bluuebunny/crossref_metadata_2025 huggingface dataset:
Disclosing temperature sensitivity of West Nile virus transmission: novel computational approaches to mosquito-pathogen trait responses
Authors: Heidecke Julian , Wallin Jonas , Fransson Peter , Singh Pratik , Sjödin Henrik , Stiles Pascale , Treskova Marina , Rocklöv Joacim
Published: September 2024

Temperature influences the transmission of mosquito-borne pathogens with significant implications for disease risk in the context of climate change. Mathematical models of mosquito-borne infections rely on functions that capture mosquito-pathogen interactions in response to temperature to better estimate transmission dynamics. To derive these functions, experimental studies provide valuable data on the temperature sensitivity of mosquito life-history traits and pathogen transmission. However, the scarcity of experimental data and inconsistencies in methodologies for analysing and comparing temperature responses across mosquito species and pathogens present challenges to accurately modelling mosquito-borne infections. In this study, we investigated the thermal biology of West Nile virus (WNV), a major mosquito-borne infection. We critically reviewed existing experimental studies, obtaining temperature responses for eight mosquito-pathogen traits across 15 mosquito species. Using this data, we employed Bayesian hierarchical models to estimate temperature response functions for each trait and estimate their variation between species and experiments. We incorporate the resulting functions into mathematical models to estimate the temperature sensitivity of WNV transmission, focusing on six competent mosquito species of the genusCulex. Our study finds similarities in the temperature response amongCulexspecies, with a general optimal transmission temperature around 24°C. We demonstrate that differing mechanistic assumptions in published models can result in a temperature optimum variation exceeding 3°C, underscoring the need for model scrutiny. Additionally, we identify substantial variability between trait temperature responses across experiments on the same mosquito species, indicating significant intra-species variation in trait performance. We provide recommendations for future experimental studies, emphasizing the critical need for additional data on all mosquito-pathogen traits, except for mosquito larva-to-adult development rate and survival, which are relatively well-documented. Incorporating additional data into our multi-species approach enhances the accuracy of temperature trait response estimates. These improvements are critical for forecasting future shifts in mosquito-borne disease risk due to climate change.
Revisiting the taxonomy ofEnterococcus casseliflavusand related species
Authors: Soares de Medeiros Lima Matheus Miguel , Prichula Janira , Sakamoto Tetsu
Published: September 2024

Enterococcus casseliflavus, a commonly mobile and yellow-colored bacterium, is a commensal member of the gastrointestinal tract. It is occasionally found in cases of bacteremia and other human infections. A concern is that all strains of this species have thevanCgene group on their chromosome, which confers resistance to vancomycin. The classification ofE. casseliflavusis challenging, as it presents 99% identity in 16S analysis withE. gallinarumand, mainly, withE. flavescens, often being classified as a single species. This study aimed to revisit the taxonomy ofE. casseliflavusand other related species by carrying out a comprehensive analysis of the genomic data available for these species in public databases.analyzing the genomic data. For this, 155 genomes ofE. casseliflavusrelated species (E. casseliflavus, E. flavescens, E. entomosocium, andE. innesii) were retrieved and submitted to Average Nucleotide Identity (ANI) and phylogenomic analysis. Both approaches showed three well-delineated clusters which correspond to threeEnterococcusspecies (E. casseliflavus, E. flavescensandE. innesii). Here we suggest (1) the removal of synonym status betweenE. flavescensandE. cassliflavus, and (2) addition of synonym status betweenE. entomosociumandE. casseliflavus.
Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD
Authors: Taubenheim Jan , Kadibalban A. Samer , Zimmermann Johannes , Taubenheim Claudia , Tran Florian , Rosenstiel Philip , Aden Konrad , Kaleta Christoph
Published: September 2024

Inflammatory bowel diseases (IBDs) are chronic disorders involving dysregulated immune responses. Despite the role of disrupted host-microbial interaction in the pathophysiology of IBD, the underlying metabolic principles are not fully understood. We densely profiled microbiome, transcriptome and metabolome signatures from longitudinal IBD cohorts before and after advanced drug therapy initiation and reconstructed metabolic models of the gut microbiome and the host intestine to study host-microbiome metabolic cross-talk in the context of inflammation. We identified concomitant changes in metabolic activity across data layers involving NAD, amino acid, one-carbon and phospholipid metabolism. In particular on the host level, elevated tryptophan catabolism depleted circulating tryptophan, thereby impairing NAD biosynthesis. Reduced host transamination reactions disrupted nitrogen homeostasis and polyamine/glutathione metabolism. The suppressed one-carbon cycle in patient tissues altered phospholipid profiles due to limited choline availability. Simultaneously, microbiome metabolic shifts in NAD, amino acid and polyamine metabolism exacerbated these host metabolic imbalances. Leveraging host and microbe metabolic models, we predicted dietary interventions remodeling the microbiome to restore metabolic homeostasis, suggesting novel therapeutic strategies for IBD.
Overview of theSaccharomyces cerevisiaepopulation structure through the lens of 3,034 genomes
Authors: Loegler Victor , Friedrich Anne , Schacherer Joseph
Published: September 2024

