bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating proteomics imputation methods with improved criteria
Authors: Harris Lincoln , Fondrie William E. , Oh Sewoong , Noble William S. 
Published: April 2023

AbstractQuantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. This missingness hinders reproducibility, reduces statistical power, and makes it difficult to compare across samples or experiments. Although many methods exist for imputing missing values in proteomics data, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error, such as the mean-squared error between the imputed and the held-out observed values. Here we evaluate the performance of a set of commonly used imputation methods using three practical, “downstream-centric” criteria, which measure the ability of imputation methods to reconstruct differentially expressed peptides, identify new quantitative peptides, and improve peptide lower limit of quantification. Our evaluation spans several experiment types and acquisition strategies, including datadependent and data-independent acquisition. We find that imputation does not necessarily improve the ability to identify differentially expressed peptides, but that it can identify new quantitative peptides and improve peptide lower limit of quantification. We find that MissForest is generally the best performing method per our downstream-centric criteria. We also argue that exisiting imputation methods do not properly account for the variance of peptide quantifications and highlight the need for methods that do.
Doxorubicin inhibits phosphatidylserine decarboxylase and confers broad-spectrum antifungal activity
Authors: Zhou Yaru , Zhao Juan , Yang Lei , Bi Ruiqing , Qin Ziting , Sun Peng , Li Renjian , Zhao Mengfei , Wang Yin , Chen Guang , Wan Hu , Zheng Lu , Chen Xiao-Lin , Wang Guanghui , Li Qiang , Li Guotian 
Published: April 2023

SummaryAs phospholipids of cell membranes, phosphatidylethanolamine (PE) and phosphatidylserine (PS) play crucial roles in glycerophospholipid metabolism. Broadly, some phospholipid biosynthesis enzymes serve as potential fungicide targets. Therefore, revealing the functions and mechanism of PE biosynthesis in plant pathogens would provide potential targets for crop disease control.We performed analyses including phenotypic characterizations, lipidomics, enzyme activity, site-directed mutagenesis, and chemical inhibition assays to study the function of PS decarboxylase-encoding geneMoPSD2in rice blast fungusMagnaporthe oryzae.TheMopsd2mutant was defective in development, lipid metabolism and plant infection. The PS level increased while PE decreased inMopsd2, consistent with the enzyme activity. Furthermore, chemical doxorubicin inhibited the enzyme activity of MoPsd2 and showed antifungal activity against ten phytopathogenic fungi includingM. oryzaeand reduced disease severity of two crop diseases in the field. Three predicted doxorubicin-interacting residues are important for MoPsd2 functions.Our study demonstrates that MoPsd2 is involved inde novoPE biosynthesis and contributes to the development and plant infection ofM. oryzaeand that doxorubicin shows broad-spectrum antifungal activity as a fungicide candidate. The study also implicates that bacteriumStreptomyces peucetius, which biosynthesizes doxorubicin, could be potentially used as an eco-friendly biocontrol agent.
Deep origin of the long root tuft: the oldest stalk-bearing sponge from the Cambrian Stage 3 black shale of South China
Authors: Yun Hao , Janussen Dorte , Zhang Xingliang , Reitner Joachim 
Published: April 2023

AbstractIn virtue of remarkable tolerance on hypoxia and adaptive specialization in morphology, diverse hexactinellid sponges were prosperous in an early Cambrian living condition that characterized by dysoxic to anoxic bottom waters documented by black shales. New fossils from the black shale of Niutitang Formation (basal Stage 3 of Cambrian) in Hunan Province of China, reveal for the first time an articulated body of the spongeHyalosinica archaicaMehl & Reitner in Steineret al., 1993, which possesses an ovoid main body and an impressive long stalk. The specular skeleton includes large diactines that are generally organized as fan-shaped clusters, a few small stauractines and hexactines, and twisted bundles of long monaxons that form the stalk/root tuft. This hexactinellid sponge represents the oldest extinct taxon that took advantage of a long stalk to elevate the main body above the sediment surface and thus to adapt to the oxygen-deficient sea-bottom environment. The long root tuft linksHyalosinicato a series of fossil and recent sponge taxa and proves a deep origin of the stalk-bearing morphology, indicating a likely parallel evolution within the Hexactinellida in response to special environmental pressures. Furthermore, the overall skeletal organization indicates thatHyalosinica, as well as related early “rossellimorphs”, are basal stem group representatives of Hexactinellida and probably branched before the extinct Reticulosa and before the two extant hexactinellid subclasses.
MOViDA: Multi-Omics Visible Drug Activity Prediction with a Biologically Informed Neural Network Model
Authors: Ferraro Luigi , Scala Giovanni , Cerulo Luigi , Carosati Emanuele , Ceccarelli Michele 
Published: April 2023

