bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of cross-reactive vaccine antigen candidates in Gram-positive ESKAPE pathogens through subtractive proteome analysis using opsonic sera
Authors: Sadones Océane , Kramarska Eliza , Sainz-Mejías Maite , Berisio Rita , Huebner Johannes , McClean Siobhán , Romero-Saavedra Felipe
Published: February 2025

The Gram-positive pathogens of the ESKAPE group,Enterococcus faecium,andStaphylococcus aureus, are well-known to pose a serious risk to human health because of their high virulence and numerous drug resistances, making them a real concern in healthcare settings worldwide. To narrow down the list of previously identified promising protein vaccine candidates, a combination of several antigen discovery approaches was performed, in particular a “false positive analysis” of peptides generated by trypsin shaving with a subtractive proteome analysis. The final list of nine potential antigens included AdcAau, a protein performing the same function as AdcAfm, an already discovered antigen in enterococci. Bioinformatic analyses revealed that AdcAauand AdcAfmshare a sequence identity of 41.2% and that the conserved regions had a high antigenicity. AdcAauwas selected for further investigation and the results reported in this manuscript demonstrate the opsonic properties of AdcAau-specific antibodies against theS. aureusstrain MW2, as well as their cross-binding and cross-opsonic activity against severalS. aureus, E. faecium, andE. faecalisstrains. This study suggests that further investigation of cross-reactive activities is a valuable tool for discovering new antigens that cover more than one clinically relevant pathogen.
Inverse modeling of heterogeneous ECM mechanical properties in nonlinear 3DTFM
Authors: Apolinar-Fernández Alejandro , Barrasa-Fano Jorge , Van Oosterwyck Hans , Sanz-Herrera José A.
Published: February 2025

Accurate characterization of cellular tractions is crucial for understanding cell-extracellular matrix (ECM) mechanical interactions and their implications in pathology-related situations, yet their direct measurement in experimental setups remains challenging. Traction Force Microscopy (TFM) has emerged as a key methodology to reconstruct traction fields from displacement data obtained via microscopic imaging techniques. While traditional TFM methods assume homogeneous and static ECM properties, the dynamic nature of the ECM through processes such as enzyme–induced collagen degradation or cellmediated collagen deposition i.e. ECM remodeling, requires approaches that account for spatio-temporal evolution of ECM stiffness heterogeneity and other mechanical properties. In this context, we present a novel inverse methodology for 3DTFM, capable of reconstructing spatially heterogeneous distributions of the ECM’s stiffness. Our approach formulates the problem as a PDE-constrained inverse method which searches for both displacement and the stiffness map featured in the selected constitutive law. The elaborated numerical algorithm is integrated then into an iterative Newton-Raphson/Finite Element Method (NR/FEM) framework, bypassing the need for external iterative solvers. We validate our methodology usingin silico3DTFM cases based on real cell geometries, modeled within a nonlinear hyperelastic framework suitable for collagen hydrogels. The performance of our approach is evaluated across different noise levels, and compared versus the commonly used iterative L-BFGS algorithm. Besides the novelty of our formulation, we demonstrate the efficacy of our approach both in terms of accuracy and CPU time efficiency.
Systems Pharmacology Screening Reveals Mertk and other Targetable Kinases in Supratentorial Ependymomas
Authors: Chan Marina , Zhu Songli , Russell Zach , Arora Sonali , Arakaki Aleena , Kumasaka Deby , Szulzewsky Frank , Michealraj Antony , Holland Eric C , Gujral Taranjit S
Published: February 2025

Ependymomas (EPN) are central nervous system tumors arising from ependymal cells, primarily affecting young children and accounting for 10% of intracranial tumors in children and 4% in adults. Current treatments are limited to surgery and radiotherapy, with chemotherapy providing minimal benefit. Over 70% of supratentorial ependymomas (ST-EPNs) are driven by ZFTA-RELA fusions (ZFTA-RELAfus), which are associated with poor prognosis. Recent molecular classifications have identified two distinct ST-EPN clusters, E1 and E2, with the E1 cluster predominantly composed of ZFTA-RELAfustumors. However, effective targeted therapies for these tumors remain lacking. Here, we show that the ZFTA-RELAfusmouse model closely mirrors the human E1 cluster, validating its use for therapeutic discovery. Using this model and a systems polypharmacology approach called Kinome Regularization, we identified mer tyrosine kinase (Mertk) as a key regulator of ZFTA-RELAfuscell viability and proliferation. Genetic depletion or pharmacological inhibition of Mertk reduced cell growthex vivoand treatment with the clinical-grade Mertk inhibitor significantly suppressed tumor proliferationin vivo. Mechanistically, both human E1 tumors and mouse ZFTA-RELAfustumors showed elevated Mertk expression, with Mertk inhibition leading to decreased activity of pro-survival pathways. Further, substantial overlap (>80%) between genes upregulated in ZFTA-RELAfustumors and those downregulated following Mertk inhibition treatment suggest a dependency on Mertk-mediated signaling for tumor growth. These findings highlight Mertk as a promising therapeutic target and support the clinical development of Mertk inhibitors for treating human E1 subtype and ZFTA-RELAfus-driven ependymomas.
siRNA-based Therapeutic Candidate Targeting PRDM2 for Inhibition of Lung Cancer Progression
Authors: Kumar Sanjay , Malik Md Zubbair , Chaturvedi Maya , Mishra Mohit , Donato Marzia Di , Casamassimi Amelia , Abbondanza Ciro , Gazzerro Patrizia , Nguyen Chuong , Nuñez Nicole N , Sen Somdutta , Niles Brad , Chaturvedi Rupesh
Published: February 2025