With the rise of high-throughput sequencing technologies, a holistic view of genetic variation within populations – through population genomics studies – appears feasible, although it remains an ongoing effort. Genetic variation arises from a diverse range of evolutionary forces, with mutation and recombination being key drivers in shaping genomes. Studying genetic variation within a population represents a crucial first step in understanding the relationship between genotype and phenotype and the evolutionary history of species. In this context, the budding yeastSaccharomyces cerevisiaehas been at the forefront of population genomic studies. In addition, it has a complex history that involves adaptation to a wide range of wild and human-related ecological niches. Although to date more than three thousand diverse isolates have been sequenced, there is currently a lack of a resource bringing together sequencing data and associated metadata for all sequenced isolates. To perform a comprehensive analysis of the population structure ofS. cerevisiae, we collected genome sequencing data from 3,034 natural isolates and processed the data uniformly. We determined ploidy levels, identified single nucleotide polymorphisms (SNPs), small insertion-deletions (InDels), copy number variations (CNVs), and aneuploidies across the population, creating a publicly accessible resource for the yeast research community. Interestingly, we showed that this population captures ∼93% of the species diversity. Using neighbor-joining and Bayesian methods, we redefined the populations, revealing clustering patterns primarily based on ecological origin. This work represents a valuable resource for the community and efforts have been made to make it evolvable and integrable to future yeast population studies.
Benchmarking coarse-grained simulation methods for investigation of transport tunnels in enzymes
Authors: Mandal Nishita , Stevens Jan A. , Poma Adolfo B. , Surpeta Bartlomiej , Sequeiros-Borja Carlos , Thirunavukarasu Aravind Selvaram , Marrink Siewert J. , Brezovsky Jan
Published: September 2024

Enzymes are pivotal to numerous biological processes, often featuring buried active sites linked to the surrounding solvent through intricate and dynamic tunnels. These tunnels are vital for facilitating substrate access, enabling product release, and regulating solvent exchange, which collectively influence enzymatic function and efficiency. Consequently, knowledge of tunnels is key for a holistic understanding of the effect of mutations as well as predicting drug residence times. Unfortunately, most transport tunnels are transient, i.e., equipped by molecular gates, rendering their opening a rare event that is often notoriously hard to study with conventional molecular dynamics simulations. To overcome the sampling limitation of such simulations, this study investigated the efficacy of three different coarse-grained (CG) molecular dynamics simulation methods for inferring enzyme tunnel structure and dynamics. Here, we covered the Martini and SIRAH models with different restraint protocols providing stability to CG proteins while to some extent biasing the sampling towards a reference structure. By contrasting CG results with all-atom simulations, we benchmarked the ability of CG methods to replicate ensemble characteristics of complex tunnel networks in haloalkane dehalogenase LinB and two of its mutants with engineered tunnel networks. The assessed tunnel parameters are essential for prioritizing functionally relevant tunnels and delineating the effect of mutations on transport tunnels. Our findings reveal that while CG methods significantly enhance the efficiency of tunnel analyses, some of them, like Martini with Elastic network restraints, were limited in recapitulating all-atom tunnel dynamics due to the structural bias applied. In contrast, the Martini Gō model even captured the intricate details of mutation perturbing tunnel dynamics. All studied CG methods performed well in capturing the geometry of tunnel ensembles in line with all-atom simulations. Additionally, the wider applicability of CG methods was verified by analyzing tunnel networks of nine enzymes from different combinations of structural and functional classes, demonstrating their potential to uncover new tunnel phenomena and validate their utility in broader biological and functional contexts. This comprehensive evaluation underscores the strengths and constraints of CG simulations in capturing enzyme tunnels and benefiting from their computational speed for studying huge datasets of enzymes. These insights are valuable for enzyme engineering, drug design, and understanding enzyme function while benefitting from the efficiency of coarse-grained models.
The Plastisphere – Marinefungicommunities in theplastics age
Authors: Kirstein Inga V. , Reich Marlis , Yang Yanyan , Timmermann Maike , Wichels Antje , Gerdts Gunnar
Published: September 2024

Fungi play important roles in biofilms, are very versatile in their ecological role, and are considered as plastic degraders. Here we aim to increase the resolution of the fungal members of the Plastisphere, to understand fungal substrate specificities and related potential ecological impacts. Fifteen-month-old fungal Plastisphere communities were investigated on 9 different plastic types and glass in seawater from the North Sea. By integrating scanning electron microscopy (SEM) imaging, ITS-based fingerprinting, and re-evaluated 18S rRNA gene sequence data through a fungal-specific phylogeny-based pipeline, we observed fungal Plastispheres and identified specific characteristics based on morphotypes, phylogeny, and biodiversity across different substrate types. Plastic types selected for specific fungal communities with polyolefine communities indicating significantly higher diversity compared to all other plastic types. Furthermore, specific plastic types may select for specific fungal taxa and their potential hosts, highlighting the complexity of marine biofilm food webs, and related ecological implications.
Deep Video Analysis for Bacteria Genotype Prediction
Authors: Dabouei Ali , Mishra Ishan , Kapur Kuwar , Cao Chengzhi , Bridges Andrew A. , Xu Min
Published: September 2024

