bluuebunny/crossref_metadata_2025_split huggingface dataset:
The evolution of antimicrobial peptide resistance inPseudomonas aeruginosais severely constrained by random peptide mixtures
Authors: Antunes B. , Zanchi C. , Johnston P.R. , Maron B. , Witzany C. , Regoes R. , Hayouka Z. , Rolff J. 
Published: February 2024

AbstractThe prevalence of antibiotic-resistant pathogens has become a major threat to public health, requiring swift initiatives for discovering new strategies to control bacterial infections. Hence, antibiotic stewardship and rapid diagnostics, but also the development, and prudent use, of novel effective antimicrobial agents are paramount. Ideally, these agents should be less likely to select for resistance in pathogens than currently available conventional antimicrobials. The usage of antimicrobial Peptides (AMPs), key components of the innate immune response, and combination therapies, have been proposed as strategies to diminish the emergence of resistance.Herein, we investigated whether newly developed random antimicrobial peptide mixtures (RPMs) can significantly reduce the risk of resistance evolutionin vitroto that of single sequence AMPs, using the ESKAPE pathogenPseudomonas aeruginosa(P. aeruginosa) as a model Gram-negative bacterium. Infections of this pathogen are difficult to treat due the inherent resistance to many drug classes, enhanced by the capacity to form biofilms.P. aeruginosawas experimentally evolved in the presence of AMPs or RPMs, subsequentially assessing the extent of resistance evolution and cross-resistance/collateral sensitivity between treatments. Furthermore, the fitness costs of resistance on bacterial growth were studied, and whole-genome sequencing used to investigate which mutations could be candidates for causing resistant phenotypes. Lastly, changes in the pharmacodynamics of the evolved bacterial strains were examined.Our findings suggest that using RPMs bears a much lower risk of resistance evolution compared to AMPs and mostly prevents cross-resistance development to other treatments, while maintaining (or even improving) drug sensitivity. This strengthens the case for using random cocktails of AMPs in favour of single AMPs, against which resistance evolvedin vitro, further providing an alternative to classic antibiotics worth pursuing.
Catabolism of germinant amino acids is required to prevent premature spore germination inBacillus subtilis
Authors: Kasu Iqra R. , Reyes-Matte Octavio , Bonive-Boscan Alejandro , Derman Alan I. , Lopez-Garrido Javier 
Published: February 2024

ABSTRACTSpores ofBacillus subtilisgerminate in response to specific germinant molecules that are recognized by receptors in the spore envelope. Germinants signal to the dormant spore that the environment can support vegetative growth, so many germinants, such as alanine and valine, are also essential metabolites. As such, they are also required to build the spore. Here we show that these germinants cause premature germination if they are still present at the latter stages of spore formation and beyond, but thatB. subtilismetabolism is configured to prevent this: alanine and valine are catabolized and cleared from wild-type cultures even when alternative carbon and nitrogen sources are present. Alanine and valine accumulate in the spent media of mutants that are unable to catabolize these amino acids, and premature germination is pervasive. Premature germination does not occur if the germinant receptor that responds to alanine and valine is eliminated, or if wild-type strains that are able to catabolize and clear alanine and valine are also present in coculture. Our findings demonstrate that spore-forming bacteria must fine-tune the concentration of any metabolite that can also function as a germinant to a level that is high enough to allow for spore development to proceed, but not so high as to promote premature germination. These results indicate that germinant selection and metabolism are tightly linked, and suggest that germinant receptors evolve in tandem with the catabolic priorities of the spore-forming bacterium.
A ribosome-associating chaperone mediates GTP-driven vectorial folding of nascent eEF1A
Authors: Sabbarini Ibrahim M. , Reif Dvir , Park Kibum , McQuown Alexander J. , Nelliat Anjali R. , Trejtnar Charlotte , Dötsch Volker , Shakhnovich Eugene I. , Murray Andrew W. , Denic Vladimir 
Published: February 2024