Lung cancer is the leading cause of tumor-related fatalities worldwide. The current precision therapies are effective but target only those molecules that are impacted in a minority of lung cancer patients. Positive Regulatory Domain 2 (PRDM2), a member of the PRDM gene family, also known as Retinoblastoma Interacting Zinc finger (RIZ) protein. RIZ is found to be misregulated in more than 60% of lung cancer patients, representing a significantly affected population when compared to other mutation-prone oncogenic factors. RIZ expresses two contrasting variants, a tumor suppressor RIZ1, and an oncogenic RIZ2 protein. In lung cancer, the RIZ1/RIZ2 ratio alters, and the epigenetic silencing of RIZ1 promotes RIZ2 overexpression. In this study, we used siRNA (ARIZ-047) to knockdown and inhibit the effect of the oncogenic protein RIZ2. Inhibiting RIZ2 with ARIZ-047 treatment increased RIZ1 expression and decreased the viability of a lung cancer cell line (A549). The ARIZ-047 treatment also upregulated the negative regulators of the Wnt signaling pathway and restrained the tumor progression in the xenograft mice model. In conclusion, this study identifies ARIZ-047 as a targeted therapy in lung cancer, which specifically inhibits RIZ2 and suggests the role of the Wnt signaling pathway in RIZ2 overexpression.

Graphical Abstract
Divergence of Functional Brain Network Configurations in Same and Other Race Face Recognition
Authors: Yaros Jessica L. , Houalla Bethany A. , McMillan Liv , Larson Myra S. , Yu Guanqiao , Hollearn Martina , Miranda Blake A. , Jirsaraie Robert , Salama Diana A. , Rapp Paul E. , Yassa Michael A.
Published: February 2025

The “Other-Race Effect” (ORE) refers to the enhanced memory individuals have for faces within their own racial group compared to other races. This effect is attributed to limited exposure to different races and social-motivational factors affecting face processing. While past research has explored this effect through neuroimaging methods, the precise neural mechanisms that underlie the ORE remain a subject of ongoing investigation. Previous studies have largely adopted a modular perspective, concentrating on the differential activation of face-processing regions when comparing same-race and other-race facial recognition behaviors. However, given the multifaceted nature of the ORE, an exclusive focus on specialized regions may miss the pivotal role played by non-face-preferential brain areas in modulating this phenomenon. In the present study, we take a broader data-driven perspective using graph-theoretical techniques to investigate whole-brain network disparities in same- and other-race facial recognition. Our findings reveal a substantial impact of race on functional connectivity during face memorization. While other-race face recognition benefitted from higher local efficiency during encoding, reduced local efficiency was advantageous for memorization of same-race faces. Notably, successful other-race recognition was disproportionately supported by locally efficient processing in regions among the ventral and dorsal attention networks.
LRTM: Left-Right Transition Matrices for Molecular Interaction Prediction
Authors: Zheng Kai , Duan Guihua , Yang Mengyun , Wu Wei , Li Yao-Hang , Wang Jianxin
Published: February 2025

Molecular interactions are central to most biological processes. The discovery and identification of potential associations between molecules can provide insights into biological exploration, diagnostic and therapeutic interventions, and drug development. So far many relevant computational methods have been proposed, but most of them are usually limited to specific domains and rely on complex preprocessing procedures, which restricts the models’ ability to be applied to other tasks. Therefore, it remains a challenge to explore a generalized approach to accurately predicting potential associations. In this study, We propose Left-Right Transition Matrices (LRTM) for molecular interaction prediction. From the perspective on the diffusion model, we construct two transition matrices to model undirected graph information propagation. This allows modeling the transition probabilities of links, which facilitates link prediction in molecular bipartite networks. The extensive experimental results show that the proposed LRTM algorithm performs better than the compared methods. Also, the proposed algorithm has the potential for cross-task prediction. Furthermore, case studies show that LRTM is a powerful tool that can be effectively applied to practical applications.
A general kernel machine comparative analysis framework for randomized block designs
Authors: Koh Hyunwook
Published: February 2025

Motivation

There are numerous potential confounders, including genetic, environmental, technical, and demographic factors. These factors may be known or unknown, measured or unmeasured; hence, it is extremely challenging to capture them in downstream data analysis. However, randomized block design is an efficient design technique to control confounding factors and to reduce variability within subjects. This helps prevent spurious discoveries and boost test power. I also note that kernel machine comparative analysis is widely employed in high-dimensional omics studies to boost test power by combining possibly weak effects from multiple underlying variants, and also to explore various linear or nonlinear patterns of disparity.

Results

In this paper, I introduce a general kernel machine comparative analysis framework for randomized block designs, named as KernRBD, to investigate the effects of treatments (e.g., medical treatment, environmental exposure) on the underlying variants. KernRBD is unique in its range of functionalities, including the computation ofP-value for global testing and adjustedP-values for pairwise comparisons, as well as visual representation through ordination plotting. KernRBD is practical, requiring only a kernel as input, and also robustly valid based on a resampling scheme not requiring the assumption of normality to be satisfied. I also introduce its omnibus test for a unified and powerful significance testing across multiple input kernels. While its applications should be much broader, I illustrate its use through human microbiomeβ-diversity analysisin praxis, and its outperformance in significance testing through simulation experimentsin silico.