Genetic modification of microbes is central to many biotechnology fields, such as industrial microbiology, bioproduction, and drug discovery. Understanding how specific genetic modifications influence observable bacterial behaviors is crucial for advancing these fields. In this study, we propose a supervised model to classify bacteria harboring single gene modifications to draw connections between phenotype and genotype. In particular, we demonstrate that the spatiotemporal patterns ofVibrio choleraegrowth, recorded in terms of low-resolution bright-field microscopy videos, are highly predictive of the genotype class. Additionally, we introduce a weakly supervised approach to identify key moments in culture growth that significantly contribute to prediction accuracy. By focusing on the temporal expressions of bacterial behavior, our findings offer valuable insights into the underlying mechanisms and developmental stages by which specific genes control observable phenotypes. This research opens new avenues for automating the analysis of phenotypes, with potential applications for drug discovery, disease management, etc. Furthermore, this work highlights the potential of using machine learning techniques to explore the functional roles of specific genes using a low-resolution light microscope.
A Bayesian framework to infer and cluster mutational signatures leveraging prior biological knowledge
Authors: Buscaroli Elena , Haghighi Azad Sadr , Bergamin Riccardo , Milite Salvatore , Garcia Edith Natalia Villegas , Tasciotti Arianna , Ansuini Alessio , Ramazzotti Daniele , Calonaci Nicola , Caravagna Giulio
Published: September 2024

The concept of mutational signatures, with its promising translational potential, provides key insights into the mutational processes underlying cancer. Current efforts are increasingly directed toward developing comprehensive catalogues of signatures linked to various tumour types and therapeutic responses. However, the existence of multiple catalogues, generated by different groups using distinct methodologies, underscores the need for standardisation across the field, and a cohesive framework that integrates established signatures remains to be fully realised. Here, we introduce a set of Bayesian algorithms that merge predefined signature catalogues with newly identified signatures, offering a systematic approach to expanding existing collections. By leveraging a diverse array of mutational signatures, our method also groups patients based on shared mutational patterns, further enhancing the translational relevance of these catalogues. We demonstrate that this approach enables the identification of both known and novel molecular subtypes across nearly 7,000 samples spanning three major cancers: breast, colon, and lung. Building on prior research, we propose a robust strategy to deepen our understanding of mutational processes in cancer.
Microtubules coordinate mitochondria transport with myofibril morphogenesis during muscle development
Authors: Avellaneda Jerome , Candeias Duarte , da Rosa Soares Ana , Gomes Edgar R. , Luis Nuno Miguel , Schnorrer Frank
Published: September 2024

Muscle morphogenesis creates highly specialised muscle cells containing contractile myofibrils and energy producing mitochondria. Myofibrils are chains of sarcomeres, whose myosin motors slide over actin filaments at the expense of ATP. Thus, myofibrils and mitochondria are in intimate contact in mature muscles. However, how mitochondria morphogenesis is coordinated with myofibrillogenesis during development remains largely unknown. Here, we usedin vivoimaging to investigate myofibril and mitochondria network dynamics in developingDrosophilaflight muscles. We found that mitochondria rapidly intercalate from the surface of actin bundles to their interior; concomitantly, actin filaments condense to individual myofibrils. This ensures that mitochondria are in intimate proximity to each myofibril. Interestingly, antiparallel microtubules bundle in concert with the assembling myofibrils, suggesting a key role in myofibril orientation. Indeed, light-induced microtubule severing directly affects myofibril orientation, whereas knock-down of kinesin heavy chain specifically blocks mitochondria intercalation and long-range transport. Importantly, mitochondria-myofibril intercalation and microtubule-based transport of mitochondria is conserved in developing mammalian muscle. Together, these data identify a key role for microtubules in coordinating mitochondria and myofibril morphogenesis to build functional muscles.
The DNA damage response and RNA Polymerase II regulator Def1 has posttranscriptional functions in the cytoplasm
Authors: Akinniyi O.T. , Kulkarni S , Hribal M.M. , Keller C.A. , Giardine B. , Reese Joseph C.
Published: September 2024

Yeast Def1 mediates RNA polymerase II degradation and transcription elongation during stress. Def1 is predominantly cytoplasmic, and DNA damage signals cause its proteolytic processing, liberating its N-terminus to enter the nucleus. Cytoplasmic functions for this abundant protein have not been identified. Proximity-labeling (BioID) experiments indicate that Def1 binds to an array of proteins involved in posttranscriptional control and translation of mRNAs. DeletingDEF1reduces both mRNA synthesis and decay rates, indicating transcript buffering in the mutant. Directly tethering Def1 to a reporter mRNA suppressed expression, suggesting that Def1 directly regulates mRNAs. Surprisingly, we found that Def1 interacts with polyribosomes, which requires its ubiquitin-binding domain located in its N-terminus. The binding of Def1 to ribosomes requires the ubiquitylation of eS7a (Rsp7A) in the small subunit by the Not4 protein in the Ccr4-Not complex. Not4 ubiquitylation of the ribosome regulates translation quality control and co-translational mRNA decay. The polyglutamine-rich unstructured C-terminus of Def1 is required for its interaction with decay and translation factors, suggesting that Def1 acts as a ubiquitin-dependent scaffold to link translation status to mRNA decay. Thus, we have identified a novel function for this transcription and DNA damage response factor in posttranscriptional regulation in the cytoplasm and establish Def1 as a master regulator of gene expression, functioning during transcription, mRNA decay, and translation.
Proof of concept study deploying CRISPR inhibition and activation opens key avenues for systematic biological exploration in zebrafish
Authors: Barrientos Nelson B. , Shoppell Elyse A. , Boyd Rachel J. , Culotta Valeria C. , McCallion Andrew S.
Published: September 2024