AbstractEukaryotic translation elongation factor 1A (eEF1A) is a highly abundant, multi-domain GTPase. Post-translational steps essential for eEF1A biogenesis are carried out by bespoke chaperones but co-translational mechanisms tailored to eEF1A folding remain unexplored. Here, we find that the N-terminal, GTP-binding domain of eEF1A is prone to co-translational misfolding and using computational approaches, yeast genetics, and microscopy analysis, we identify the conserved yet uncharacterized yeast protein Ypl225w as a chaperone dedicated to solving this problem. Proteomics and biochemical reconstitution reveal that Ypl225w’s interaction with ribosomal eEF1A nascent chains depends on additional binding of Ypl225w to the UBA domain of nascent polypeptide-associated complex (NAC). Lastly, we show by orthogonal chemical genetics that Ypl225w primes eEF1A nascent chains for their subsequent binding to GTP and release from Ypl225w. Our work establishes eEF1A as a model system for chaperone-dependent co-translational folding and unveils a novel mechanism for GTP-driven folding on the ribosome.
Laboratory evolution reveals transcriptional mechanisms underlying thermal adaptation ofEscherichia coli
Authors: Rychel Kevin , Chen Ke , Catoiu Edward A. , Olson Connor A. , Sandberg Troy E. , Gao Ye , Xu Sibei , Hefner Ying , Szubin Richard , Patel Arjun , Feist Adam M. , Palsson Bernhard O. 
Published: February 2024

AbstractAdaptive laboratory evolution (ALE) is able to generate microbial strains which exhibit extreme phenotypes, revealing fundamental biological adaptation mechanisms. Here, we use ALE to evolveEscherichia colistrains that grow at temperatures as high as 45.3°C, a temperature lethal to wild type cells. The strains adopted a hypermutator phenotype and employed multiple systems-level adaptations that made global analysis of the DNA mutations difficult. Given the challenge at the genomic level, we were motivated to uncover high temperature tolerance adaptation mechanisms at the transcriptomic level. We employed independently modulated gene set (iModulon) analysis to reveal five transcriptional mechanisms underlying growth at high temperatures. These mechanisms were connected to acquired mutations, changes in transcriptome composition, sensory inputs, phenotypes, and protein structures. They are: (i) downregulation of general stress responses while upregulating the specific heat stress responses; (ii) upregulation of flagellar basal bodies without upregulating motility, and upregulation fimbriae; (iii) shift toward anaerobic metabolism, (iv) shift in regulation of iron uptake away from siderophore production, and (v) upregulation ofyjfIJKL, a novel heat tolerance operon which we characterized using AlphaFold. iModulons associated with these five mechanisms explain nearly half of all variance in the gene expression in the adapted strains. These thermotolerance strategies reveal that optimal coordination of known stress responses and metabolism can be achieved with a small number of regulatory mutations, and may suggest a new role for large protein export systems. ALE with transcriptomic characterization is a productive approach for elucidating and interpreting adaptation to otherwise lethal stresses.
Deep plasma proteomics with data-independent acquisition: A fastlane towards biomarkers identification
Authors: Ward Bradley , Pyr dit Ruys Sébastien , Balligand Jean-Luc , Belkhir Leïla , Cani Patrice D. , Collet Jean-François , De Greef Julien , Dewulf Joseph P. , Gatto Laurent , Haufroid Vincent , Jodogne Sébastien , Kabamba Benoît , Lingurski Maxime , Yombi Jean Cyr , Vertommen Didier , Elens Laure 
Published: February 2024

AbstractPlasma proteomic is a precious tool in human disease research, but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional Data-Dependent Acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and Data-Independent Acquisition (DIA) to significantly improve proteome coverage and depth, while remaining cost- and time-efficient.Using human plasma collected from a 20-patient COVID-19 cohort, our method utilises commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 LC-MS/MS injections for a 360-minutes DIA run time. DIA-NN software was then used for precursor identification, and the QFeatures R package was used for protein aggregation.We detect 1,321 proteins on average per patient, and 2,031 unique proteins across the cohort. Filtering precursors present in under 25% of patients, we still detect 1,230 average proteins and 1,590 unique proteins, indicating robust protein identification. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification.In summary, this study introduces a streamlined, cost- and time-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multi-omics investigations in clinical settings.
Hyperbaric Oxygen-Induced acute lung injury: A Mouse Model Study on Pathogenesis and Recovery Dynamics
Authors: Wang Shu , Li Zhi , Xu Guangxu , Bao Xiaochen 
Published: February 2024