AbstractDrug discovery is a challenging task, characterized by a protracted period of time between initial development and market release, with a high rate of attrition at each stage. Computational virtual screening, powered by machine learning algorithms, has emerged as a promising approach for predicting therapeutic efficacy. However, the complex relationships between features learned by these algorithms can be challenging to decipher. We have devised a neural network model for the prediction of drug sensitivity, which employs a biologically-informed visible neural network (VNN), enabling a greater level of interpretability. The trained model can be scrutinized to investigate the biological pathways that play a fundamental role in prediction, as well as the chemical properties of drugs that influence sensitivity. The model leverages multi-omics data obtained from diverse tumor tissue sources and molecular descriptors that encode drug properties. We have extended the model to predict drug synergy, resulting in favorable outcomes while retaining interpretability. Given the often imbalanced nature of publicly available drug screening datasets, our model demonstrates superior performance compared to state-of-the-art visible machine learning algorithms.
DEVELOPMENTAL ULTRASTRUTCTURE MICROSCOPY IN DRUG DISCOVERY FROM DIOSCOREA SPECIES
Authors: Odimegwu Joy Ifunanya , Sangwan Neelam Singh , Chanotiya C. S. , Steve Ogbonnia , Abiodun Odukoya Olukemi 
Published: April 2023

ABSTRACTTubers of wild Dioscorea species (yam) are used as low-cost materials for the synthesis of steroids; cortisone and progesterone using the Marker Degradation chemical route. Decoctions from yam leaves and tubers are also used in ethnomedicine for regulating female fertility and alleviating painful periods and menopausal symptoms. It is now known that yam tuber extracts reduce and inhibit the proliferative action of breast cancer cells and reverse cardiovascular diseases.Due to current urgent needs and global interest in plants’ biodiversity advancement and drug discovery importance:Dioscorea compositaandDioscorea floribundashoots were studied with Scanning Electron Microscopy (SEM) to detect anatomical types of trichomes compared to essential oil production as integrated into the ontogeny of the studied shoots and hydro-distilled oils from the same organs were characterized with Gas Chromatography/Mass Spectrometry (GC/MS).The SEM study revealed the presence of oil glands, the capitate type on the epidermal layers of parts studied which GC/MS analysis further revealed the components of the oils on the leaves to be Farnesene, Citronellyl acetate, Terpinene, Elemol, Nerolidol, Farnesol and Valerenyl acetate. This is the first time these phytoconstituents are reported in the species. In this light, microscopical methods supported by chromatography contribute to the rapid identification of novel lead compounds contributing to important drug discovery.
Structural RNA components supervise the sequential DNA cleavage in R2 retrotransposon
Authors: Deng Pujuan , Tan Shun-Qing , Yang Qi-Yu , Zhu Han-Zhou , Sun Lei , Bao Zhangbin , Lin Yi , Zhang Qiangfeng Cliff , Wang Jia , Liu Jun-Jie Gogo 
Published: April 2023

SummaryRetroelements are the widespread jumping elements considered as major drivers for genome evolution, which can also be repurposed as gene-editing tools. Here, we determined the cryo-EM structures of eukaryotic R2 retrotransposon with ribosomal DNA target and regulatory RNAs. Combined with biochemical and sequencing analysis, we revealed two essential DNA regions, Drr and Dcr, required for R2 recognition and cleavage. The association of 3’ regulatory RNA with R2 protein accelerates the first-strand cleavage, blocks the second-strand cleavage, and initiates the reverse transcription starting from the polyA tail. Removing 3’ regulatory RNA by reverse transcription allows the association of 5’ regulatory RNA and initiates the second-strand cleavage. Our work explained the DNA recognition and supervised sequential retrotransposition mechanisms by R2 machinery, providing novel insights into the retrotransposon and application reprogramming.
scSPARKL: Apache Spark based parallel analytical framework for the downstream analysis of scRNA-seq data
Authors: Adil Asif , Bhattacharya Namrata , Asger Mohammed 
Published: April 2023