The application of CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) technologies in zebrafish has the potential to expand its capacity for the study of gene function significantly. We report proof-of-principle data evaluating transient expression of a codon optimized CRISPRi/a system for zebrafish across established pigmentary and growth phenotypes. A codon-optimized and catalytically inactivecas9gene (dcas9) was cloned upstream of codon-optimized Krüppel associated box (KRAB) and methyl-CpG binding protein 2 (MeCP2) for CRISPRi, and VP64 for CRISPRa. To validate CRISPRi, we targeted key genes in melanocyte differentiation (sox10, mitfa,andmitfb); and melanin production (tyrosinase;tyr). Microinjection of CRISPRi mRNA and single guide RNAs (sgRNAs) targeting thetyrpromoter or 5’-UTR resulted in larvae with hypopigmented epidermal melanocytes. CRISPRi-mediated targeting of the promoters or 5’-UTR of transcription factors mitfa and mitfb also results in pronounced hypopigmentation of epidermal melanocytes (mitfa), and RPE (mitfb). Also, CRISPRi targeting of thesox10promoter results in hypopigmentation of both epidermal melanocytes and RPE consistent with its role upstream ofmitfaandmitfb, andtyr. Finally, we tested both CRISPRi/a to modulate a single gene to yield hypomorphic and hypermorphic effects, selectingmrap2aas our target. This gene regulates energy homeostasis and somatic growth via inhibition of the melanocortin 4 receptor gene (mc4r). We demonstrate that inactivating or activatingmrap2awith CRISPRi/a significantly decreases or increases larval body length, respectively. We demonstrate that CRISPRi/a can modulate control of zebrafish gene expression, facilitating efficient assay of candidate gene function and disease relevance.
Manipulating attentional priority creates a trade-off between memory and sensory representations in human visual cortex
Authors: Rademaker Rosanne L. , Serences John T.
Published: September 2024

People often remember visual information over brief delays while actively engaging with ongoing inputs from the surrounding visual environment. Depending on the situation, one might prioritize mnemonic contents (i.e., remembering details of a past event), or preferentially attend sensory inputs (i.e., minding traffic while crossing a street). Previous fMRI work has shown that early sensory regions can simultaneously represent both mnemonic and passively viewed sensory information. Here we test the limits of such simultaneity by manipulating attention towards sensory distractors during a working memory task performed by human subjects during fMRI scanning. Participants remembered the orientation of a target grating while a distractor grating was shown during the middle portion of the memory delay. Critically, there were several subtle changes in the contrast and the orientation of the distractor, and participants were cued to either ignore the distractor, detect a change in contrast, or detect a change in orientation. Despite sensory stimulation being matched in all three conditions, the fidelity of memory representations in early visual cortex was highest when the distractor was ignored, intermediate when participants attended distractor contrast, and lowest when participants attended the orientation of the distractor during the delay. In contrast, the fidelity of distractor representations was lowest when ignoring the distractor, intermediate when attending distractor-contrast, and highest when attending distractor-orientation. These data suggest a trade-off in early sensory representations when engaging top-down feedback to attend both seen and remembered features and may partially explain memory failures that occur when subjects are distracted by external events.
Shared selection and genetic architecture drive strikingly repeatable evolution in long-term experimental hybrid populations
Authors: Owens Gregory L. , Caseys Celine , Mitchell Nora , Hübner Sariel , Whitney Kenneth D. , Rieseberg Loren H.
Published: September 2024

The degree to which evolution repeats itself has implications regarding the major forces driving evolution and the potential for evolutionary biology to be a predictive (versus solely historical) science. To understand the factors that control evolutionary repeatability, we experimentally evolved four replicate hybrid populations of sunflowers at natural sites for up to 14 years and tracked ancestry across the genome. We found that there was very strong negative selection against introgressed ancestry in several chromosomes, but positive selection for introgressed ancestry in one chromosome. Further, the strength of selection was influenced by recombination rate. High recombination regions had lower selection against introgressed ancestry due to more frequent recombination away from incompatible backgrounds. Strikingly, evolution was highly parallel across replicates, with shared selection driving 88% of variance in introgressed allele frequency change. Parallel evolution was driven by both high levels of sustained linkage in introgressed alleles and strong selection on large-effect quantitative trait loci. This work highlights the repeatability of evolution through hybridization and confirms the central roles that natural selection, genomic architecture, and recombination play in the process.
HP1α-driven Phase Separation and Repair Pathway Choice in Response to Heterochromatin Damage
Authors: Bohra Darshika , Mazumder Aprotim
Published: September 2024