ABSTRACTHyperbaric oxygen (HBO) therapy is extensively used to treat a number of ailments. Although oxygen is crucial for survival, too much oxygen can be harmful. Excessive oxygen inhalation in a short period of time can lead to injury, and the lung is one of the main target organs. Lung injury induced by hyperbaric oxygen is notably more severe than that caused by normobaric oxygen, yet systematic research on such injury and its regression is scarce. In this study, mice were exposed to 2 atmospheres absolute (ATA), ⩾ 95% oxygen for 2, 4, 6, 8 hours. Changes in lung histopathology, inflammation and expression of chemokines, vascular endothelial permeability, 8-OHdG and apoptotic cells were detected before and after the exposure. These parameters were also measured immediately, 12 hours, and 24 hours following 6 hours of exposure to 2 ATA of ⩾95% oxygen. The study indicates that lung damage from HBO is histologically characterized by bronchiolar and alveolar dilation, atelectasis, inflammatory cell infiltration, and hemorrhage. At 2 ATA with over 95% oxygen for 4 hours, there is a significant increase in pulmonary vascular permeability, as evidenced by elevated Evans blue scores (p= 0.02). After 6 hours of HBO exposure, there is a significant rise in pulmonary tissue pathology scores, 8-OHdG levels, and inflammatory and chemotactic factors (such as IL-6, CCL2, CCL3, CXCL5, and CXCL10), along with intercellular adhesion molecule 1 (ICAM1), vascular cell adhesion molecule 1(VCAM1). Moreover, it was observed that these markers continued to progress even after leaving the hyperoxic environment, peaking at 12 hours and starting to recover after 24 hours, suggesting that the peak of inflammatory lung damage occurs within 12 hours post-exposure, with recovery beginning at 24 hours. However, the content of Evans Blue, reflecting vascular endothelial damage, and ICAM1, VCAM1 remain significantly elevated 24 hours after leaving the hyperoxic environment, indicating that the pulmonary vasculature endothelium is the most sensitive to damage and the slowest to recover in HBO-induced lung injury. These findings provide evidence for the prevention and treatment of acute lung injury complications caused by HBO.NEW & NOTEWORTHYThis study systematically observed the development and outcome changes of ALI induced by HBO. In lung injuries caused by high partial pressure of oxygen, the pulmonary vascular endothelial cells are the first to be damaged and the slowest to recover. A 6-hour exposure to 2 ATA, ⩾95% oxygen of hyperbaric oxygen primarily causes oxidative DNA damage and inflammatory responses without significant apoptosis. The lung injury progresses even after leaving the high-oxygen setting, with inflammation peaking at 12 hours post-exposure and beginning to subside after 24 hours.
Molecular and Cellular Mechanisms of Teneurin Signaling in Synaptic Partner Matching
Authors: Xu Chuanyun , Li Zhuoran , Lyu Cheng , Hu Yixin , McLaughlin Colleen N. , Wong Kenneth Kin Lam , Xie Qijing , Luginbuhl David J. , Li Hongjie , Udeshi Namrata D. , Svinkina Tanya , Mani D. R. , Han Shuo , Li Tongchao , Li Yang , Guajardo Ricardo , Ting Alice Y. , Carr Steven A. , Li Jiefu , Luo Liqun 
Published: February 2024

SUMMARYIn developing brains, axons exhibit remarkable precision in selecting synaptic partners among many non-partner cells. Evolutionally conserved teneurins were the first identified transmembrane proteins that instruct synaptic partner matching. However, how intracellular signaling pathways execute teneurin’s functions is unclear. Here, we usein situproximity labeling to obtain the intracellular interactome of teneurin (Ten-m) in theDrosophilabrain. Genetic interaction studies using quantitative partner matching assays in both olfactory receptor neurons (ORNs) and projection neurons (PNs) reveal a common pathway: Ten-m binds to and negatively regulates a RhoGAP, thus activating the Rac1 small GTPases to promote synaptic partner matching. Developmental analyses with single-axon resolution identify the cellular mechanism of synaptic partner matching: Ten-m signaling promotes local F-actin levels and stabilizes ORN axon branches that contact partner PN dendrites. Combining spatial proteomics and high-resolution phenotypic analyses, this study advanced our understanding of both cellular and molecular mechanisms of synaptic partner matching.HIGHLIGHTSIn situspatial proteomics reveal the first intracellular interactome of teneurinsTen-m signals via a RhoGAP and Rac1 GTPase to regulate synaptic partner matchingSingle-axon analyses reveal a stabilization-upon-contact model for partner matchingTen-m signaling promotes F-actin in axon branches contacting partner dendrites
Development and validation of a gene expression score to account for tumour purity and improve prognostication in breast cancer
Authors: Barreca Marco , Dugo Matteo , Galbardi Barbara , Győrffy Balázs ,   NA-PHER2 consortium,   NeoTRIP consortium, Valagussa Pinuccia , Besozzi Daniela , Viale Giuseppe , Bianchini Giampaolo , Gianni Luca , Callari Maurizio 
Published: February 2024