Availability and Implementation

KernRBD is available athttps://github.com/hk1785/kernrbd.
Mitotic polarity oscillation promotes epithelial tumor progression
Authors: Jeyanathan Gayaanan , Cao Ming Meggie , Pellikka Milena , Robinson Sarah , Talukder Parama , Ghorayeb Vanessa , Tepass Ulrich
Published: February 2025

Mitosis of epithelial cells requires a transient loss of epithelial polarity [1–5]. However, the nature of this mitotic polarity oscillation and its functional consequences for epithelial development are not fully understood. Here we show that the Crumbs (Crb) complex, a key regulator of epithelial polarity, is lost from the membrane during mitosis, and the Crb mutant phenotype is ameliorated when cell division is inhibited. Remarkably, an essential requirement of Crb for epithelial polarity is fully suspended when cell division is blocked in conjunction with inhibition of either cell ingression or cell intercalation. We conclude that the amount of morphogenetic stress induced by mitosis, ingression, and intercalation determines the requirement for Crb. Increased cell division and loss of cell polarity are two main drivers of epithelial cancer [6–8]. Maintaining epithelial polarity is important for limiting proliferation. Whether the loss of polarity during mitosis impacts tissue growth is less clear. We show that increasing cell division in a morphogenetically quiet epithelium not only increases tissue size but also causes hyperplastic to neoplastic transition. Conversely, reducing cell division restores epithelial polarity in neoplastic tissue of tumor mutants. Taken together, our study revealed that a major function of polarity factors in epithelial maintenance is to counteract morphogenetic stress. Moreover, we propose a feedforward mechanism that links cell division and the loss of polarity as a key driver of epithelial cancer.
Distinguishing new from persistent infections at the strain level using longitudinal genotyping data
Authors: Nickols William A. , Schwabl Philipp , Niangaly Amadou , Murphy Sean C. , Crompton Peter D. , Neafsey Daniel E.
Published: February 2025

Motivation

Longitudinal pathogen genotyping data from individual hosts can uncover strain-specific infection dynamics and their relationships to disease and intervention, especially in the malaria field. An important use case involves distinguishing newly incident from pre-existing (persistent) strains, but implementation faces statistical challenges relating to individual samples containing multiple strains, strains sharing alleles, and markers dropping out stochastically during the genotyping process. Current approaches to distinguish new versus persistent strains therefore rely primarily on simple rules that consider only the time since alleles were last observed.

Results

We developed DINEMITES (DistinguishingNewMalariaInfections inTime Series), a set of statistical methods to estimate, from longitudinal genotyping data, the probability each sequenced allele represents a new infection harboring that allele, the total molecular force of infection (molFOI, the cumulative number of newly acquired strains over time) for each individual, and the total number of new infection events for each individual. DINEMITES can handle time points with missing sequencing data, incorporate treatment history and covariates affecting the rate of new or persistent infections, and can scale to studies with thousands of samples sequenced across multiple loci containing hundreds of possible alleles. In synthetic evaluations, the DINEMITES Bayesian model, which generally outperformed an alternative clustering-based model also developed in this work, accurately estimated key clinical parameters such as molFOI (bias 2.5, compared to −12.2 for a typical simple rule). When applied to three real longitudinal genotyping datasets, the model detected 33%, 112%, and 359% more average infections per participant than would have been detected by applying a typical simple rule to the equivalent datasets without sequencing.

Availability and implementation

DINEMITES is freely available as an R package, along with documentation, tutorials, and example data, athttps://github.com/WillNickols/dinemites.
Efficient Production of Pseudopregnant Female Mice Using Non-Estrous Individuals and the Whitten Effect
Authors: Noguchi Yuji , Watanabe Eiji
Published: February 2025

Pseudopregnant recipient females are essential for transplanting early mouse embryos during individualization. Traditionally, pseudopregnancy is induced through mating stimulation with vasectomized males, targeting females in proestrus or estrus. However, group housing of females in animal facilities often leads to fewer females entering estrus due to the Lee-Boot effect. This study focused on utilizing non-estrous females and the Whitten effect to produce pseudopregnant females. Females exhibiting characteristics of non-estrous states were visually selected and paired monogamously with vasectomized males for three consecutive days. This approach resulted in a high copulation success rate of 72.1% (CLEA Japan, Inc.) and 77.0% (Japan SLC, Inc.) on the expected third day. Subsequent embryo transfer using successfully copulated females resulted in offspring from 93.5% of ICR females from CLEA Japan, Inc. and 89.6% of ICR females from Japan SLC, Inc. Additionally, the suitability for embryo transfer could be determined by observing the condition of the ampulla of the oviduct. While this method requires a three-day preparation period compared to conventional approaches, it offers an effective alternative for creating pseudopregnant females for embryo transfer, potentially reducing animal use and associated costs.
A reservoir model of respiration-induced perceptual alternation in binocular rivalry
Authors: Yonekura Shogo , Narita Atsushi , Kanazawa Hoshinori , Kuniyoshi Yasuo
Published: February 2025

