ma Wei Ji 
Published: November 2022

AbstractWe use efficient coding principles borrowed from sensory neuroscience to derive the optimal population of neurons to encode rewards from a probability distribution. We find that the response properties of dopaminergic reward prediction error neurons in a rodent and a primate data set are similar to those of the efficient code in many ways: the neurons have a broad distribution of midpoints covering the reward distribution; neurons with higher thresholds have higher gains, more convex tuning functions, and lower slopes; moreover, their slope is higher when the reward distribution is narrower. Furthermore, we derive learning rules that converge to this efficient code; the learning rule for the position of the neuron on the reward axis closely resembles the learning rule of distributional reinforcement learning. Thus, reward prediction error neuron responses may be optimized to broadcast an efficient reward signal, forming a connection between efficient coding and reinforcement learning, two of the most successful theories in computational neuroscience.
Evolutionary rescue in a fluctuating environment
Authors: Marrec Loïc , Bank Claudia 
Published: November 2022

AbstractNo environment is constant over time, and environmental fluctuations impact the outcome of evolutionary dynamics. Survival of a population not adapted to some environmental conditions is threatened unless a mutation rescues it, an eco-evolutionary process termed evolutionary rescue. We here investigate evolutionary rescue in an environment that fluctuates between a favorable state, in which the population grows, and a harsh state, in which the population declines. We develop a stochastic model that includes both population dynamics and genetics. We derive analytical predictions for the mean extinction time of a non-adapted population given that it is not rescued, the probability of rescue by a generalist mutation, and the mean appearance time of a rescue mutant, which we validate using numerical simulations. We find that evolutionary rescue is less (respectively more) likely if the environmental fluctuations are stochastic rather than deterministic and if the mean time between each environmental change is less (respectively more) than the mean survival time of the population in the harsh environment. We demonstrate that high equilibrium population sizes andper capitagrowth rates maximize the chances of evolutionary rescue. We show that an imperfectly harsh environment, which does not fully prevent births but makes the death rate to birth rate ratio much greater than unity, has almost the same rescue probability as a perfectly harsh environment, which fully prevents births. Finally, we put our results in the context of antimicrobial resistance and conservation biology.
Infection-experienced HSPCs protect against infections by generating neutrophils with enhanced bactericidal activity
Authors: Darroch Hannah , Keerthisinghe Pramuk , Sung Yih Jian , Prankerd-Gough Anneke , Crosier Philip S. , Astin Jonathan W. , Hall Christopher J. 
Published: November 2022

SUMMARYHematopoietic stem and progenitor cells (HSPCs) respond to infection by proliferating and generating in-demand neutrophils through a process called emergency granulopoiesis (EG). Recently, infection-induced changes in HPSCs have also been shown to underpin the longevity of trained immunity, where they generate innate immune cells with enhanced responses to subsequent microbial threats. Using larval zebrafish to live image neutrophils and HSPCs we show that infection-experienced HSPCs generate neutrophils with enhanced bactericidal functions. Transcriptomic analysis of EG neutrophils uncovered a previously unknown function for mitochondrial reactive oxygen species in elevating neutrophil bactericidal activity. We also reveal that driving expression of zebrafish C/EBPβ within infection-naïve HSPCs is sufficient to generate neutrophils with similarly enhanced bactericidal capacity. Our work suggests that this demand-adapted source of neutrophils contributes to trained immunity by providing enhanced protection towards subsequent infections. Manipulating demand-driven granulopoiesis may provide a therapeutic strategy to boost neutrophil function and treat infectious disease.
Dynamics of electrical resistance of kombucha zoogleal mats
Authors: Adamatzky Andrew 
Published: November 2022

AbstractWe demonstrated that zoogleal mats of kombucha exhibit spikes of electrical resistance. A kombucha is a sugared tea fermented by a symbiotic community of over twenty species of bacteria and yeasts which produce cellulosic gelatinous zoogleal mats. We recorded electrical resistance of the zoogleal mats via platinum electrodes placed at a distance one centimetre of each other. We found that the mats show temporal variations in electrical resistance in a range 0.13 MOhm to 0.19 MOhm. We discovered spikes of the mats resistance morphologically similar to action potential spikes. Average duration of a resistance spike is 1.8 min, average amplitude is 2.2 kOhm. Average interval between resistance spikes is c. 20 min. The discovered resistive spiking of kombucha mats might indicate on their memfractive properties, and thus open pathways towards prototyping neuromorphic devices with living zoogleal mats.
Integrated analysis of single-cell transcriptome of liver cancer and cirrhosis reveals cell lineage similarity and prognostic-associated subpopulations
Authors: Tong Mengsha , Luo Shijie , Gu Lin , Zhang Zheyang , Liang Chenyu , Tian Jingyi , Huang Huaqiang , Lin Yuxiang , Huang Jialiang 
Published: November 2022