Double-strand breaks (DSBs) pose significant threat to genomic stability and need immediate attention from DNA Damage Response (DDR) machinery involved in Homologous Recombination (HR) or Non-homologous end joining (NHEJ). DDR in heterochromatin is challenging owing to the distinct chromatin organization. Heterochromatin Protein 1 (HP1) isoforms that contribute significantly to the organization of heterochromatin, have been shown to be involved in DDR. Mammalian HP1 has three isoforms, HP1α, HP1β, and HP1γ, which possess significant homology and yet have distinct functions. HP1α is the only isoform known to undergo liquid-liquid phase separation. We show that the minute-scale dynamics of HP1α and HP1β differ dramatically and they promote differential recruitment of HR vs. NHEJ factors at the sites of laser-induced clustered DSBs. Perturbing HP1α phase-separation abrogates both the recruitment of HR factors and readouts of HR. Our study provides a link between phase-separation and DDR-centric roles of HP1α and hints at spatial partitioning of repair pathways in response to damage in heterochromatin.
Humoral Immune Responses in German Dialysis Patients after mRNA Omicron JN.1 Vaccination
Authors: Stankov Metodi V. , Hoffmann Markus , Happle Christine , Lürken Karsten , Kempf Amy , Nehlmeier Inga , Stölting Andrea , Pöhlmann Stefan , Dopfer-Jablonka Alexandra , Behrens Georg M. N.
Published: September 2024

To assess the effect of the updated mRNA JN.1 omicron vaccine (bretovameran, BioNTech/Pfizer, Mainz, Germany) in an immunocompromised and elderly population, we measured humoral immune responses after mRNA omicron JN.1 vaccination in 37 haemodialysis patients before and 21 days after vaccination.

We observed a 3-fold change in anti-S IgG, and a 4·7-fold change in anti-S omicron IgG. Memory B cells (MBC) exclusively binding the receptor binding domain (RBD) of JN.1 displayed a median frequency of 0·11% before vaccination and changed significantly 3·9-fold to a median of 0·43%. Cross reactive JN.1 RBD and Wuhan-Hu-1 S-binding MBCs and MBCs only binding to Wuhan-Hu-1 S changed 2·3-fold and 1·8-fold, respectively. Using a vesicular stomatitis virus-based pseudovirus particle (pp) neutralisation assay, baseline response rates were 86% for XBB.1.5pp, 78% for JN.1pp, 73% for and KP.2pp, 65% for KP.2.3ppand KP.3pp, and 68% for LB.1pp. After vaccination, the response rates for all pseudoviruses increased significantly, and we observed a mean increase in neutralisation of XBB.1.5pp, JN.1pp, KP.2pp, KP.2.3pp, KP.3pp, and LB.1ppof 8·3-fold, 18·7-fold, 22·5-fold, 18·7-fold, 25·5-fold, and 23·5-fold, respectively. In summary, our report provides first evidence for a firm humoral immune response in dialysis patients after mRNA omicron JN.1 vaccination.

Our data suggest that the vaccine could be highly effective at enhancing protection of vulnerable populations against evolving SARS-CoV-2 variants.
DNA-PK controls cyclic dinucleotide-associated type I Interferon responses
Authors: Taffoni Clara , Vila Isabelle K. , Jardine Jane , Schussler Moritz , McKellar Joe , Chemarin Morgane , Re Joanna , Messaout-Nacer Yasmine , El Mansouri Insaf , Chrousos George P , Bidère Nicolas , Majzoub Karim , Vlachakis Dimitrios , Laguette Nadine
Published: September 2024

Cytosolic dsDNAs are potent immune-stimulatory molecules that trigger inflammation in several human pathologies1,2. A major pathway for the detection of cytosolic dsDNA relies on the cyclic GMP-AMP (cGAMP) synthase (cGAS) that produces the 2’3’-cGAMP cyclic dinucleotide (CDN) for activation of the Stimulator of Interferon Genes (STING) adaptor protein that subsequently drives type I Interferon (IFN) responses3,4. Here, we investigated the mechanism regulating intracellular 2’3’-cGAMP levels. We show that the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), a major player in the repair of double-strand breaks, directly regulates intracellular levels of 2’3’-cGAMP, thereby reducing STING activation. We describe that the binding of 2’3’-cGAMP to DNA-PKcs occurs in its catalytic cleft, impeding its kinase function. Contrary to other CDN regulatory mechanisms that have been shown to primarily regulate extracellular 2’3’-cGAMP, we show that DNA-PKcs also interacts with the 3’3’-cGAMP bacterial CDN, limiting its capacity to activate STING signaling. Furthermore, we found that DNA-PKcs decreases the potency of pharmacological STING activators. As STING is a major target for therapeutic interventions aiming to boost inflammatory responses in immunosuppressed contexts5, our data bear important implications for drug development and deepens our understanding of inflammatory regulation in response to CDNs.
The predominant binding mode of Palmatine to DNA
Authors: Gentile Marziogiuseppe , Talotta Francesco , Tremblay Jean Christophe , González Leticia , Monari Antonio
Published: September 2024

Palmatine is a protoberberine alkaloid, which may produce singlet oxygen under visible light irradiation and binds to DNA. The fact that singlet oxygen activation in palmatine may be triggered by environmental conditions, and in particular its interaction with nucleic acids, makes it a most suitable candidate for photodynamic therapy and DNA-targeted non-invasive anticancer strategies. Despite these remarkable properties the actual binding mode between palmatine and DNA has not been resolved, yet. Its elucidation has, indeed, led to contrasting hypothesis. In this contribution by using long-range molecular dynamic simulations and enhanced sampling approaches, we unequivocally identify that intercalation is the dominant binding mode of palmatine with DNA, from either a thermodynamic and kinetic point of view.

