bluuebunny/crossref_metadata_2025_split huggingface dataset:
The protein structurome ofOrthornaviraeand its dark matter
Authors: Mutz Pascal , Camargo Antonio Pedro , Sahakyan Harutyun , Neri Uri , Butkovic Anamarija , Wolf Yuri I. , Krupovic Mart , Dolja Valerian V. , Koonin Eugene V. 
Published: September 2024

ABSTRACTMetatranscriptomics is uncovering more and more diverse families of viruses with RNA genomes comprising the viral kingdomOrthornaviraein the realmRiboviria. Thorough protein annotation and comparison are essential to get insights into the functions of viral proteins and virus evolution. In addition to sequence- and hmm profile-based methods, protein structure comparison adds a powerful tool to uncover protein functions and relationships. We constructed anOrthornavirae‘structurome’ consisting of already annotated as well as unannotated (‘dark matter’) proteins and domains encoded in viral genomes. We used protein structure modeling and similarity searches to illuminate the remaining dark matter in hundreds of thousands of orthornavirus genomes. The vast majority of the dark matter domains showed either ‘generic’ folds, such as single α-helices, or no high confidence structure predictions. Nevertheless, a variety of lineage-specific globular domains that were new either to orthornaviruses in general or to particular virus families were identified within the proteomic dark matter of orthornaviruses, including several predicted nucleic acid-binding domains and nucleases. In addition, we identified a case of exaptation of a cellular nucleoside monophosphate kinase as an RNA-binding protein in several virus families. Notwithstanding the continuing discovery of numerous orthornaviruses, it appears that all the protein domains conserved in large groups of viruses have already been identified. The rest of the viral proteome seems to be dominated by poorly structured domains including intrinsically disordered ones that likely mediate specific virus-host interactions.IMPORTANCEAdvanced methods for protein structure prediction, such as AlphaFold2, greatly expand our capability to identify protein domains and infer their likely functions and evolutionary relationships. This is particularly pertinent for proteins encoded by viruses that are known evolve rapidly and as a result often cannot be adequately characterized by analysis of the protein sequences. We performed an exhaustive structure prediction and comparative analysis for uncharacterized proteins and domains (‘dark matter’) encoded by viruses with RNA genomes. The results show the dark matter of RNA virus proteome consists mostly of disordered and all α-helical domains that cannot be readily assigned a specific function and that likely mediate various interactions between viral proteins and between viral and host proteins. The great majority of globular proteins and domains of RNA viruses are already known although we identified several unexpected domains represented in individual viral families.
Museomics analyses inform aboutChannichthysicefish species diversity
Authors: Garmann-Aarhus Benedicte , Nikolaeva Ekaterina , Desvignes Thomas , Straube Nicolas , Matschiner Michael 
Published: September 2024

AbstractThe rapid diversification of notothenioid fishes in the waters surrounding the Antarctic continent is a prime example of the process of adaptive radiation. Within around 10 million years, Antarctic notothenioids have diversified into over 100 species with a broad range of lifestyles and ecological adaptations. However, the exact number of species within this radiation has long been unclear. Particularly challenging is the taxonomy of the genusChannichthys, for which between one and nine species have been recognized by different authors. The putative species from this genus are known from a limited number of representative specimens, of which most were sampled decades ago. Here, we investigated the mitochondrial genomes of museum specimens representing the four recently recognized species Unicorn Icefish (C. rhinoceratus), Red Icefish (C. rugosus), Sailfish Pike (C. velifer), and Charcoal Icefish (C. panticapaei), complemented by morphological analyses. All analyzed specimens were collected in the 1960s and 1970s and fixed in formaldehyde, and their DNA has thus been heavily degraded. Applying ancient-DNA protocols for DNA extraction and single-stranded library preparation, we were nevertheless able to obtain sufficient endogenous DNA to reconstruct the mitochondrial genomes of one specimen of each species. These mitochondrial genome sequences were nearly identical for the three specimens assigned to Unicorn Icefish, Red Icefish, and Sailfish Pike, while greater mitochondrial divergence was observed for the Charcoal Icefish specimens. We discuss possible explanations of the contrast between these molecular results and the recognizable morphological variation found among the four species, and recommend that at least the Charcoal Icefish be included the list of valid icefish and notothenioid species.
Ecological dynamics explain modular denitrification in the ocean
Authors: Sun Xin , Buchanan Pearse , Zhang Irene H. , Roman Magdalena San , Babbin Andrew R. , Zakem Emily 
Published: September 2024

