bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Folding Mechanism of an Artificial Knotted Protein Characterized by Optical Tweezers.
Authors: Bustamante Andrés , Rivera Maira , Molina José , Baez Mauricio 
Published: November 2023

Protein folding occurs because establishment of weak interactions observed in the native state (native contacts) predominate over the formation of transient interactions that could promote alternative conformations (non‐native contacts). However, knotted proteins defy this view because their polypeptide chains would require to form non‐native contacts during its folding. To determine the role of non‐native contacts in such topologies, we explored the folding mechanism of an artificial knotted protein (2ouf‐knot). In this case, optimization of non‐native contacts should play a minor role during its folding. The folding of 2ouf‐knot was characterized maintaining the knotted topology in the unfolded state by pulling their C and N extremes by using optical tweezers. The molecular stretching of 2ouf‐knot obtained at constant velocity of pulling showed two transitions of unfolding occurring at 9 ± 1 and 14 ± 1 pN, followed by two transitions of refolding at 8 ± 1 and 12 ± 1 pN. This indicates the presence of an intermediate in both directions of the folding reaction of 2ouf‐knot. In terms of the molecular extension, the contour length (Lc) associated with the first transition at low force account for the 30% of the expected extension for the fully unfolded polypeptide. Notably, the intermediate of 2ouf‐knot was also apparent under equilibrium conditions. At constant force, 2ouf‐knot oscillates between the intermediate and the unfolded state extended by 5 and 16 nm with respect to the native state respectively. We observe that there was no full unfolding of the protein without visiting the intermediate state of 5 nm. Therefore, this specie is an obligate step (on‐pathway intermediate) for the complete unfolding of the protein. Nevertheless, we also observe that approximately 20% of the times the fully unfolded protein jump until reach a smaller intermediate of 4 nm with very short residence time. This short‐live off‐pathway intermediates backtrack to the fully unfolded state which refolds to the on‐pathway intermediate of 5 nm. These results contrast with the absence of intermediates (on and off‐pathway) in the case of a natural knotted protein (MJ0366 of Methanocaldococcus jannaschii) characterized under the same experimental setup. We suggest that the intermediates observed in the case of artificial knots arise by lack of specific non‐native contacts that could help to accommodate the knot during unfolding/refolding process. These specific interactions otherwise will help to smooth the energetic landscape of natural knotted proteins.Support or Funding InformationFondecyt 1151274, CONICYT fellowship No 21150966. CONICYT fellowship No 21130254.
Characterization of a putative monooxygenase involved in climate regulation from Hyphomicrobium sulfonivorans
Authors: Gordon Jackson M. , Culpepper Matthew B. , Culpepper Megen A. 
Published: November 2023

Dimethylsulfide (DMS) is a volatile organic sulfur compound that readily aerosolizes in the atmosphere. Aerosolized DMS products decrease solar radiation by increasing cloud albedo, resulting in overall climate cooling. DMS is degraded via bacterial metabolic pathways, including the enzyme DMS monooxygenase. DMS monooxygenase purified from Hyphomicrobium sulfonivorans has been identified as a two‐component enzyme in which a DmoA monooxygenase subunit couples with an NADH‐dependent FMNH2 oxidoreductase (DmoB) to catalyze DMS degradation. The putative DmoA monooxygenase subunit has been expressed recombinantly in E. coli, and purified to >99 % after gel filtration chromatography. A method has been developed to detect and quantitate enzymatic conversion of DMS to its product methanethiol by headspace gas chromatography coupled to a flame ionization detector. Ethanethiol is used as an internal standard. Peak resolution of the three analytes; DMS, ethanethiol, and methanethiol has been determined. Activity assays of the DmoA monooxygenase subunit are underway. In addition, the purified DmoA monooxygenase subunit has been crystallized by vapor diffusion under several sparse‐matrix screening conditions. Preliminary diffraction data supports that the crystals contain protein. Crystal optimization is underway to improve the resolution toward unraveling the three‐dimensional structure of the DmoA monooxygenase subunit.Support or Funding InformationThis research was funded by the Appalachian State University College of Arts and Sciences and Office of Student Research.
Diversity and evolutionary analysis of iron‐containing (Type‐III) alcohol dehydrogenases in the three domains of life
Authors: Julián‐Sánchez Adriana , Gaona‐López Carlos , Riveros‐Rosas Héctor 
Published: November 2023

