bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Bayesian analysis of birth pulse effects on the probability of detecting Ebola virus in fruit bats
Authors: Pleydell David R.J. , Bass Innocent Ndong , Mba Djondzo Flaubert Auguste , Djomsi Dowbiss Meta , Kouanfack Charles , Peeters Martine , Cappelle Julien 
Published: August 2023

AbstractSince 1976 various species of Ebolavirus have caused a series of zoonotic outbreaks and public health crises in Africa. Bats have long been hypothesised to function as important hosts for ebolavirus maintenance, however the transmission ecology for these viruses remains poorly understood. Several studies have demon-strated rapid seroconversion for ebolavirus antibodies in young bats, yet paradoxically few PCR studies have confirmed the identity of the circulating viral species causing these seroconversions. The current study presents an age-structured epidemiological model that characterises the effects of seasonal birth pulses on ebolavirus transmission within a colony of African straw-coloured fruit bats (Eidolon helvum). Bayesian calibration is performed using previously published serological data collected from Cameroon, and age-structure data from Ghana. The model predicts that annual birth pulses most likely give rise to annual outbreaks, although more complex dynamic patterns – including skip years, multi-annual cycles and chaos – may be possible. Weeks 30 to 31 of each year were estimated to be the most likely period for isolating the circulating virus in Cameroon. The probability that a previous PCR campaign failed to detect Ebola virus, assuming that it was circulating, was estimated to be one in two thousand. This raises questions such as (1) what can we actually learn from ebolavirus serology tests performed without positive controls? (2) are current PCR tests sufficiently sensitive? (3) are swab samples really appropriate for ebolavirus detection? The current results provide important insights for the design of future field studies aiming to detect Ebola viruses from sylvatic hosts, and can contribute to risk assessments concerning the timing of zoonotic outbreaks.
Three Accessory Gene Clusters Drive Host-Adaptation in Group BStreptococcus
Authors: Crestani Chiara , Forde Taya L. , Bell John , Lycett Samantha J. , Oliveira Laura M.A. , Pinto Tatiana C.A. , Cobo-Ángel Claudia G. , Ceballos-Márquez Alejandro , Phuoc Nguyen N. , Sirimanapong Wanna , Chen Swaine L. , Jamrozy Dorota , Bentley Stephen D. , Fontaine Michael , Zadoks Ruth N. 
Published: August 2023

AbstractStreptococcus agalactiae(Group BStreptococcus, GBS) is a major pathogen of humans and animals, posing a threat to human health as well as food security. Here, we investigate the role of genomic mechanisms, including homologous recombination and horizontal gene transfer, in shaping the population structure of GBS and its adaptation to three major host groups (humans, cattle, fishes). We demonstrate that the GBS population comprises host-specialist, host-adapted lineages as well as host generalists, and that these categories differ in their level or recombination. Although the accessory genome at large varies by lineage rather than host, genome wide association studies show that host association is driven by three accessory genome clusters, regardless of lineage or breadth of the host spectrum. These genomic clusters (scpBin human GBS, lactose operon in bovine GBS, Locus 3 in fish GBS) are known (scpB, Lac.2) or shown here (Locus 3) to be functionally relevant and are shared with other streptococcal species occupying the same host niche. These findings demonstrate the importance of considering the role of non-human host species in the evolution of GBS, including high risk clones that may lead to interspecies transmission and affect efficacy of future GBS vaccines.
Residence-colonization trade-off and niche differentiation enable the coexistence ofEscherichia coliphylogroups in healthy humans
Authors: Morel-Journel Thibaut , Lehtinen Sonja , Cotto Olivier , Amia Rafika , Dion Sara , Figueroa Clarisse , Martinson Jonathan , Ralaimazava Pascal , Clermont Olivier , Duval Xavier , Nowrouzian Forough L. , Walk Seth , Denamur Erick , Blanquart François 
Published: August 2023