Perceptual alternation in human binocular rivalry is more likely to occur during certain respiratory phases. In this paper, we show that the respiration dependence of perceptual alternations can be reproduced by a randomly connected recurrent neural network coupled with respiration relevant information via a neuromodulator of norepinephrine (NA). We considered two models of NA modulations; NA increases or decreases the nonlinearity of the activation function of neurons, and we found that the shape of the likelihood function of perceptual alternation depends only on respiratory phase, regardless of whether NA increases or decreases neural nonlinearity. Our results suggest that periodic neuromodulation facilitates the switching of competing neural states in specific phases and that this effect is independent of the excitatory or inhibitory effect of NA.
Third-generation cephalosporin antibiotics induce phage bursts in the human gut microbiome
Authors: Pfeifer Eugen , d’Humières Camille , Lamy-Besnier Quentin , Plaza-Onate Florian , Denise Remi , Dion Sara , Condamine Bénédicte , Touchon Marie , Ma Laurence , Burdet Charles , Mentre France , Denamur Erick , Rocha Eduardo ,   the PrediRes study group
Published: February 2025

The use of antibiotics disrupts the gut microbiota, potentially leading to long-term health issues and the spread of resistance. To investigate the impact of antibiotics on phage populations, we followed 22 healthy individuals two weeks before and up to six months after a three-day course of 3rd-generation cephalosporins. The populations of phages encoded very rarely antibiotic resistance genes and were mostly temperate including many phage-plasmids. Gut phages remained individual-specific even after microbiome perturbation by antibiotics. Yet, we found a 20% decline in phage diversity and abundance the day after treatment, caused by the burst of a few (mostly virulent) phages. We suggest they contribute to the recovery of gut bacterial diversity, since several targetedParabacteroides distasonis, a bacterium thriving after cephalosporin treatment that only proliferated in the absence of these phages. Our findings point out that phages play a crucial role in the gut microbiota’s response to antibiotics by restoring microbial balance and diversity.

Graphical abstract
SHINE: Deterministic Many-to-Many clustering of Molecular Pathways
Authors: Chen Lexin , Leung Jeremy M. G. , Zsigmond Krisztina , Chong Lillian T. , Miranda-Quintana Ramón Alain
Published: February 2025

State-of-the-art molecular dynamics (MD) simulation methods can generate diverse ensembles of pathways for complex biological processes. Analyzing these pathways using statistical mechanics tools demands identifying key states that contribute to both the dynamic and equilibrium properties of the system. This task becomes especially challenging when analyzing multiple MD simulations simultaneously, a common scenario in enhanced sampling techniques like the weighted ensemble strategy. Here, we present a new module of the MDANCE package designed to streamline the analysis of pathway ensembles. This module integrates n-ary similarity, cheminformatics-inspired tools, and hierarchical clustering to improve analysis efficiency. We present the theoretical foundation behind this approach, termed Sampling Hierarchical Intrinsic N-ary Ensembles (SHINE), and demonstrate its application to simulations of alanine dipeptide and adenylate kinase.
Direct Optical Detection of Factor Xa Activity in Minimally Processed Whole Blood
Authors: Cartwright Alyssa P. , Wollant Benjamin C. , York Elizabeth S. , Zheng Liwei , Yee Steven , Chau Huong C. , Batsuli Glaivy , Soh H. Tom
Published: February 2025

The ability to measure factor Xa activity directly in whole blood samples offers a path toward point-of-care monitoring and personalized anticoagulant dosage, potentially reducing bleeding risk and other anticoagulant-associated complications. We present a strategy to enable direct optical detection of factor Xa in minimally processed whole blood samples. Our strategy relies on a custom FRET-pair labeled DNA-peptide substrate, allowing FRET ratio to be monitored as an indicator of factor Xa activity. Substrates are tethered to a tapered-fiber sensor to allow evanescent detection of fluorescence directly at the sensor surface, minimizing background media interference and enabling detection directly in blood samples. After characterizing the custom substrate and demonstrating the correlation of fiber-based measurements to an existing chromogenic assay, we demonstrate the detection of endogenous factor Xa activity in >85% whole blood. Finally, we demonstrate the detection of therapeutic concentrations of enoxaparin, a widely used anticoagulant, directly in 90% whole blood in less than an hour and correlate these measurements to activated partial thromboplastin time (aPTT) testing. Together, these results indicate a promising strategy to achieve point-of-care factor Xa detection, enabling personalized anticoagulant treatment and reducing adverse outcomes.
RFdiffusion Exhibits Low Success Rate in De Novo Design of Functional Protein Binders for Biochemical Detection
Authors: Jiang Bruce , Li Xiaoxiao , Guo Amber , Wei Moris , Wu Jonny
Published: February 2025