Alcohol dehydrogenase (ADH) activity is widely distributed in the three domains of life. Currently, there are three non‐homologous NAD(P)+‐dependent ADH families reported: Type I ADH comprises Zn‐dependent ADHs; type II ADH comprises short‐chain ADHs described first in Drosophila; and, type III ADH comprises iron‐containing ADHs (FeADHs). These three families arose independently throughout evolution and possess different structures and mechanisms of reaction. While types I and II ADHs have been extensively studied, type III (iron‐activated) ADHs have been scarcely analyzed. Therefore in this work, a global phylogenetic analysis of iron‐activated ADHs was performed to get insights into the evolution of this protein family.Results showed that FeADHs are distributed in twenty two protein subfamilies, eight of them possessing protein sequences distributed in the three domains of life. Protein sequences from bacteria are present in all FeADH subfamilies, but protein sequences from archaea and eukarya are present in fourteen and thirteen subfamilies, respectively. Interestingly, none of these protein subfamilies possess protein sequences found simultaneously in the three main eukaryotic kingdoms (i.e., animals, plants and fungi).Animal FeADHs are found in just one protein subfamily, the hydroxyacid‐oxoacid transhydrogenase (HOT) subfamily, which includes protein sequences widely distributed in fungi, but not in plants), and in several taxa from lower eukaryotes, bacteria and archaea. Fungi FeADHs are found mainly in two subfamilies: HOT and maleylacetate reductase (MAR), but some can be found also in other three different protein subfamilies. Plant FeADHs are found only in chlorophyta but not in higher plants, and are distributed in three different protein subfamilies.In conclusion, FeADH is an ancient protein family that probably was present in the last common ancestor, and comprises a diversity of subfamilies that shares a common 3D scaffold that resulted with a patchy distribution in eukaryotes.Support or Funding InformationSupported by DGAPA‐UNAM grant IN225016.
Investigating the Catalytic Molecular Details of Malonyl‐thioester Decarboxylating Enzymes
Authors: Stunkard Lee Michael , Lohman Jeremy Michael 
Published: November 2023

Decarboxylation reactions release the free energy necessary for carbon‐carbon bond formation in the biosynthesis of polyketides and fatty acids. Ketosynthases from fatty acid and polyketide synthases perform a decarboxylative Claisen‐condensation between an acyl‐thioester intermediate and a malonyl‐derived extender unit. However, the molecular details of decarboxylation and C‐C bond formation is not well understood. We are synthesizing and characterizing non‐hydrolyzable and non‐decarboxylatable substrate mimics to capture intermediate catalytic states via X‐ray crystallography. Capturing the substrate mimics in the active site of ketosynthases will yield insight into the mechanism of decarboxylation and polymerization of the two carbon units. Decarboxylation reactions are essentially non‐reversible and have various possible chemical mechanisms, which makes them difficult to study. Ketosynthases are also challenging to study due to their multiple substrates and need for protein‐protein interactions. Therefore, we have begun characterization of our substrate mimics with simpler systems, such as malonyl‐ and methylmalonyl‐CoA decarboxylases (MCD and MMCD), as a proof of principle. We have successfully crystallized E. coli MMCD and the bifunctional acyltransferase/decarboxylase, LnmK, with our substrate mimics. Our substrate mimics preserve the thioester carbonyl as a thioester, ester or amide and have a nitro or sulfonate moiety in place of the carboxylate. Structures of MMCD and LnmK with multiple bound substrate mimics reveals mechanistic insight into decarboxylation. While MMCD and LnmK have no sequence homology to ketosynthases, this study reveals that our substrate mimics indeed inhibit decarboxylation reactions. Therefore, we are beginning to apply this concept to ketosynthases from type III polyketide synthases.Support or Funding InformationFunding provided by the Department of Biochemistry at Purdue University
How strong is enemy release? A systematic compilation across taxa and approaches
Authors: Zeng Karen , Schembri Jess , Slavich Eve , Moles Angela T. 
Published: November 2023