AbstractDespite extensive literature on the pathogenicity and virulence of the opportunistic pathogenEscherichia coli, much less is known about its ecological and evolutionary dynamics as a commensal in healthy hosts. Based on two detailed longitudinal datasets on the gut microbiota of healthy adult individuals followed over months to years in France and in the USA, we identified a robust trade-off between the ability to establish in a new host (colonization) and the ability to remain in the host (residence). MajorE. colilineages (phylogroups) exhibited similar fitness but a diversity of strategies, from strong colonizers residing for a few days in the gut, to poor colonizers residing for years. Strains with the largest number of extra-intestinal virulence associated genes and highest pathogenicity resided for longest in hosts. Moreover, the residence time of a strain was reduced more strongly when it competed with other strains of the same phylogroup than of different phylogroups, suggesting niche differentiation between them. To investigate the consequences of the trade-off and niche differentiation for coexistence between strains, we developed a discrete-state Markov model describing the dynamics ofE. coliin a population of hosts. We found that the trade-off and niche differentiation acted together as equalizing and stabilizing mechanisms enabling the coexistence of phylogroups over extended periods of time. Our model predicted that a reduction in transmission (e.g. better hygiene) would not alter the balance between phylogroups, while disturbance of the microbiome (e.g. antibiotics) would hinder residents strains such as those of the extra-intestinal pathogenic phylogroup B2.3.
Rapid establishment of a tumor-retained state curtails the contribution of conventional NK cells to anti-tumor immunity in solid cancers
Authors: Dean Isaac , Lee Colin Y.C. , Tuong Zewen K. , Li Zhi , Tibbitt Christopher A. , Willis Claire , Gaspal Fabrina , Kennedy Bethany C. , Matei-Rascu Veronika , Fiancette Rémi , Nordenvall Caroline , Lindforss Ulrik , Baker Syed Murtuza , Stockmann Christian , Sexl Veronika , Carlesso Gianluca , Hammond Scott A. , Dovedi Simon J. , Mjösberg Jenny , Hepworth Matthew R. , Clatworthy Menna R. , Withers David R. 
Published: August 2023

AbstractImmune cell dysfunction within the tumor microenvironment undermines the control of cancer progression. NK cells play critical roles in limiting early tumor growth and metastatic disease, however, established cancers contain a phenotypically distinct, tumor-specific NK cell compartment. The temporal dynamics, mechanistic underpinning and functional significance of this tumor NK pool remains incompletely understood. To address this, we exploited photo-labeling, combined with longitudinal transcriptomic and cellular analyses, to interrogate the fate of NK cells after tumor entry. In multiple murine cancer models we reveal that conventional NK cells are continuously recruited into tumors, but rapidly adopt a distinct phenotypic state with features associated with tissue-residency and complete loss of effector functions (including chemokine and cytokine production and cytotoxicity), within 48-72 hrs of entering the tumor. Depletion of NK cells from established tumors did not alter tumor growth, indicating that intratumoral NK cells cease to actively contribute to anti- tumor responses. Furthermore, comparable NK populations were identified in human colorectal cancers, confirming translational relevance and raising the possibility that interventions to reactivate NK cells within tissues may boost anti-tumor immunity in established cancers. Indeed, administration of IL-15:IL-15Ra complexes prevented the loss of NK cell function and improved tumor control, generating intratumoral NK cells with both enhanced tissue-residency characteristics and effector function. Collectively, our data reveals the fate of cNK cells after recruitment into tumors and provides insight into how intratumoral NK cell functions may be revived.SummaryConventional NK cells recruited from the circulation rapidly establish a tissue-resident phenotype defined by impaired cytotoxicity and chemokine production after tumor entry; administration of IL- 15:IL-15Rα complexes further promotes this tissue-residency programme but maintains core NK cell effector functions within the tumor.
DLTKcat: deep learning based prediction of temperature dependent enzyme turnover rates
Authors: Qiu Sizhe , Zhao Simiao , Yang Aidong 
Published: August 2023