The design of high-affinity protein binders is critical for biochemical detection, yet traditional methods remain labor-intensive. AI-driven tools like RFdiffusion, a RoseTTAFold-based diffusion model, offer promising alternatives for generating protein structures with tailored binding interfaces. This study evaluates RFdiffusion’s efficacy in designingde novobinders for six targets: Strep-Tag II (a peptide tag) and five eukaryotic proteins (STAT3, FGF4, EGF, PDGF-BB, and CD4). Five binders were designed for each target and experimentally validated. While two Strep-Tag II binders outperformed streptavidin in Western blot assays, none matched the sensitivity of anti-Strep-Tag II antibodies. Binders for the other targets failed due to low expression, nonspecific binding, or undetectable affinity. Despite generating structurally diverse candidates, RFdiffusion’s success rate was limited by low-affinity designs and inconsistent recombinant expression. These results underscore the need for further optimization of AI-driven protein design tools for practical biochemical applications.
Pathology of Influenza A (H5N1) infection in pinnipeds reveals novel tissue tropism and vertical transmission
Authors: Fiorito Carla , Colom Ana , Fernández Antonio , Alonso-Almorox Paula , Andrada Marisa , Lombardo Daniel , Sierra Eva
Published: February 2025

In 2023, an unprecedented outbreak of highly pathogenic avian influenza (HPAI) H5N1 resulted in the death of thousands of pinnipeds along the Argentinean coast, raising concerns about its ecological and epidemiological impact. Here, we present clinical, pathological, and molecular findings associated with HPAI H5N1 infection in pinnipeds from Chubut, Argentina. Necropsies were conducted on three South American Sea Lions (SASLs) (Otaria flavescens) and one Southern Elephant Seal (SES) (Mirounga leonina), followed by histopathological, immunohistochemical and RT-sqPCR analyses. Neurological clinical signs were observed in two SASLs, with one also exhibiting respiratory distress. Neuropathological findings included lymphoneutrophilic meningoencephalomyelitis and choroiditis, neuronal necrosis, gliosis, hemorrhages, and perivascular cuffing. Viral antigen was localized in neurons, glial cells, choroid plexus epithelial cells, ependymal cells, and the neuropil. Systemic manifestations included HPAI-related necrotizing myocarditis in the elephant seal and placental necrosis in a sea lion, with fetal tissues testing positive for HPAIV. Pulmonary lesions were minimal, limited to bronchial glands in one individual. RT-sqPCR confirmed HPAI H5 in all tested animals. Our findings highlight the neurotropism of HPAI H5N1 in pinnipeds, and expand the known systemic effects of the virus, revealing new tissue tropism and vertical transmission.
Synergistic MAPT mutations as a platform to uncover modifiers of tau pathogenesis
Authors: Bryan Miles R , Almeida Michael , Opland Carli , McGillion-Moore Jake , Trzeciakiewicz Hanna , King Diamond , Tian Xu , Tseng Jui-Heng , Schisler Jonathan , Bahr Ben , Cohen Todd J
Published: February 2025

The natively unfolded tau protein is extremely soluble, which poses challenges when modeling neurofibrillary tangle (NFT) pathology in Alzheimers disease (AD). To overcome this hurdle, we combined P301L and S320F mutations (PL-SF) to generate a rapid and reliable platform to expedite the discovery of factors that modulate tau aggregation. Using this model, we evaluated heat-shock proteins (Hsp), traditionally linked to tau pathology, but whose role in AD remains enigmatic and controversial. In primary neurons, expression of Hsp70, but not Hsc70 or Hsp90, exacerbated tau aggregation. Conversely, lowering of Hsp70 by shRNA or a chaperone-deficient tau mutant (PL-SF-4delta) reduced tau phosphorylation and abrogated tau aggregation, highlighting Hsp70 as a key driver of tau aggregation. Functionally, mature aggregate-bearing neurons showed deficits in neuronal firing and network communication, while chaperone-binding deficient tau variants displayed reduced tau pathology and restored network properties. This study provides a powerful cell intrinsic model for accelerated tau aggregation, which can be harnessed to identify regulators of tau aggregation as promising therapeutic targets.
Multiplexed CRISPRi Reveals a Transcriptional Switch Between KLF Activators and Repressors in the Maturing Neocortex
Authors: Kirk Ryan W , Sun Liwei , Xiao Ruixuan , Clark Erin A , Nelson Sacha
Published: February 2025

A critical phase of mammalian brain development takes place after birth. Neurons of the mouse neocortex undergo dramatic changes in their morphology, physiology, and synaptic connections during the first postnatal month, while properties of immature neurons, such as the capacity for robust axon outgrowth, are lost. The genetic and epigenetic programs controlling prenatal development are well studied, but our understanding of the transcriptional mechanisms that regulate postnatal neuronal maturation is comparatively lacking. By integrating chromatin accessibility and gene expression data from two subtypes of neocortical pyramidal neurons in the neonatal and maturing brain, we predicted a role for the Krüppel-Like Factor (KLF) family of Transcription Factors in the developmental regulation of neonatally expressed genes. Using a multiplexed CRISPR Interference (CRISPRi) knockdown strategy, we found that a shift in expression from KLF activators (Klf6, Klf7) to repressors (Klf9, Klf13) during early postnatal development functions as a transcriptional ‘switch’ to first activate, then repress a set of shared targets with cytoskeletal functions includingTubb2bandDpysl3. We demonstrate that this switch is buffered by redundancy between KLF paralogs, which our multiplexed CRISPRi strategy is equipped to overcome and study. Our results indicate that competition between activators and repressors within the KLF family regulates a conserved component of the postnatal maturation program that may underlie the loss of intrinsic axon growth in maturing neurons. This could facilitate the transition from axon growth to synaptic refinement required to stabilize mature circuits.
Repeated application of bifocal transcranial alternating current stimulation (tACS) improves network connectivity and driving performance: a double-blind sham control study
Authors: Fujiyama Hakuei , Bowden Vanessa K. , Tang Alexander D , Tan Jane , Librizzi Elisha , Loft Shayne
Published: February 2025