AbstractAs the field of single-cell genomics continues to develop, the generation of large-scale scRNA-seq datasets has become more prevalent. While these datasets offer tremendous potential for shedding light on the complex biology of individual cells, the sheer volume of data presents significant challenges for management and analysis. To address these challenges, a new discipline, known as “big single-cell data science,” has emerged. Within this field, a variety of computational tools have been developed to facilitate the processing and interpretation of scRNA-seq data. In this paper, we present a novel parallel analytical framework, scSPARKL, that leverages the power of Apache Spark to enable the efficient analysis of single-cell transcriptomic data. Our methodology incorporates six key operations for dealing with single-cell Big Data, including data reshaping, data preprocessing, cell/gene filtering, data normalization, dimensionality reduction, and clustering. By utilizing Spark’s unlimited scalability, fault tolerance, and parallelism, scSPARKL enables researchers to rapidly and accurately analyze scRNA-seq datasets of any size. We demonstrate the utility of our framework through a series of experiments on simulated and real-world scRNA-seq data. Overall, our results suggest that scSPARKL represents a powerful and flexible tool for the analysis of single-cell transcriptomic data, with broad applications across the fields of biology and medicine.
The BTB-ZF geneBm-mamoregulates pigmentation in silkworm caterpillars
Authors: Wu Songyuan , Tong Xiaoling , Peng Chenxing , Luo Jiangwen , Zhang Chenghao , Lu Kunpeng , Li Chunlin , Ding Xin , Duan Xiaohui , Lu Yaru , Hu Hai , Tan Duan , Dai Fangyin 
Published: April 2023

AbstractThe color pattern of insects is one of the most diverse adaptive evolutionary phenotypes. However, the molecular regulation of this color pattern is not fully understood. In this study, we found that the transcription factor Bm-mamo is responsible forblack dilute(bd) allele mutations in the silkworm. Bm-mamo belongs to the BTB zinc finger family and is orthologous to mamo inDrosophila melanogaster. This gene has a conserved function in gamete production inDrosophilaand silkworms and has evolved a pleiotropic function in the regulation of color patterns in caterpillars. Using RNAi and clustered regularly interspaced short palindromic repeats (CRISPR) technology, we showed that Bm-mamo is a repressor or has dark melanin patterns in the larval epidermis. Using in vitro binding assays and gene expression profiling in wild-type and mutant larvae, we also showed thatBm-mamolikely regulates the expression of related pigment synthesis and cuticular protein genes in a coordinated manner to mediate its role in color pattern formation. This mechanism is consistent with the dual role of this transcription factor in regulating both the structure and shape of the cuticle and the pigments that are embedded within it. This study provides new insight into the regulation of color patterns as well as into the construction of more complex epidermis features in some insects.
Extensive genetic variation of leaf specialized metabolites in sessile oak (Quercus petraea) populations
Authors: Coq--Etchegaray Domitille , Bernillon Stéphane , Le-Provost Grégoire , Kremer Antoine , Ducousso Alexis , Lalanne Céline , Bonne Fabrice , Moing Annick , Plomion Christophe , Brachi Benjamin 
Published: April 2023