AbstractMicroorganisms in marine oxygen minimum zones (OMZs) drive globally impactful biogeochemical processes. One such process is the multi-step denitrification, the dominant pathway for bioavailable nitrogen (N) loss and nitrous oxide (N2O) production. Denitrification-derived N loss is typically measured and modeled as a single step, but observations reveal that most denitrifiers in OMZs contain only subsets (“modules”) of the complete pathway. Here, we identify the ecological mechanisms sustaining diverse denitrifiers, explain the observed prevalence of certain modules, and examine the implications for N loss. We describe microbial functional types carrying out diverse denitrification modules by their underlying redox chemistry, constraining their traits with thermodynamics and pathway length penalties, in an idealized OMZ ecosystem model. Biomass yields of single-step modules increase along the denitrification pathway when growth is limited by organic matter (OM), explaining the viability of populations respiring nitrite and N2O in a nitrate-filled ocean. Results predict denitrifier community succession along environmental gradients: shorter versus longer modules are favored when OM versus N limits growth, respectively, suggesting a niche for the NO3−⟶NO2−module in free-living communities and for the complete pathway in organic particles, consistent with observations. The model captures and mechanistically explains the observed dominance and higher oxygen tolerance of the NO3−⟶NO2−module. Results also capture observations that nitrate is the dominant source of N2O. These results advance the mechanistic understanding of the relationship between microbial ecology and N loss, which is essential for accurately predicting the ocean’s future.
Impact of Interval Censoring on Data Accuracy and Machine Learning Performance in Biological High-Throughput Screening
Authors: Doffini Vanni , Nash Michael A. 
Published: September 2024

AbstractHigh-throughput screening (HTS) combined with deep mutational scanning (DMS) and next-generation DNA sequencing (NGS) have great potential to accelerate discovery and optimization of biological therapeutics. Typical workflows involve generation of a mutagenized variant library, screening/selection of variants based on phenotypic fitness, and comprehensive analysis of binned variant populations by NGS. However, in such cases, the HTS data are subject to interval censoring, where each fitness value is calculated based on the assignment of variants to bins. Such censoring leads to increased uncertainty, which can impact data accuracy and, consequently, the performance of machine learning (ML) algorithms tasked with predicting sequence-fitness pairings. Here, we investigated the impact of interval censoring on data quality and ML performance in biological HTS experiments. We theoretically analyzed the impact of data censoring and propose a dimensionless number, theRatio of Discretization(RD), to assist in optimizing HTS parameters such as the bin width and the sampling size. This approach can be used to minimize errors in fitness prediction by ML and to improve the reliability of these methods. These findings are not limited to biological HTS techniques and can be applied to other systems where interval censoring is an advantageous measurement strategy.
Natural Language Processing Algorithms Outperform ICD Codes in the Development of Fall Injuries Registry
Authors: Taseh Atta , Sasanfar Souri , Chan Jia-Zhen M. , Sirls Evan , Nazarian Ara , Batmanghelich Kayhan , Bean Jonathan F. , Ashkani-Esfahani Soheil 
Published: September 2024

AbstractBackgroundStandardized registries are commonly built using administrative codes assigned to patient encounters, such as the International Classification of Diseases (ICD) codes. However, fall patients are often coded using subsequent injury codes, such as hip fractures. This necessitates manual screening to ensure the accuracy of data registries. Herein, we aimed to automate the extraction of fall incidents and mechanisms using Natural Language Processing (NLP) and compare this approach with the ICD method.MethodsClinical notes for patients with fall-induced hip fractures were retrospectively reviewed by medical experts. Fall incidences were detected, annotated, and classified among patients who had fall-induced hip fracture (case group). The control group included patients with hip fracture without any evidence of fall. NLP models were developed using the annotated notes of the study groups to fulfill two separate tasks: fall occurrence detection and fall mechanism classification. The performances of the models were compared using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and area under the ROC curve (AUC-ROC).ResultsA total of 1,769 clinical notes were included in the final analysis for the fall occurrence task, and 783 clinical notes were analyzed for the fall mechanism classification task. The highest F1 score using NLP for fall occurrence was 0.97 (specificity=0.96; sensitivity=0.97) and for fall mechanism classification was 0.61 (specificity=0.56; sensitivity=0.62). NLP could detect up to 98% of the fall occurrences and 65% of the fall mechanisms accurately compared to 26% and 12%, respectively, by ICD codes.ConclusionOur findings showed promising performance with a higher accuracy of NLP algorithms compared to the conventional method for detecting fall occurrence and mechanism in developing disease registries using clinical notes. Our approach can be introduced to other registries that are based on large data and are in need for accurate annotation and classification.
Transcriptome and evolutionary analysis ofPseudotrichomonas keilini, a free-living anaerobic eukaryote
Authors: Abu-Elmakarem Hend , Taerum Stephen J. , Petitjean Celine , Kotyk Michael , Kay Christopher , Čepička Ivan , Bass David , Gile Gillian H. , Williams Tom A. 
Published: September 2024