Mounting evidence suggests that transcranial alternating current stimulation (tACS) can enhance response inhibition, a cognitive process crucial for sustained effort and decision-making. However, most prior studies have focused on within-session effects, with limited investigation into the effects of repeated applications, which are crucial for clinical applications. We examined the effects of repeated bifocal tACS targeting the right inferior frontal gyrus (rIFG) and pre-supplementary motor area (preSMA), regions implicated in response inhibition, on inhibitory control. We also explored changes to functional connectivity and whether this stimulation improved simulated driving performance. Thirty young adults (18–35 years) were assigned to either a sham or tACS group (20 Hz, 20 minutes), undergoing five stimulation sessions over two weeks. Resting-state electroencephalography (EEG) was used to assess functional connectivity between the preSMA and rIFG during the first and fifth bifocal tACS sessions and at a 7-day follow-up. Response inhibition was measured using a stop-signal task (SST) administered throughout the sessions. Participants completed two simulated driving tasks (braking, general driving) before the first and after the final tACS intervention. Results revealed a significant improvement in functional connectivity in the tACS group across sessions, although no changes were observed in response inhibition and the braking task. Notably, general driving performance improved, with participants demonstrating closer adherence to the speed limit and greater spare attentional capacity. These findings highlight the potential of repeated bifocal tACS to enhance functional connectivity and related cognitive and motor processes, suggesting promising clinical applications for addressing issues related to cortical connectivity.
Sparse deconvolution of cell type medleys in spatial transcriptomics
Authors: Sogunmez Erdogan Nuray , Eroglu Deniz
Published: February 2025

Mapping cell distributions across spatial locations with whole-genome coverage is essential for understanding cellular responses and signaling pathways. However, current deconvolution models often assume strong overlap between reference and spatial datasets, neglecting biological constraints like sparsity and cell-type variations. As a result, these methods rely on brute-force algorithms that ignore tissue complexity, leading to inaccurate predictions, particularly in heterogeneous or unmatched datasets.

We introduce Weight-Induced Sparse Regression (WISpR), a machine learning algorithm that integrates spot-specific hyperparameters and sparsity-driven modeling. Unlike brute-force methods, WISpR accurately predicts cell-type distributions while maintaining biological coherence, even in unmatched datasets. Benchmarking against five leading methods across ten datasets, WISpR consistently outperformed competitors and predicted cellular landscapes in both normal and cancerous tissues.

By leveraging sparse cell-type arrangements, WISpR provides biologically informed, high-resolution cellular maps. Its ability to decode tissue organization in both healthy and diseased states marks a major advancement in spatial transcriptomics, setting a new standard for accurate deconvolution.
Correlation ofin vitrobiofilm formation capacity with persistence of antibiotic-resistantEscherichia colion gnotobiotic lamb’s lettuce
Authors: Schlechter Rudolf O. , Marti Elisabet , Remus-Emsermann Mitja N. P. , Drissner David , Gekenidis Maria-Theresia
Published: February 2025

Bacterial contamination of fresh produce is a growing concern for food safety, as apart from human pathogens, antibiotic-resistant bacteria can persist on fresh leafy produce. A prominent persistence trait in bacteria is biofilm formation, as it provides increased tolerance to stressful conditions. We screened a comprehensive collection of 174 antibiotic-susceptible and -resistantEscherichia colioriginating from fresh leafy produce and its production environment. We tested the ability of these strains to produce biofilms, ranging from none or weak to extreme biofilm-forming bacteria. Next, we tested the ability of selected antibiotic-resistant isolates to colonize gnotobiotic lamb’s lettuce (Valerianella locusta) plants. We hypothesized that a higherin vitrobiofilm formation capacity correlates with increased colonization of gnotobiotic plant leaves. Despite a marked difference in the ability to formin vitrobiofilms for a number ofE. colistrains,in vitrobiofilm formation was not associated with increased survival on gnotobioticV. locustaleaf surfaces. However, all tested strains persisted for at least 21 days, highlighting potential food safety risks through unwanted ingestion of resistant bacteria. Population densities of biofilm-formingE. coliexhibited a complex pattern, with subpopulations more successful in colonizing gnotobioticV. locustaleaves. These findings emphasise the complex behaviour of antibiotic-resistant bacteria on leaf surfaces and their implications to human safety.