AbstractThe enzyme turnover rate,kcat, quantifies enzyme kinetics by indicating the maximum efficiency of enzyme catalysis. Despite its importance,kcatvalues remain scarce in databases for most organisms, primarily due to the cost of experimental measurements. To predictkcatand account for its strong temperature dependence, DLTKcat was developed in this study and demonstrated superior performance (log10-scale RMSE = 0.88, R2 = 0.66) than previously published models. Through two case studies, DLTKcat showed its ability to predict the effect of protein sequence mutations and temperature changes onkcatvalues. Although its quantitative accuracy is not high enough yet to model the responses of cellular metabolism to temperature changes, DLTKcat has the potential to eventually become a computational tool to describe the temperature dependence of biological systems.
OneFlowTraX: A User-Friendly Software for Super-Resolution Analysis of Single-Molecule Dynamics and Nanoscale Organization
Authors: Rohr Leander , Ehinger Alexandra , Rausch Luiselotte , Burmeister Nina Glöckner , Meixner Alfred J. , Gronnier Julien , Harter Klaus , Kemmerling Birgit , zur Oven-Krockhaus Sven 
Published: August 2023

ABSTRACTSuper-resolution microscopy (SRM) approaches revolutionize cell biology by providing insights into the nanoscale organization and dynamics of macromolecular assemblies and single molecules in living cells. A major hurdle limiting SRM democratization is post-acquisition data analysis which is often complex and time-consuming. Here, we present OneFlowTraX, a user-friendly and open-source software dedicated to the analysis of single-molecule localization microscopy (SMLM) approaches such as single-particle tracking photoactivated localization microscopy (sptPALM). Through an intuitive graphical user interface, OneFlowTraX provides an automated all-in-one solution for single-molecule localization, tracking, as well as mobility and clustering analyses. OneFlowTraX allows the extraction of diffusion and clustering parameters of millions of molecules in a few minutes. Finally, OneFlowTraX greatly simplifies data management following the FAIR (Findable, Accessible, Interoperable, Reusable) principles. We provide a detailed step-by-step manual and guidelines to assess the quality of single-molecule analyses. Applying different fluorophores including mEos3.2, PA-GFP, and PATagRFP, we exemplarily used OneFlowTraX to analyze the dynamics of plant plasma membrane-localized proteins including an aquaporin, the brassinosteroid receptor Brassinosteroid Insensitive 1 (BRI1) and the Receptor-Like Protein 44 (RLP44).
Translation as a Biosignature
Authors: McKaig Jordan M. , Kim MinGyu , Carr Christopher E. 
Published: August 2023

AbstractLife on Earth relies on mechanisms to store heritable information and translate this information into cellular machinery required for biological activity. In all known life, storage, regulation, and translation are provided by DNA, RNA, and ribosomes. Life beyond Earth, even if ancestrally or chemically distinct from lifeas we know itmay utilize similar structures: it has been proposed that charged linear polymers analogous to nucleic acids may be responsible for storage and regulation of genetic information in non-terran biochemical systems. We further propose that a ribosome-like structure may also exist in such a system, due to the evolutionary advantages of separating heritability from cellular machinery. Here, we use a solid-state nanopore to detect DNA, RNA, and ribosomes, and demonstrate that machine learning can distinguish between biomolecule samples and accurately classify new data. This work is intended to serve as a proof of principal that such biosignatures (i.e., informational polymers or translation apparatuses) could be detected, for example, as part of future missions targeting extant life on Ocean Worlds. A negative detection does not imply the absence of life; however, detection of ribosome-like structures could provide a robust and sensitive method to seek extant life in combination with other methods.One Sentence SummaryLife, defined as a chemical system capable of Darwinian evolution, likely requires an apparatus to translate heritable instructions into cellular machinery, and we propose to detect this as a biosignature of extant life beyond Earth.
Short-term fasting of a single amino acid extends lifespan
Authors: Fulton Tahlia L. , Wansbrough Mia R. , Mirth Christen K. , Piper Matthew D. W. 
Published: August 2023