ABSTRACTThe enemy release hypothesis posits that introduced species escape some of their predators, pathogens and parasites when they move to a new range. We used a systematic review to compile data from 691 quantifications of enemy release spanning plants, animals and algae in aquatic and terrestrial systems worldwide. Data from 311 biogeographic contrasts (between home and new range) revealed that on average, a species experience only 30% as much enemy pressure in their introduced range as they experience in their native range. In contrast, data from 380 community contrasts (between native and introduced species) revealed that introduced species experience on average 57% of the enemy pressure that their native congeners endure. Interestingly, one third (36%) of contrasts showed higher, rather than lower, enemy pressure on the introduced population. Enemy release was consistently strong in contrasts of the diversity of enemies, intermediate in contrasts comparing enemy damage, and not significant in contrasts of host fitness, suggesting that while introduced populations are attacked by fewer enemies, this does not always result in higher fitness. We also found that enemy release was higher in molluscs and fish but lower in insects and algae, indicating that certain taxa may be favoured by enemy release. We hope that an improved understanding of the extent to which introduced species are released from enemy pressures will help managers to identify good opportunities for biocontrol, and to understand the factors likely to be affecting the success of invasive species.
Development and validation of a pharmacogenomics reporting workflow based on the Illumina Global Screening Array chip
Authors: Gan Pamela , Hajis Muhammad Irfan bin , Yumna Mazaya , Haruman Jessline , Matoha Husnul Khotimah , Wahyudi Dian Tri , Silalahi Santha , Oktariani Dwi Rizky , Dela Fitria , Annisa Tazkia , Pitaloka Tessalonika Damaris Ayu , Adhiwijaya Priscilla Klaresza , Pauzi Rizqi Yanuar , Hertanto Robby , Kumaheri Meutia Ayuputeri , Sani Levana , Irwanto Astrid , Pradipta Ariel , Chomchopbun Kamonlawan , Porta Mar Gonzalez 
Published: November 2023

AbstractBackgroundMicroarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction.However, establishing clinical reporting workflows requires a thorough evaluation of the assay’s performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes.MethodsTo evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets.ResultsIn our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance.ConclusionOur comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.
Genomic-guided conservation actions to restore the most endangered conifer in the Mediterranean Basin
Authors: del Valle José Carlos , Arista Montserrat , Benítez-Benítez Carmen , Ortiz Pedro Luis , Jiménez-López Francisco J. , Terrab Anass , Balao Francisco 
Published: November 2023

AbstractSpecies with extremely small population sizes are critically endangered due to reduced genetic diversity, increased inbreeding, and the added threat of hybridization. Genomic tools significantly advance conservation by revealing genetic insights into endangered species, notably in monitoring frameworks. Sicilian fir is the most endangered conifer in Europe with only 30 adult trees spread across an 84-hectare area. Using 20,824 SNPs from RAD-seq employing the silver fir genome assembly and a custom 120 SNP-array, we evaluated genetic diversity, mating patterns, and effective population size in adult trees, 118 natural seedlings, and 2,064 nursery seedlings from past conservation actions. We assessed introgression from neighboring non-native fir plantations and established an intra-population assisted gene flow program selecting the most genetically dissimilar individuals and investigating the outcome through simulations. Genomic analysis unveiled significant genetic diversity among adult Sicilian firs, comparable to non-endangered Mediterranean firs with larger populations. However, the genetic diversity of the forthcoming generation declined due to high self-fertilization, leading to marked inbreeding (Fis = 0.38) and an alarmingly low effective population size (Ne = 6). Nursery seedling monitoring revealed similar selfing rates but significant introgression (∼50%) from non-native firs. Although intra-population assisted gene flow could help to mitigate genetic loss, it may not alleviate the species vulnerability to imminent environmental challenges, perpetuating the risk of an extinction vortex. Hence, investigating the impact of Sicilian fir population decline and selfing on inbreeding depression, along with exploring the potential of hybrids for genetic load alleviation and future adaptation, is crucial for effective conservation strategies. This study stands as a compelling model for guiding conservation strategies in similarly imperiled species characterized by extremely small populations.
Genomic reconstruction of the successful establishment of a feralized bovine population on the subantarctic island of Amsterdam
Authors: Gautier Mathieu , Micol Thierry , Camus Louise , Moazami-Goudarzi Katayoun , Naves Michel , Guéret Elise , Engelen Stefan , Colas François , Flori Laurence , Druet Tom 
Published: November 2023

AbstractThe feral cattle of the subantarctic island of Amsterdam provide an outstanding case study of a large mammalian population that was established by a handful of founders and thrived within a few generations in a seemingly inhospitable environment. Here, we investigated the genetic history and composition of this population using genotyping and sequencing data. Our inference showed an intense but brief founding bottleneck around the late 19thcentury and revealed contributions from European taurine and Indian Ocean zebu in the founder ancestry. Comparative analysis of whole genome sequences further revealed a moderate reduction in genetic diversity despite high levels of inbreeding. The brief and intense bottleneck was associated with high levels of drift, a flattening of the site frequency spectrum and a slight relaxation of purifying selection on mildly deleterious variants. However, we did not observe any significant purge of highly deleterious variants.Interestingly, the population’s success in the harsh environment can be attributed to pre-adaptation from their European taurine ancestry, suggesting no strong bioclimatic challenge, and also contradicting evidence for insular dwarfism. Genome scan for footprints of selection uncovered a majority of candidate genes related to nervous system function, likely reflecting rapid feralization driven by behavioral changes and complex social restructuring. This unprecedented case study provides valuable insights into rapid population establishment, feralization, and genetic adaptation in challenging environments. It highlights the importance of preserving the unique genetic legacies of feral populations and raises ethical questions in the eyes of conservation efforts.
AptaBERT: Predicting aptamer binding interactions
Authors: Morsch Flemming , Umasankar Iswarya Lalitha , Moreta Lys Sanz , Latawa Paridhi , Lange Danny B. , Wengel Jesper , Konjen Huram , Code Christian 
Published: November 2023