ABSTRACTThe early evolution of eukaryotes and their adaptations to low-oxygen environments are fascinating open questions in biology. Genome-scale data from novel eukaryotes, and particularly from free-living lineages, are key to answering these questions. The Parabasalia are an ancient lineage of anaerobes, and the most speciose lineage of Metamonada, a major lineage of eukaryotes. The most well-studied metamonads are parasitic parabasalids includingTrichomonas vaginalis, Tritrichomonas foetus, andGiardia intestinalis, but very little genome-scale data is available for free-living members of the group. Here, we sequenced the transcriptome ofPseudotrichomonas keilini, a free-living parabasalian. Comparative genomic analysis indicated thatP. keilinipossesses a metabolism and gene complement that are in many respects similar to its parasitic relativeTrichomonas vaginalis, and that in the time since their most recent common ancestor, it is theTrichomonas vaginalislineage that has experienced more genomic change, likely due to the transition to a parasitic lifestyle. Features shared betweenP. keiliniandTrichomonas vaginalisinclude a hydrogenosome (anaerobic mitochondrial homologue) that we predict to function much as inTrichomonas vaginalis, and a complete glycolytic pathway that is likely to represent one of the primary means by whichP. keiliniobtains ATP. Phylogenomic analysis indicates thatP. keilinibranches within a clade of endobiotic parabasalids, consistent with the hypothesis that different parabasalid lineages evolved towards parasitic or free-living lifestyles from an endobiotic, anaerobic or microaerophilic common ancestor.
Diverse defense systems synergistically drive the microbe-virus arms race in deep sea cold seeps
Authors: Han Yingchun , Liao Jing , Li Chengpeng , Xing Fengmin , Peng Jiaxue , Liu Xinyue , Xie Wentao , Wu Fabai , Jian Huahua , Cheng Rui , Dong Xiyang 
Published: September 2024

AbstractCold seeps are unique deep-sea ecosystems that host diverse uncharacterized microbes and viruses, many of which potentially possess novel defense and counter-defense systems. Despite their ecological significance, the diversity of microbial defense systems, their interactions, and the evolutionary arms race with viral anti-defense strategies in cold seeps remain largely unexplored. To address this, we analyzed 3,813 microbial and 13,336 viral genomes from 193 metagenomic samples collected across 17 cold seep sites. Cold seep microbes harbor an extensive repertoire of ‘defense systems (n = 26,389), with 63% representing novel systems. Laboratory experiments confirm that several of these novel systems effectively protect against viral infections. These defense systems frequently co-occur and interact synergistically to combat viral infections. They are widely distributed across different sediment depths and geographical locations, exhibiting active expression. In response, cold seep viruses have evolved a diverse array of anti-defense genes (n = 1,197), employing complex strategies to counteract host defenses. The concurrent presence of multiple viral anti-defense genes and various microbial defense genes in their hosts highlights the intricate and dynamic interactions between viruses and their microbial counterparts. Functionally critical lineages, such as anaerobic methanotrophic archaea (ANME), sulfate-reducing bacteria (SRB), and diazotrophs, adapt their defensive strategies according to ecological niches and environmental pressures. Notably, SRB strains were found to harbor multiple Gabija defense systems, enhancing their resistance to viral attacks, while corresponding viruses carry anti-Gabija genes, illustrating a specific evolutionary adaptation. Overall, these findings underscore the critical role of virus-microbe interactions in shaping microbial metabolic functions and environmental adaptation in extreme deep-sea subseafloor environments.
The neural time course of size constancy in natural scenes
Authors: Yeh Lu-Chun , Gayet Surya , Kaiser Daniel , Peelen Marius V. 
Published: September 2024