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On the Analysis of Protein Genetic Architecture: Response to “Protein sequence landscapes are not so simple”
Authors: Park Yeonwoo , Metzger Brian P.H. , Thornton Joseph W.
Published: September 2024

We recently reanalyzed 20 combinatorial mutagenesis datasets using a novel reference-free analysis (RFA) method and showed that high-order epistasis contributes negligibly to protein sequence-function relationships in every case. Dupic, Phillips, and Desai (DPD) commented on a preprint of our work. In our published paper, we addressed all the major issues they raised, but we respond directly to them here. 1) DPD’s claim that RFA is equivalent to estimating reference-based analysis (RBA) models by regression neglects fundamental differences in how the two formalisms dissect the causal relationship between sequence and function. It also misinterprets the observation that using regression to estimate any truncated model of genetic architecture will always yield the same predicted phenotypes and variance partition; the resulting estimates correspond to those of the RFA formalism but are inaccurate representations of the true RBA model. 2) DPD’s claim that high-order epistasis is widespread and significant while somehow explaining little phenotypic variance is an artifact of two strong biases in the use of regression to estimate RBA models: this procedure underestimates the phenotypic variance explained by RBA epistatic terms while at the same time inflating the magnitude of individual terms. 3) DPD erroneously claim that RFA is “exactly equivalent” to Fourier analysis (FA) and background-averaged analysis (BA). This error arises because DPD used an incorrect mathematical definition of RFA and were misled by a simple numerical relationship among the models that only holds only for the simplest kinds of datasets. 4) DPD argue that using a nonlinear transformation to account for global nonlinearities in sequence-function relationships is often unnecessary and may artifactually absorb specific epistatic interactions. We show that nonspecific epistasis caused by a limited dynamic range affects datasets of all types, even when the phenotype is represented on a free-energy scale. Moreover, using a nonlinear transformation in a joint fitting procedure does not underestimate specific epistasis under realistic conditions, even if the data are not affected by nonspecific epistasis. The conclusions of our work therefore hold: the genetic architecture of all 20 protein datasets we analyzed can be efficiently and accurately described in an RFA framework by first-order amino acid effects and pairwise interactions with a simple model of global nonlinearity. We are grateful for DPD’s commentary, which helped us improve our paper.
Patient-specificin silicoprediction of outcomes of partial continuous-flow LVAD treatment in peripartum cardiomyopathy
Authors: Nagawa Juliet , Sack Kevin L. , Nchejane N. John , Motchon Y. Dodzi , Sirry Mazin S. , Kraus Sarah , Davies Neil H. , Ntusi Ntobeko A.B. , Franz Thomas
Published: September 2024

Patients with severe peripartum cardiomyopathy (PPCM) often receive mechanical circulatory support with good outcomes. However, the mechanisms underlying the functional improvements are poorly understood. This study investigated the effects of partial, continuous-flow left ventricular assist device (LVAD) support on cardiac function and mechanics in patients with PPCM of different severity. Patient-specific biventricular finite element models of six PPCM patients (four recovered, two non-recovered) were developed from magnetic resonance images and combined with a circulatory system model, including variable LVAD support. Ventricular function and myocardial mechanics were predicted, and changes due to LVAD support were quantified. The LVAD support decreased myofiber stress and increased ejection fraction (EF) of the LV. EF increased steadily (two patients), fluctuated (two patients), or peaked before a steady decrease (two patients) with increasing LVAD speed. Improvement due to LVAD support was greater for PPCM patients with higher disease severity than those with lower disease severity. The LVAD and native LV jointly generated stroke volume (SV) in four patients, and the LV contribution diminished with increasing LVAD speed. In the two patients with the lowest EF, the LVAD was the sole source of SV. The improvement of cardiac function and mechanics due to LVAD support in PPCM exceeds that reported for chronic heart failure due to ischemia. However, the predicted variability of the LVAD benefits with PPCM severity and mechanical support level suggests the need and potential for further studies to guide clinicians in selecting personalised treatment parameters required for optimised LVAD therapy for each PPCM patient.

Key points summary

Partial continuous-flow left ventricular assist device (LVAD) therapy has presented positive outcomes for critically ill patients with peripartum cardiomyopathy (PPCM), but the underlying LVAD mechanisms are poorly understood.

This study showed greater functional improvement for patients who did not recover than those who recovered from PPCM.

In patients with severe functional impairment, the LVAD provides the entire ventricular output at all speeds, whereas the LVAD and left ventricle generate the output jointly in patients with mild impairment, and the contribution of the left ventricle decreases with increasing LVAD speed.

The variability of the LVAD benefits with disease severity and device speeds emphasises the need for patient-specific treatment to achieve optimal therapy outcomes.