Importance

Each raw food contains a collection of microorganisms, including bacteria. This is of special importance for fresh produce such as leafy salads or herbs, as these foods are usually consumed raw or after minimal processing, whereby higher loads of living bacteria are ingested than with a food that is heated before consumption. A common bacterial lifestyle involves living in large groups embedded in secreted protective substances. Such bacterial assemblies, so-called biofilms, confer high persistence and resistance of bacteria to external harsh conditions. In our research we investigated whether strongerin vitrobiofilm formation of antibiotic-resistantEscherichia colicorrelates with a better survival on lamb’s lettuce leaves. Although no clear correlation was observed between biofilm formation capacity and population density on the salad, all tested isolates could survive for at least three weeks with no significant decline over time, highlighting a potential food safety risk independently ofin vitrobiofilm formation.
MAIT cells protect in severe pneumococcal pneumonia by regulating neutrophil/macrophage antimicrobial activities
Authors: Barsac Emilie , Gonzalez Loïc , Ilango Guy , Hankard Antoine , Jouan Youenn , Lemoine Roxane , Minhas Vikrant , Lenain Marion , Benard Matthieu , Fernandez Mégane , Gaudio Albanne , Si-Tahar Mustapha , Guillon Antoine , Mallevaey Thierry , Ganskow Charity Siu Gee , Klahn Philipp , Veening Jan-Willem , Salou Marion , Lantz Olivier , Baranek Thomas , Paget Christophe
Published: February 2025

Mucosal-Associated Invariant T (MAIT) cells populate the lung tissue where they contribute to defense against respiratory infections. While MAIT cells have been implicated in host resistance to infections caused by Gram-negative bacteria, their contribution in immunity against Gram-positive bacteria-driven pneumonia is still enigmatic. Here, we demonstrate that both mouse and human MAIT cells are activated during severe infection caused byStreptococcus pneumoniae,the major cause of community-acquired bacterial pneumonia. Upon infection, lung MAIT cells undergo a transcriptional reprogramming associated with acquisition of potent antimicrobial properties. MAIT cell-deficient mice are more susceptible to pneumococcal pneumonia, including higher mortality, uncontrolled bacterial growth and dissemination, and impaired neutrophil and interstitial macrophage activity. Moreover, prophylactic stimulation of MAIT cells using cognate antigen protects from pneumococcus-induced lethal pneumonia. These findings demonstrate that MAIT cells are key cellular actors during Gram-positive bacterial infections.
Evaluating the use of Monte Carlo simulation for statistically assessing topological congruence of phylogenetic trees
Authors: DuBose James G.
Published: February 2025

Many questions in evolutionary biology involve assessing the topological congruence between phylogenetic trees. However, quantification of tree congruence provides a single measurement that is often difficult to contextualize and use to make inferences. One approach to statistically inform measurements of tree congruence is to generate null congruence distributions using Monte Carlo simulations, which can then be used for hypothesis testing. Although this approach has previously been used in empirical studies, its validity and effectiveness have yet to be tested. Here, I evaluate this method in combination with a variety of commonly used congruence metrics. I first explore how the number of simulations conducted influences the stability of null model generation. I then explore the error and power associated with different congruence metrics and tree sizes. These findings reveal nuances to this approach that are important for researchers to consider when using it to make evolutionary inferences. Finally, I introducemanticore, an R library that provides a simple interface for researchers to utilize this approach.
Dispersive interactions determine Urea and TMAO thermodynamic effects across the protein folding landscape
Authors: Pereira Ander Francisco , Martínez Leandro
Published: February 2025

The molecular mechanisms by which osmolytes promote protein denaturation or protection are under permanent debate, because the characterization of the structure and solvation of denatured states is a major challenge. Here we show that similar qualitative interactions occur between urea and TMAO and the β-sheet SH3 domain and the helical B domain of protein A (BdpA). The strength of non-specific interactions is the determining feature for cosolvent preferential accumulation or exclusion and dictate the free energy differences of native and denatured states. Urea and TMAO hydrogen-bonds with the proteins, on the other side, are disfavored in the denatured states relative to water. Notably, urea destabilizes partially denatured states of BdpA, which are only marginally affected by TMAO, demonstrating that osmolytes can also selectively interfere with denaturation pathways. These analyses are possible by the study of the solvation structures throughout complete folding landscapes using coarse-grained and atomistic simulations, the use of minimum-distance distribution functions, and the Kirkwood-Buff solvation theory. Cosolvent effects on folding free energies match experimental data within 1 kcal mol-1, validating force-fields and analysis methods. These findings provide a novel perspective on osmolyte-protein interplay, with implications for solvent and biomolecular design.
Human colon stem cells are the principal epithelial responders to bacterial antigens
Authors: de Vries Maaike Hillegonda , Meddens Claartje , Hijma Hemme , Berrens Anne-Claire , Jansen Suze , Kooiman Berend , Snapper Scott , Clevers Hans , Mokry Michal , Kuijk Ewart , Nieuwenhuis Edward
Published: February 2025

Intestinal epithelial cells (IECs) are capable of mounting an adequate antimicrobial inflammatory response to pathogens while tolerating commensals. The underlying regulatory mechanisms of immune sensitivity remain incompletely understood, particularly in the context of human IECs. To enhance our understanding of the immune response of IECs to bacterial epithelial barrier breach, we investigated whether epithelial responsiveness is contingent on cell identity and cell polarization. We exposed human intestinal organoids to bacterial antigens to study their immune responses. Notable discrepancies were observed in the specific reactions exhibited by intestinal stem cells (ISCs) and enterocytes. It was determined that basolateral exposure of IECs to bacterial antigens resulted in a robust response, whereas apical exposure elicited a significantly more modest response. We identified ISCs as the responders, while the reaction of enterocytes was found to be attenuated. The regulation of bacterial responsiveness in enterocytes occurs at multiple levels, including the modulation of NFκB activation and post-transcriptional control of mRNA stability. Our findings demonstrate that differentiated non-responsive enterocytes can be sensitized to bacterial antigens through the activation of the WNT pathway. These findings extend the crucial role of WNT signaling for intestinal epithelial homeostasis and regulation of stem cell maintenance, proliferation, differentiation, and tissue architecture in the gut. Additionally, they reveal a new function of WNT signaling in regulating microbial responses within the intestinal environment.
Rot or not? Uncovering the spatial patterns and drivers of Norway spruce root rot with harvester data
Authors: Suvanto Susanne , Heikkinen Juha , Holmström Eero , Honkaniemi Juha , Piri Tuula , Hantula Jarkko , Räsänen Tapio , Riekki Kirsi , Sorsa Juha-Antti , Hytönen Harri , Höglund Henna , Rajala Tuomas , Lehtonen Aleksi , Peltoniemi Mikko
Published: February 2025