AbstractAptamers, short single-stranded DNA or RNA, are promising as future diagnostic and therapeutic agents. Traditional selection methods, such as the Systemic Evolution of Ligands by Exponential Enrichment (SELEX), are not without limitations being both resource-intensive and prone to biases in library construction and the selection phase. Leveraging Dianox’s extensive aptamer database, we introduce a novel computational approach, AptaBERT, built upon the BERT architecture. This method utilizes self-supervised pre-training on vast amounts of data, followed by supervised fine-tuning to enhance the prediction of aptamer interactions with proteins and small molecules. AptaBERT is fine-tuned for binary classification tasks, distinguishing between positive and negative interactions with proteins and small molecules. AptaBERT achieves a ROC-AUC of 96% for protein interactions, surpassing existing models by at least 15%. For small molecule interactions, AptaBERT attains an ROC-AUC of 85%. Our findings demonstrate AptaBERT’s superior predictive capability and its potential to identify novel aptamers binding to targets.
Deep learning-based method to identify disease-resistance proteins inOryza sativaand relative species
Authors: Dhiman Vedikaa , Biswas Soham , Swain Asish Kumar , Sadhukhan Ayan , Yadav Pankaj 
Published: November 2023

AbstractRice (Oryza sativa) is a significant agricultural crop consumed by more than half of the global population. Its demand is expected to increase due to rising consumption and a growing global population. Moreover, the rice plant is frequently exposed to disease-causing pathogens, such as bacteria, fungi, viruses, and nematodes. Thus, cultivating disease-resistant varieties is an efficient way of disease control compared to pesticide applications. However, the rice plant has a well-defined defense system to prevent the onset of disease, including Pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) and effector-triggered immunity (ETI). The defense system is controlled by various disease-resistance proteins, such as resistance (R) proteins and pathogen recognition receptors (PRRs). Therefore, the identification of disease-resistance proteins not only reduces the amount of pesticides used in rice fields but also increases their yield. Though some resistant proteins have been characterized, their rapid identification, precise diagnosis, and appropriate management are still lacking. However, few methods based on sequence-similarity and de novo prediction, such as Machine Learning (ML), usually have low prediction power. In this study, we built a state-of-the-art classifier based on Deep Learning (DL) for the early detection of disease-resistance proteins in rice and related species. We compared the DL-based Multi-layer Perceptron (MLP) model with the five well-established ML-based methods using a protein dataset of rice and its related species. The DL-based MLP model outperformed all of the five classifiers on 10-fold cross-validation. The accuracy, Area Under Receiving Operating Characteristic (ROC) curve (AUC), F1-score, precision, and recall were superior in the DL-based MLP model. In conclusion, the MLP model is an effective DL model for predicting disease-resistance proteins with high scores in performance metrics. This study will provide insight to the breeders in developing disease-resistant rice varieties and assist in transforming traditional rice farming practices into a new age of smart rice farming.
A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations
Authors: Vanoni Marco , Palumbo Pasquale , Papa Federico , Busti Stefano , Gotti Laura , Wortel Meike , Teusink Bas , Orlandi Ivan , Pessina Alex , Airoldi Cristina , Brambilla Luca , Vai Marina , Alberghina Lilia 
Published: November 2023

SummaryFor unicellular organisms, the reproduction rate and growth are crucial determinants of fitness and, therefore, essential functional manifestations of the organism genotype. Using the budding yeastSaccharomyces cerevisiaeas a model organism, we integrated metabolism, which provides energy and building blocks for growth, with cell mass growth and cell cycle progression into a low-granularity, multiscale (from cell to population) computational model. This model predicted that cells with constitutive respiration do not modulate cell size according to the growth conditions. We experimentally validated the model predictions using mutants with defects in the upper part of glycolysis or glucose transport. Plugging in molecular details of cellular subsystems allowed us to refine predictions from the cellular to the molecular level. Our hybrid multiscale modeling approach provides a framework for structuring molecular knowledge and predicting cell phenotypes under various genetic and environmental conditions.