AbstractSpecialized or secondary metabolites play a key role in plant resistance against abiotic stresses and defences against bioaggressors. For example, in sessile oaksQuercus petraea, phenolics contribute to reduce herbivore damage and improve drought resistance. Here, we explored the natural variation of specialized metabolites in nine European provenances of sessile oaks and aimed to detect its underlying genetic bases. We sampled mature leaves from high and low branches on 225 sessile oak trees located in a common garden and used untargeted metabolomics to characterise the variation of 217 specialized metabolites. In addition, we used whole genome low-depth sequencing to genotype individuals for 1.4M genetic markers. We found that leaf specialized metabolites displayed extensive within-provenance variation, but very little differentiation between provenances. In addition, a genome-wide association study allowed detecting significant associations for 42% of these metabolites. Hence, our results suggest that genetic variation for most leaf specialized metabolites is unlikely to be locally adaptive, however lack of differentiation among populations suggests selection acts locally to maintain diversity at loci associated with leaf specialized metabolites variation.
The origin of a mountain biota: hyper-aridity shaped reptile diversity in an Arabian biodiversity hotspot
Authors: Burriel-Carranza Bernat , Tejero-Cicuéndez Héctor , Carné Albert , Riaño Gabriel , Talavera Adrián , Saadi Saleh Al , Els Johannes , Šmíd Jiří , Tamar Karin , Tarroso Pedro , Carranza Salvador 
Published: April 2023

AbstractAdvances in genomics have greatly enhanced our understanding of mountain biodiversity, providing new insights into the complex and dynamic mechanisms that drive the formation of mountain biotas. These include from broad biogeographic patterns, to population dynamics and adaptations to these environments. However, significant challenges remain in integrating these large-scale and fine-scale findings to develop a comprehensive understanding of mountain biodiversity. One significant challenge is the lack of genomic data, particularly in historically understudied arid regions where reptiles are a particularly diverse vertebrate group. We generatedde novogenome-wide SNP data for more than 600 specimens and integrated state-of-the-art biogeographic analyses at the community, species and population level. We, thus, provide for the first time, a holistic integration of how a whole endemic reptile community has originated, diversified and dispersed through a mountain range. Our results show that reptiles independently colonized the Hajar Mountains of eastern Arabia 11 times. After colonization, species delimitation methods suggest high levels of within-mountain diversification, supporting up to 49 putative species. This diversity is strongly structured following local topography, with the highest peaks acting as a broad barrier to gene flow among the entire community. Surprisingly, orogenic events do not seem to rise as key drivers of the biogeographic history of reptiles in this system. However, paleoclimate seems to have had a major role in this community assemblage. We observe an increase of vicariant events from Late Pliocene onwards, coinciding with an unstable climatic period of rapid shifts between hyper-arid to semiarid conditions that led to the ongoing desertification of Arabia. We conclude that paleoclimate, and particularly extreme aridification, acted as a main driver of diversification in arid mountain systems which is tangled with the generation of highly adapted endemicity. Our study provides a valuable contribution to understanding the evolution of mountain biodiversity and the role of environmental factors in shaping the distribution and diversity of reptiles in arid regions.
Reversal learning of visual cues in Heliconiini butterflies
Authors: Young Fletcher J. , Melo-Flórez Lina , McMillan W. Owen , Montgomery Stephen H. 
Published: April 2023

AbstractThe mushroom bodies, an integrative region of the insect brain involved in learning and memory, have undergone volumetric increase in several independent lineages includes bees and ants, cockroaches and some beetles. However, the selective pressures driving these expansion events are not fully understood. One promising system for investigating this question is the Neotropical butterfly genusHeliconius, which exhibits markedly enlarged mushroom bodies compared with other members of the Heliconiini tribe. Notably, this neural elaboration co-occurs with the evolution of trapline foraging behaviour and an improved capacity for learning complex visual cues and long-term memory. Here, we further investigate the behavioural consequences of this brain expansion by testing reversal learning ability, a commonly used measure of cognition and behavioural flexibility in both vertebrates and invertebrates, across threeHeliconiusand three closely-related Heliconiini species. We trained butterflies to associate a food reward with either purple or yellow flowers, before training them with the reversed associations, and then reversing the cues again. All six successfully learned the reversed cues, and, contrary to our expectations, we found no evidence thatHeliconiusperformed better than the other Heliconiini species. These results are surprising, given previous evidence linking the mushroom bodies to reversal learning in other insects, and the enhanced performance ofHeliconiusin other cognitive tests. This serves as a reminder that the functional consequences of brain expansion can be multifaceted, and do not necessarily result in an overall increase in general cognitive ability, but rather enhanced performance in specific, ecologically-relevant tasks.
Gut barrier defects, increased intestinal innate immune response, and enhanced lipid catabolism drive lethality inN-glycanase 1 deficientDrosophila
Authors: Pandey Ashutosh , Galeone Antonio , Han Seung Yeop , Story Benjamin A , Consonni Gaia , Mueller William F , Steinmetz Lars M , Vaccari Thomas , Jafar-Nejad Hamed 
Published: April 2023