AbstractThe prevalence of malignant cells in clinical specimens, or tumour purity, is affected by both intrinsic biological factors and extrinsic sampling bias. Molecular characterization of large clinical cohorts is typically performed on bulk samples; data analysis and interpretation can be biased by tumour purity variability. Transcription-based strategies to estimate tumour purity have been proposed, but no breast cancer specific method is available yet.We interrogated over 4400 expression profiles from 9 breast cancer datasets to develop and validate a 9-gene Breast Cancer Purity Score (BCPS). BCPS outperformed existing methods for estimating tumour content. Adjusting transcriptomic profiles using the BCPS reduce sampling bias and aid data interpretation. BCPS-estimated tumour purity improved prognostication in luminal breast cancer, correlated with pathologic complete response in on-treatment biopsies from triple-negative breast cancer patients undergoing neoadjuvant treatment and effectively stratified the risk of relapse in HER2+ residual disease post-neoadjuvant treatment.
Photoreceptor-induced LHL4 protects photosystem II inChlamydomonas reinhardtii
Authors: Dannay Marie , Bertin Chloé , Cavallari Eva , Albanese Pascal , Tolleter Dimitri , Giustini Cécile , Menneteau Mathilde , Brugière Sabine , Couté Yohann , Finazzi Giovanni , Demarsy Emilie , Ulm Roman , Allorent Guillaume 
Published: February 2024

AbstractPhotosynthesis, the fundamental process using light energy to convert CO2to organic matter, is vital for life on Earth. It relies on capturing light through light-harvesting complexes in evolutionarily well-conserved photosystems (PS) I and II and on the conversion of light energy into chemical energy. Composition and organization of both photosystem core complexes are well conserved across evolution. PSII is particularly sensitive to photodamage but benefits from a large diversity of photoprotective mechanisms, finely tuned for the specific light conditions. Light Harvesting Complex protein family members (LHC and LHC-like families) have acquired a dual function during evolution. Members of the LHC antenna complexes of photosystems capture light energy whereas others dissipate excess energy that cannot be harnessed for photosynthesis. This process mainly occurs through non photochemical quenching (NPQ). In this work, we focus on the LHL4 protein, which is a LHC-like protein induced by UV-B and blue light photoreceptor signaling pathways in the model green microalgaeChlamydomonas reinhardtii. We demonstrate that alongside established NPQ effectors, LHL4 plays a key role in photoprotection, preventing singlet oxygen accumulation in PSII and promoting cell survival upon light stress. LHL4 protective function is distinct from that of NPQ-related proteins, as it specifically and uniquely binds to the transient monomeric form of the core PSII complex, safeguarding its integrity. LHL4 characterization expands our understanding of the interplay between light harvesting and photoprotection mechanisms upon light stress in photosynthetic microalgae.
Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex Diseases
Authors: Gholipourshahraki Tahereh , Bai Zhonghao , Shrestha Merina , Hjelholt Astrid , Kjølby Mads , Rohde Palle Duun , Sørensen Peter 
Published: February 2024