The developed patient-specific computational models offer a tool for further research and the potential for developing a clinical decision guide for personalised treatment of PPCM.
Associations between RetNet gene polymorphisms and efficacy of orthokeratology for myopia control : sample from a clinical retrospective study
Authors: Xia Ruijing , Yu Xiangyi , Peng Lulu , Du Zhenlin , Yu Xiaoguang , Xing Shilai , Lu Fan , Mao Xinjie
Published: September 2024

Background

To study how clinical and genetic factors control the effectiveness of orthokeratology lenses in myopia.

Methods

In this study, we conducted a retrospective clinical study of 545 children aged 8–12 years with myopia who were wearing orthokeratology lenses for one year and performed whole-genome sequencing (WGS) for 60 participants in two groups, one with rapid axial length progression of larger than 0.33 mm and the other with slow axial length progression of less than 0.09 mm. Genes in the RetNet database were used to screen candidate genes that may contribute to the effectiveness of orthokeratology lenses in controlling myopia.

Results

We found that children with a greater baseline eye axial length, greater spherical equivalent (SE) and greater age had better myopia control with orthokeratology. We observed a significant excess of nonsynonymous variants among those with slow myopia progression, which were prominently enriched in retinal disease related genes. We subsequently identifiedRIMS2(OR=0.01,p=0.0075) andLCA5(OR=6.96,p=0.0080) harboring an excess number of nonsynonymous variants in patients with slow progression of high myopia. Two intronic common variants rs36006402 inSLC7A14and rs2285814 inCLUAP1 were strongly associated with axial length growth. Together, our finding identified novel genes associated with the effectiveness of orthokeratology lenses therapy in myopic children and provide insight into the genetic mechanism of orthokeratology treatment.

Conclusion

The effectiveness of orthokeratology lenses treatment involved interindividual variability in controlling axial length growth in myopic eyes. The efficacy increased when patients carried more nonsynonymous variants in retinal disease-related gene sets. Our data will serve as a well-founded reference for genetic counseling and better management of patients who choose orthokeratology lenses to control myopia.
Prevalence and determinants of central obesity among adults 18–69 years in Kenya: a cross-sectional study
Authors: Nyakundi Caleb , Okemwa Sharonmercy , Ngesa Romeo Warera , Gatimu Samwel Maina
Published: September 2024

Background

Central obesity affects about 4 out of every 10 people globally, and it is a notable public health concern linked with premature morbidity and mortality. In Kenya, regional studies have approximated the prevalence to range from 37% to 50%. However, these studies have been done in specific regions or population groups, such as among urban residents or women. Therefore, we aimed to assess the general and sex-specific prevalence and determinants of central obesity among adults in Kenya.

Methods

An analysis of the prevalence and determinants of central obesity was assessed using data from the 2015 Kenya STEPwise survey on non-communicable diseases and injuries. We included a final sample of 4 003 participants. Participants’ characteristics and prevalence of central obesity were described and summarized using frequencies and percentages. The bivariate and multivariate logistic regression were used to assess the determinants of central obesity.

Results

The overall weighted prevalence of central obesity was 46.7% [95% confidence interval (CI): 43.2, 50.3], with women exhibiting a significantly higher prevalence compared to men (58.3% vs. 35.6%, p=0.001). Sex, age, household wealth index, and smoking were among the factors significantly associated with central obesity. Men had 66% lower odds of central obesity compared to women, while the risk increased with age, ranging from 1.6 to 4 times higher odds among those aged 30—39 and 50—69 years, respectively, compared to 18—29–year–olds. Other predictors of central obesity were wealthier households and non-smoking.

Conclusion

About half of the adult Kenyan population is centrally obese, with a higher prevalence among women than men. Kenya’s policymakers should consider targeting high-risk groups in this population to reduce the burden of central obesity.
A mapping review of good practices of participatory research for an impactful collaboration in disabilities studies
Authors: Corcuff Maëlle , Jribi Rania , Rodrigue Guillaume , Lamontagne Marie-Eve , Raymond Émilie , Archambault Philippe S. , Routhier François
Published: September 2024

Introduction

Participatory research is particularly relevant to understanding the challenges faced by people with disabilities (PWDs), as it actively involves them as partners, enabling methodologies to be better adapted to lived realities and producing more relevant and applicable results. By reducing systemic barriers and promoting inclusion, this approach improves understanding and consideration of the specific needs of PWDs in research. Yet, studies have identified hurdles associated with this approach, prompting questions about how organizations portray PWDs, the dynamics among research stakeholders, the distribution of decision-making power, and the actual impact of research on its partners.

Aim

This study aims to identify the factors that influence the process and results of participatory research in the field of disability studies

Methods

We conducted a mapping review following the PRISMA-ScR guidelines, and analysis the results according to the input-throughput-outcomes Bergen model

Results

This study identifies partners skills and training, power sharing and benefits of active involvement as facilitators of participatory research. On the other hand, contextual challenges, and lack of guidance are reported as obstacles.