AbstractIntestinal barrier dysfunction leads to inflammation and associated metabolic changes. However, the relative impact of infectious versus non-infectious mechanisms on animal health in the context of barrier dysfunction is not well understood. Here, we establish that loss ofDrosophila N-glycanase 1 (Pngl) leads to gut barrier defects, which cause starvation and increased JNK activity. These defects result in Foxo overactivation, which induces a hyperactive innate immune response and lipid catabolism, thereby contributing to lethality associated with loss ofPngl. Notably, germ-free rearing ofPnglmutants did not rescue lethality. In contrast, raisingPnglmutants on isocaloric, fat-rich diets improved animal survival in a dosage-dependent manner. Our data indicate that Pngl functions inDrosophilalarvae to establish the gut barrier, and that the immune and metabolic consequences of loss ofPnglare primarily mediated through non-infectious mechanisms.
Repurposing the Memory-promoting Meclofenoxate Hydrochloride as a Treatment for Parkinson‘s Disease through Integrative Multi-omics analysis
Authors: Zhang Huasong , Fan Cong , Li Ling , Liu Feiyi , Li Shaoying , Ma Linyun , Yang Yuanhao , Cooper David N. , Yang Yuedong , Hu Ronggui , Zhao Huiying 
Published: April 2023

AbstractParkinson‘s disease (PD) is a devastating neurodegenerative disorder with growing prevalence worldwide and, as yet, no effective treatment. Drug repurposing promises to be invaluable for the identification of novel therapeutics for the treatment of PD due to the associated shortened drug development time, fewer safety concerns, and reduced costs. Here, we compiled gene expression data from 1,231 healthy human brains and 357 PD patients across ethnicities, brain regions, Braak stages, and disease status. By integrating them with multiple-source PD-associated genomic data, we found a conserved PD-associated gene co-expression module, and its alignment with the CMAP database successfully identified 15 drug candidates. Among these, we selected meclofenoxate hydrochloride (MH) and sodium phenylbutyrate (SP) for experimental validation because they are capable of passing through the blood brain barrier. In primary neurons, MH was found to prevent the neuronal death and synaptic damage associated with PD and to reverse the abnormal mitochondrial metabolism caused by PD. In hippocampal tissues, MH and SP were found to prevent the destruction of mitochondria, to reduce lipid peroxidation and to protect dopamine synthesis by PET-CT examination, malondialdehyde (MAD) testing and glutathione (GSH) testing, and immunohistochemical tests. Finally, MH was found to have the ability to improve gait behavior, and reduce anhedonic and depressive-like behaviors that are characteristics of PD mice. Taken together, our findings support the contention that MH may have the potential to ameliorate PD by improving mitochondrial metabolism and brain function.
Predictive power of non-identifiable models
Authors: Grabowski Frederic , Nałęcz-Jawecki Paweł , Lipniacki Tomasz 
Published: April 2023

AbstractResolving practical nonidentifiability of computational models typically requires either additional data or non-algorithmic model reduction, which frequently results in models containing parameters lacking direct interpretation. Here, instead of reducing models, we explore an alternative, Bayesian approach, and quantify predictive power of non-identifiable models. Considering an example biochemical signalling cascade model as well as its mechanical analog, we demonstrate that by measuring a single variable in response to a properly chosen stimulation protocol, the dimensionality of the parameter space is reduced, which allows for prediction of its trajectory in response to different stimulation protocols even if all model parameters remain unidentified. Successive measurements of remaining variables further constrain model parameters and enable more predictions. We analyse potential pitfalls of the proposed approach that can arise when the investigated model is oversimplified, incorrect, or when the training protocol is inadequate. The main advantage of the suggested iterative approach is that the predictive power of the model can be assessed and practically utilised at each step.