AbstractDiet and health are strongly linked, though the strict changes in diet required to improve health outcomes are usually difficult to sustain. We sought to understand whether short term bouts of amino acid-specific modifications to the diet ofDrosophila melanogastercould mimic the lifespan and stress resistance benefits of dietary restriction, without the requirement for drastic reductions in food intake. We found that flies fed diets lacking the essential amino acid isoleucine, but otherwise nutritionally complete, exhibited enhanced nicotine tolerance, indicating elevated detoxification capacity. The protection from isoleucine deprivation increased with the duration of exposure, up to a maximum at 7-day isoleucine deprivation for flies 2, 3, or 4 weeks of age, and a 5-day deprivation when flies were 5 weeks of age. Because of these beneficial effects on toxin resistance, we intermittently deprived flies of isoleucine during the first 6 weeks of adulthood and monitored the effect on lifespan. Lifespan was significantly extended when flies experienced short term isoleucine deprivation at 3 and 5 weeks of age, regardless of whether they were also deprived at 1 week. These results indicate that short-term bouts of isoleucine deprivation can extend lifespan and highlight its cumulative and time-dependent benefits. Interestingly, we found that isoleucine-deprived flies lost their protection against nicotine within three days of returning to fully fed conditions. Therefore, the mechanisms underlying lifespan extension may involve transient damage clearance during the bouts of isoleucine deprivation rather than sustained enhanced detoxification capacity. These data highlight a new time-restricted, nutritionally precise method to extend life inDrosophila melanogasterand point to a more manageable dietary method to combat ageing.
Ovariectomy-Induced Arterial Stiffening Differs from Vascular Aging and is Reversed by GPER Activation
Authors: Kilanowski-Doroh Isabella M. , McNally Alexandra B. , Wong Tristen , Visniauskas Bruna , Blessinger Sophia A. , Imulinde Sugi Ariane , Richard Chase , Diaz Zaidmara , Horton Alec , Natale Christopher A. , Ogola Benard O. , Lindsey Sarah H. 
Published: August 2023

ABSTRACTArterial stiffness is a cardiovascular risk factor and dramatically increases as women transition through menopause. The current study assessed whether a mouse model of menopause increases arterial stiffness in a similar manner to aging, and whether activation of the G protein-coupled estrogen receptor (GPER) could reverse stiffness. Female C57Bl/6J mice were ovariectomized (OVX) at 10 weeks of age or aged to 52 weeks, and some mice were treated with GPER agonists. OVX and aging increased pulse wave velocity to a similar extent independent of changes in blood pressure. Aging increased carotid wall thickness, while OVX increased material stiffness without altering vascular geometry. RNA-Seq analysis revealed that OVX downregulated smooth muscle contractile genes. The enantiomerically pure GPER agonist, LNS8801, reversed stiffness in OVX mice to a greater degree than the racemic agonist G-1. In summary, OVX and aging induced arterial stiffening via potentially different mechanisms. Aging was associated with inward remodeling while OVX induced material stiffness independent of geometry and a loss of the contractile phenotype. This study helps to further our understanding of the impact of menopause on vascular health and identifies LNS8801 as a potential therapy to counteract this detrimental process in women.
ToxinPred 3.0: An improved method for predicting the toxicity of peptides
Authors: Rathore Anand Singh , Arora Akanksha , Choudhury Shubham , Tijare Purva , Raghava Gajendra P. S. 
Published: August 2023