ABSTRACTGenome-wide association studies (GWAS) provide valuable insights into the genetic architecture of complex traits, yet interpreting their results remains challenging due to the polygenic nature of most traits. Gene set analysis offers a solution by aggregating genetic variants into biologically relevant pathways, enhancing the detection of coordinated effects across multiple genes. In this study, we present and evaluate a gene set prioritization approach utilizing Bayesian Linear Regression (BLR) models to uncover shared genetic components among different phenotypes and facilitate biological interpretation. Through extensive simulations and analyses of real traits, we demonstrate the efficacy of the BLR model in prioritizing pathways for complex traits. Simulation studies reveal insights into the model’s performance under various scenarios, highlighting the impact of factors such as the number of causal genes, proportions of causal variants, heritability, and disease prevalence. Application of both single-trait and multi-trait BLR models to real data, specifically GWAS summary data for type 2 diabetes (T2D) and related phenotypes, identifies significant associations with T2D-related pathways. Furthermore, comparison between single- and multi-trait BLR analyses highlights the superior performance of the multi-trait approach in identifying associated pathways, showcasing increased statistical power when analyzing multiple traits jointly. Additionally, enrichment analysis with integrated data from various public resources supports our results, confirming significant enrichment of diabetes-related genes within the top T2D pathways resulting from the multi-trait analysis. The BLR model’s ability to handle diverse genomic features, perform regularization, conduct variable selection, and integrate information from multiple traits, genders, and ancestries demonstrates its utility in understanding the genetic architecture of complex traits. Our study provides insights into the potential of the BLR model to prioritize gene sets, offering a flexible framework applicable to various datasets. This model presents opportunities for advancing personalized medicine by exploring the genetic underpinnings of multifactorial traits, potentially leading to tailored therapeutic interventions.
Mitochondrial origins of the pressure to sleep
Authors: Sarnataro Raffaele , Velasco Cecilia D. , Monaco Nicholas , Kempf Anissa , Miesenböck Gero 
Published: February 2024

SummaryThe neural control of sleep requires that sleep need is sensed during waking and discharged during sleep. To obtain a comprehensive, unbiased view of molecular changes in the brain that may underpin these processes, we have characterized the transcriptomes of single cells isolated from rested and sleep-deprived flies. Transcripts upregulated after sleep deprivation, in sleep-control neurons projecting to the dorsal fan-shaped body (dFBNs) but not ubiquitously in the brain, encode almost exclusively proteins with roles in mitochondrial respiration and ATP synthesis. These gene expression changes are accompanied by mitochondrial fragmentation, enhanced mitophagy, and an increase in the number of contacts between mitochondria and the endoplasmic reticulum, creating conduits for the replenishment of peroxidized lipids. The morphological changes are reversible after recovery sleep and blunted by the installation of an electron overflow in the respiratory chain. Inducing or preventing mitochondrial fission or fusion in dFBNs alters sleep and the electrical properties of sleep-control cells in opposite directions: hyperfused mitochondria increase, whereas fragmented mitochondria decrease, neuronal excitability and sleep. ATP levels in dFBNs rise after enforced waking because of diminished ATP consumption during the arousal-mediated inhibition of these neurons, which predisposes them to heightened oxidative stress. Consistent with this view, uncoupling electron flux from ATP synthesis relieves the pressure to sleep, while exacerbating mismatches between electron supply and ATP demand (by powering ATP synthesis with a light-driven proton pump) promotes sleep. Sleep, like ageing, may be an inescapable consequence of aerobic metabolism.
Is myeloid-derived growth factor a ligand of the sphingosine-1-phosphate receptor 2?
Authors: Zheng Yong-Shan , Liu Ya-Li , Xu Zeng-Guang , He Cheng , Guo Zhan-Yun 
Published: February 2024

ABSTRACTSecretory myeloid-derived growth factor (MYDGF) exerts beneficial effects on organ repair, probably via a plasma membrane receptor; however, the identity of the expected receptor has remained elusive. In a recent study, MYDGF was reported as an agonist of the sphingosine-1-phosphate receptor 2 (S1PR2), an A-class G protein-coupled receptor that mediates the functions of the signaling lipid, sphingosine-1-phosphate (S1P). In the present study, we conducted living cell-based functional assays to test whether S1PR2 is a receptor for MYDGF. In the NanoLuc Binary Technology (NanoBiT)-based β-arrestin recruitment assay and the cAMP-response element (CRE)-controlled NanoLuc reporter assay, S1P could efficiently activate human S1PR2 overexpressed in human embryonic kidney (HEK) 293T cells; however, recombinant human MYDGF, overexpressed either fromEscherichia colior HEK293 cells, had no detectable effect. Thus, the results demonstrated that human MYDGF is not a ligand of human S1PR2. Considering the high conservation of MYDGF and S1PR2 in evolution, MYDGF is also probably not a ligand of S1PR2 in other vertebrates.