AbstractBackground & AimsLiver cancer is one of the most leading causes of cancer deaths. Cirrhosis is an important risk factor for liver cancer, which is the result of over-fibrosis caused by diffuse and long-term liver damage. Despite extensive research, a systematic study for characterizing similarity between liver cancer and cirrhosis at single cell resolution is still lacking.MethodsWe established a data analysis framework to elucidate cell lineage similarity between liver cancer and cirrhosis to discover prognostic-associated subpopulations. We integrated single-cell transcriptome data from liver samples at normal, cirrhotic and cancer conditions, which totally contained 78,000 cells. Gene regulation analysis, cellular interactions and trajectory analysis were performed to characterize cirrhosis-like cell subpopulations. Bulk transcriptomes were used to discover prognostic-associated subpopulations.ResultsBy aligning cellular subpopulations across different samples, we found remarkable similarity betweenKNG1+hepatocytes in cirrhosis andPGA5+hepatocytes in HCC. Furthermore, gene regulation analysis and cellular interactions implicated E2F1, FOXA2, EGF, CDH and ANGPTL signaling in maintaining cirrhosis-like ecosystem. Strikingly, subpopulations with higher expression of cirrhosis-like signatures were associated with patients’ worse survival.ConclusionsWe revealed a previously unexplored cirrhosis-like ecosystem of liver cancer, which could provide novel biomarkers for therapeutic interventions in HCC. Core analysis modules in this study were integrated into a user-friendly toolkit, SIMscRNA(https://github.com/xmuhuanglab/SIM-scRNA), which could facilitate the exploration of similarity and heterogeneity between precancerous diseases and solid tumors.
Quorum sensing-dependent invasion ofRalstonia solanacearumintoFusarium oxysporumchlamydospores
Authors: Tsumori Chiaki , Matsuo Shoma , Murai Yuta , Kai Kenji 
Published: November 2022

AbstractStrains ofRalstonia solanacearumspecies complex (RSSC), though known as the causative agent of bacterial wilt disease in plants, induce the chlamydospores of many fungi species and invade them through the spores. The lipopeptide ralstonins are the chlamydospore inducers produced by RSSC and are essential for this invasion. However, no mechanistic investigation of this interaction has been conducted. In this study, we report that quorum sensing (QS), which is bacterial cell–cell communication, is important for RSSC to invade the fungusFusarium oxysporum(Fo). ΔphcB, a deletion mutant of QS signal synthase, lost the ability to both produce ralstonins and invadeFochlamydospores. The QS signal methyl 3-hydroxymyristate rescued these disabilities. In contrast, exogenous ralstonin A, while inducingFochlamydospores, failed to rescue the invasive ability. Gene-deletion and -complementation experiments revealed that the QS-dependent production of extracellular polysaccharide (EPS I) is essential for this invasion. The RSSC cells adhered toFohyphae and formed biofilms there before inducing chlamydospores. This biofilm formation was not observed in the EPS I- or the ralstonin-deficient mutant. Microscopic analysis showed that RSSC infection resulted in the death ofFochlamydospores. Altogether, we reported that the RSSC QS system is important for this lethal endoparasitism. Among the factors regulated by the QS system, ralstonins, EPS I, and biofilm are important parasitic factors.SignificanceRSSC strains are Gram-negative bacteria that infect both plants and fungi. ThephcQS system of RSSC is important for parasitism in plants because it allows them to invade and increase within the host by causing appropriate system activation at each infection step. In this study, we confirmed not only the importance of ralstonins asFochlamydospore inducers, but also that of biofilm formation on the hyphae. In addition to ralstonins, EPS I turned out to be important for biofilm formation. The QS system comprehensively controls the production of these factors in the interaction withFo. Due to RSSC infection, the cell membranes and organelles ofFochlamydospores were destroyed, showing that RSSC cells are not endosymbionts but lethal invaders. This result advocates a new QS-dependent mechanism for the process by which a bacterium invades a fungus.