Root rot is a major problem for forestry, leading to reduced timber quality, growth losses, and increased disturbance risks. Harvester data provides a promising source of information for improving the knowledge on the root rot distribution. Here, we used harvester data (1) to map the risk of spruce root rot in southern and central Finland, and (2) to understand the drivers of the spatial patterns in rot occurrence. First, we built a statistical model predicting the percentage of stems affected by root rot on stand-level. To train the model, we used an extensive set of harvester data, containing 10,402 clear-cut forest stands, where the presence of root rot was recorded for each cut tree using an algorithm based on bucking patterns (i.e., cutting of the stem into different log assortments) recorded by the harvester. The model consisted of two parts, a fixed component describing the effects of different drivers of root rot, and a spatial random component describing the spatial patterns not explained by the fixed part of the model. The fixed part included forest and site attributes, landscape characteristics and proxies of forest-use legacies. The model was then used to map root rot risk, by predicting the probability of root rot occurrence using spatial data sets of the variables in the fixed part of the model, and the known rot status of locations in the data set for the random part of the model. Finally, the map was tested with an independent validation data, verifying its ability to identify the high-risk areas. Proxies of forest-use legacies, tree size and site fertility were found to drive the percentage of rot-affected stems in stands. The results quantify the root rot risk in Finland in higher detail than before and demonstrate the large potential of harvester data in informing about the risk of root rot in boreal forests.
Pangenome graph augmentation from unassembled long reads
Authors: Denti Luca , Bonizzoni Paola , Brejova Brona , Chikhi Rayan , Krannich Thomas , Vinar Tomas , Hormozdiari Fereydoun
Published: February 2025

Pangenomes are becoming increasingly popular data structures for genomics analyses due to their ability to compactly represent the genetic diversity within populations. Constructing a pangenome graph, however, is still a time-consuming and expensive process. A promising approach for pangenome construction consists of progressively augmenting a pangenome graph with additional high-quality assemblies. Currently, there is no approach to augment a pangenome graph using unassembled reads from newly sequenced samples that does not require to align them and genotype the new individuals.

In this work, we present the first assembly-free and mapping-free approach for augmenting an existing pangenome graph using unassembled long reads from an individual not already present in the pangenome. Our approach consists of finding sample specific sequences in reads using efficient indexes, clustering reads corresponding to the same novel variant(s), and then building a consensus sequence to be added to the pangenome graph for each variant separately.

Using simulated reads based on Human Pangenome Reference Consortium (HPRC) assemblies, we demonstrate the effectiveness of the proposed approach for progressively augmenting the pangenome with long reads, without the need forde novoassembly or predicting genetic variants of the new sample. The software is freely available athttps://github.com/ldenti/palss.
Constitutive and regulatory responses ofArabidopsis thalianato harmonically oscillating light
Authors: Niu Yuxi , Fuente David , Matsubara Shizue , Lazár Dušan , Nedbal Ladislav
Published: February 2025

The rate of net CO2uptake is proportional to dim light and saturates when the light exceeds the plant assimilation capacity. This simple relationship between constant light and photosynthesis becomes intriguingly complex when the light oscillates. The rates of photosynthesis may differ between the descending and ascending phases of light oscillation. This hysteresis changes with the frequency and amplitude of the light and reports on the dynamics of the photosynthetic reactions and their regulation. Here, we investigated the chlorophyll fluorescence response ofArabidopsis thalianato light oscillating with three different amplitudes: 100–200, 100–400, and 100–800 μmol photons·m-2·s-1, each with periods ranging from 1 s to 8 min. The light amplitudes and periods were chosen to represent light patterns often appearing in nature. Three genotypes were compared: wild-type Col-0 andnpq1andnpq4mutants that are incapacitated in the rapidly reversible energy-dependent non-photochemical quenching (qE). The experiments identified two major dynamic patterns. One was found in oscillation periods shorter than 30 s, characterized by constitutive non-linearity and hysteresis. The other was mainly formed by regulatory non-linearity and hysteresis, occurring when the oscillation periods were longer than 30 s. The mathematical model simulating the chlorophyll fluorescence dynamics qualitatively reproduced the constitutive and regulatory dynamic patterns observed in the experiments. The model simulations illustrated the dynamics of non-photochemical quencher activation, plastoquinone pool reduction, and lumen pH that form the constitutive and regulatory non-linearities. The model simulations provided mechanistic insight into molecular processes forming the plant response to oscillating light.