AbstractToxicity emerges as a prominent challenge in the design of therapeutic peptides, causing the failure of numerous peptides during clinical trials. In 2013, our group developed ToxinPred, a computational method that has been extensively adopted by the scientific community for predicting peptide toxicity. In this paper, we propose a refined variant of ToxinPred that showcases improved reliability and accuracy in predicting peptide toxicity. Initially, we used BLAST for alignment-based toxicity prediction, yet coverage was limited. We adopted a motif-based approach with MERCI software to identify unique toxic patterns. Despite specificity gains, sensitivity was compromised. We developed alignment-free methods using machine/deep learning, achieving a balance sensitivity and specificity of prediction. A deep learning model (ANN – LSTM with fixed sequence length) developed using one-hot encoding attained a 0.93 AUROC and 0.71 MCC on independent data. The machine learning model (extra tree) developed using compositional features of peptides achieved 0.95 AUROC and 0.78 MCC. Lastly, we developed hybrid or ensemble methods combining two or more models to enhance performance. Hybrid approaches, including motif-based and machine learning, achieved a 0.98 AUROC and 0.81 MCC. Evaluation on independent data demonstrated our method’s superiority. To cater to the needs of the scientific community, we have developed a standalone software, pip package and web-based server ToxinPred3 (https://github.com/raghavagps/toxinpred3andhttps://webs.iiitd.edu.in/raghava/toxinpred3/).Author’s BiographyAnand Singh Rathore is currently pursuing a Ph.D. in Computational Biology at the Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Akanksha Arora is currently pursuing a Ph.D. in Computational Biology at the Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Shubham Choudhury is currently pursuing a Ph.D. in Computational Biology at the Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Purava Tijare is a Project Fellow in Computational Biology at the Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.Gajendra P. S. Raghava is currently working as a Professor and Head of the Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.HighlightsImplementation of alignment or similarly based techniques for predicting toxic peptides.Discovery of toxicity-associated patterns and identification of toxic regions in peptides.Development of machine and deep learning-based models for toxicity prediction.Ensemble methods that combine alignment-based and alignment-free methods.Web server and standalone software package for screening toxicity in peptides/proteins.
PRIEST - Predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information
Authors: Saha Gourab , Sawmya Shashata , Akil Md. Ajwad , Saha Arpita , Tasnim Sadia , Rahman Md. Saifur , Rahman M. Sohel 
Published: August 2023

AbstractThe dynamic evolution of the SARS-CoV-2 virus is largely driven by mutations in its genetic sequence, culminating in the emergence of variants with increased capability to evade host immune responses. Accurate prediction of such mutations is fundamental in mitigating pandemic spread and developing effective control measures. In this study, we introduce a robust and interpretable deep-learning approach called PRIEST. This innovative model leverages time-series viral sequences to foresee potential viral mutations. Our comprehensive experimental evaluations underscore PRIEST’s proficiency in accurately predicting immune-evading mutations. Our work represents a substantial step forward in the utilization of deep-learning methodologies for anticipatory viral mutation analysis and pandemic response.
Large-scale analysis of the integration of enhancer-enhancer signals by promoters
Authors: Martinez-Ara Miguel , Comoglio Federico , Steensel Bas van 
Published: August 2023

ABSTRACTGenes are often regulated by multiple enhancers. It is poorly understood how the individual enhancer activities are combined to control promoter activity. Anecdotal evidence has shown that enhancers can combine sub-additively, additively, synergistically, or redundantly. However, it is not clear which of these modes are more frequent in mammalian genomes. Here, we systematically tested how pairs of enhancers activate promoters using a three-way combinatorial reporter assay in mouse cells. By assaying about 69,000 enhancer-enhancer-promoter combinations we found that enhancer pairs generally combine near-additively. This behaviour was conserved across seven developmental promoters tested. Surprisingly, these promoters scale the enhancer signals in a non-linear manner that depends on promoter strength. A housekeeping promoter showed an overall different response to enhancer pairs, and a smaller dynamic range. Thus, our data indicate that enhancers mostly act additively, but promoters transform their collective effect non-linearly.
Alternative mutational architectures producing identical M-matrices can lead to different patterns of evolutionary divergence
Authors: Jiang Daohan , Pennell Matt 
Published: August 2023

AbstractExplaining macroevolutionary divergence in light of population genetics requires understanding the extent to which the patterns of mutational input contribute to long-term trends. In the context of quantitative traits, mutational input is typically described by the mutational variance-covariance matrix, or theM-matrix, which summarizes phenotypic variances and covariances introduced by new mutations per generation. However, as a summary statistic, theM-matrix does not fully capture all the relevant information from the underlying mutational architecture, and there exist infinitely many possible underlying mutational architectures that give rise to the sameM-matrix. Using individual-based simulations, we demonstrate mutational architectures that produce the sameM-matrix can lead to different levels of constraint on evolution and result in difference in within-population genetic variance, between-population divergence, and rate of adaptation. In particular, the rate of adaptation and that of neutral evolution are both reduced when a greater proportion of loci are pleiotropic. Our results reveal that aspects of mutational input not reflected by theM-matrix can have a profound impact on long-term evolution, and suggest it is important to take them into account in order to connect patterns of long-term phenotypic evolution to underlying microevolutionary mechanisms.