Conclusion

This study provides insight into how the various facilitators and obstacles to participatory research and its different processes interact to produce positive, valid and rigorous results.
Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain
Authors: Miller Jonathan , Jacobs Skylar , Koppes William , Minella Frank , Porta Federica , White Fletcher A. , Lovelace Joseph A.
Published: September 2024

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions of dollars annually. Despite the tremendous impact of chronic pain in the US and worldwide, the standard of care for diagnosis depends on subjective self-reporting of pain state, with no effective objective assessment procedure available. This study investigated the application of signal processing and machine learning to electroencephalography (EEG) data for the development of classification algorithms capable of differentiating subjects in pain from pain free subjects. In this study, nineteen (19) channels of EEG data were obtained from subjects in an eyes closed resting state, and ultimately data from 186 participants were used for algorithm development, including 35 healthy controls and 151 chronic pain patients. Signal processing was applied to identify noise free segments of EEG data and 6375 quantitative EEG (qEEG) measures were calculated for each subject. Various machine learning methodologies were applied to the data, with Elastic Net chosen as the optimal methodology. The final classifier developed using Elastic Net contained 34 qEEG features with non-zero weights. The classifier was able to differentiate pain versus no pain subjects with an accuracy of 79.6%, sensitivity of 82.2%, and specificity of 66.7%. The features used in the classifier were evaluated and found to align well with contemporary literature regarding changes in neurological characteristics associated with chronic pain.
Interactive effects of bacterial vaginal colonization and HIV on pregnancy outcomes: A Systematic Review and Meta-analysis
Authors: Matovelo Dismas , Goddard Quinn , Sabuni Paul , Kidenya Benson , Downs Jennifer , Magoma Moke , Seni Jeremiah , Chaput Kathleen Helen
Published: September 2024

Background

The independent impact of HIV and bacterial vaginal colonization on pregnancy outcomes has been documented and is compounded by the burden of rapidly escalating antimicrobial resistance. However, the interactive effect of HIV and lower genital tract bacterial colonization, on pregnancy outcomes has not been thoroughly studied and is examined in our study.

Methods

We performed a systematic review and meta-analysis to quantitatively assess the interaction between HIV and vaginal bacterial colonization and associations with birth weight and preterm birth. We searched Ovid MEDLINE, Ovid EMBASE, CINAHL, Scopus, Web of Science, Cochrane Library, African Journals Online, and PubMed databases to identify studies published up to December 31, 2023. We included observational reporting on vaginal colonization with bacterial pathogens stratified by HIV status that reported pregnancy outcomes. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and used a modified Newcastle-Ottawa Scale to assess study quality. Meta-analysis was conducted using random-effects modeling in STATA Version 18. Pooled log-odds ratios were calculated. The study protocol was registered in PROSPERO(CRD42023485123).

Results

We selected 13 studies, involving 6,073 pregnant women, from 5,807 studies identified. The overall pooled prevalence of bacterial colonization was 26%(95%CI:17.3-37.4). There was no significant effect of HIV status and vaginal colonization on birth weight(OR=1.2, 95%CI:-2.57-2.20,p=0.88) and borderline increased odds of preterm birth (OR=2.64, 95%CI:-0.01-1.94,p=0.05). There was no significant association between HIV status and bacterial colonization(OR=1.08, 95%CI =-0.91-1.07), nor in antimicrobial resistance between pregnant women with HIV and those without.

Conclusion

Bacterial colonization is prevalent among pregnant women, but there is no clear evidence to suggest that HIV and bacterial colonization interact to affect birth weight or preterm birth. Research with large sample sizes, strict selection criteria, reliable and valid measurement, adequate control for confounding variables, and birthweight and gestational age at delivery assessment as continuous outcomes are still needed to provide robust evidence.
A Minimal PBPK Model Describes the Differential Disposition of Silica Nanoparticles In Vivo
Authors: Parrot Madison , Cave Joseph , Pelaez Maria J , Ghandehari Hamidreza , Dogra Prashant , Yellepeddi Venkata
Published: September 2024

Nanoparticles (NPs) have emerged as promising candidates for drug delivery due to their tunable physical and chemical properties. Among these, silica nanoparticles (SiNPs) are particularly valued for their biocompatibility and adaptability in applications like drug delivery and medical imaging. However, predicting SiNP biodistribution and clearance remains a significant challenge. To address this, we developed a minimal physiologically-based pharmacokinetic (mPBPK) model to simulate the systemic disposition of SiNPs, calibrated using in vivo PK data from mice. The model assesses how variations in surface charge, size, porosity, and geometry influence SiNP biodistribution across key organs, including the kidneys, lungs, liver, and spleen. A global sensitivity analysis identified the most influential parameters, with the unbound fraction and elimination rate constants for the kidneys and MPS emerging as critical determinants of SiNP clearance. Non-compartmental analysis (NCA) further revealed that aminated SiNPs exhibit high accumulation in the liver, spleen, and kidneys, while mesoporous SiNPs primarily accumulate in the lungs. Rod-shaped SiNPs showed faster clearance compared to spherical NPs. The mPBPK model was extrapolated to predict SiNP behavior in humans, yielding strong predictive accuracy with Pearson correlation coefficients of 0.98 for mice and 0.92 for humans. This model provides a robust framework for predicting the pharmacokinetics of diverse SiNPs, offering valuable insights for optimizing NP-based drug delivery systems and guiding the translation of these therapies from preclinical models to human applications.