AbstractAccurate real-world size perception relies on size constancy, a mechanism that integrates an object’s retinal size with distance information. The neural time course of extracting pictorial distance cues from scenes and integrating them with retinal size information - a process referred to as scene-based size constancy - remains unknown. In two experiments, participants viewed objects with either large or small retinal sizes, presented at near or far distances in outdoor scene photographs, while performing an unrelated one-back task. We applied multivariate pattern analysis (MVPA) to time-resolved EEG data to decode the retinal size of large versus small objects, depending on their distance (near versus far) in the scenes. The objects were either perceptually similar in size (large-near versus small-far) or perceptually dissimilar in size (large-far versus small-near), reflecting size constancy. We found that the retinal size of objects could be decoded from 80 ms after scene onset onwards. Distance information modulated size decoding at least 120 ms later: from 200 ms after scene onset when objects were fixated, and from 280 ms when objects were viewed in the periphery. These findings reveal the neural time course of size constancy based on pictorial distance cues in natural scenes.
Differential Kinetics of SARS-CoV-2 Proteases Revealed by a Dual-Color, BRET-based Protease Biosensor, DuProSense
Authors: Fatima Asma , Geethakumari Anupriya M , Uddin S M Nasir , Biswas Kabir H 
Published: September 2024

SummaryWhile SARS-CoV-2 Mproand PLproproteases are known to cleave polyproteins pp1a and pp1ab at multiple sites, these have not been comprehensively characterized in living cells. Here we engineered a two-color Bioluminescence Resonance Energy Transfer (BRET)-based, dual protease (DuProSense) biosensor platform relying on a proximity-dependent energy transfer from a luciferase donor to two spectrally separated fluorescent protein acceptors enabling simultaneous monitoring of processing of two cleavage sites in a single assay with high specificity. DuProSense revealed a similar Mproand PLprocleavage kinetics for their N-terminal autocleavage sites. Importantly, systematic characterization of various Mproand PLprocleavage sites using DuProSense revealed significant differences in cleavage rates and nirmatrelvir potency of Mprocleavage sites but no correlation between the cleavage rates and nirmatrelvir IC50values. Overall, our results provide deeper insights into the proteolytic processing of SARS-CoV-2 polyproteins and the dual color BRET platform will find wider applications in the future.HighlightsEngineered a two-color BRET-based, dual protease biosensor (DuProSense)DuProSense biosensor enabled simultaneous and specific monitoring of Mproand PLproactivitiesDuProSense platform revealed differential cleavage kinetics of Mprocleavage sites in live cellsDuProSense platform revealed Mprocleavage site-dependent nirmatrelvir potency in live cells
Evolutionary trends in the emergence of skeletal cell types
Authors: Damatac Amor , Koska Sara , Ullrich Kristian K , Domazet-Lošo Tomislav , Klimovich Alexander , Kaucká Markéta 
Published: September 2024

AbstractThe emergence of novel cell types fuels evolutionary innovations and contributes to the diversity of life forms and their morphological and functional traits. Cell types are fundamental functional units of multicellular organisms defined by their specific gene expression programs. The evolution of these transcriptional programs is driven by genetic changes, such as gene co-option and cis- regulatory evolution, known to facilitate the assembly or rewiring of molecular networks and give rise to new cell types with specialized functions. However, the role of novel genes in this complex evolutionary process is underexplored. Here, we examine the trends in skeletal cell type evolution with a focus on lineage-specific genes. We find that immature chondrocytes express the oldest transcriptome and resemble ancestral skeletogenic cell type, supporting the existence of a conserved genetic program for cartilage development in bilaterians. The subsequent acquisition of lineage-restricted genes led to the individuation of the ancient gene expression program and powered the emergence of osteoblasts and hypertrophic chondrocytes. We found a significant enrichment of Vertebrate-specific genes in osteoblasts and Gnathostome-specific genes in hypertrophic chondrocytes. By identifying the functional properties of the recruited genes, coupled with the recently discovered fossil evidence, our findings challenge the long-standing view on the evolution of vertebrate skeletal structures and suggest that endochondral ossification and chondrocyte hypertrophy evolved already in the last common ancestors of gnathostomes. Finally, our findings highlight the critical role of novel genes in shaping cellular diversity.
Unipept in 2024: Expanding Metaproteomics Analysis with Support for Missed Cleavages, Semi-Tryptic and Non-Tryptic Peptides
Authors: Vande Moortele Tibo , Devlaminck Bram , Van de Vyver Simon , Van Den Bossche Tim , Martens Lennart , Dawyndt Peter , Mesuere Bart , Verschaffelt Pieter 
Published: September 2024

AbstractUnipept, a pioneering software tool in metaproteomics, has significantly advanced the analysis of complex ecosystems by facilitating both taxonomic and functional insights from environmental samples. From the onset, Unipept’s capabilities focused on tryptic peptides, utilizing the predictability and consistency of trypsin digestion to efficiently construct a protein reference database. However, the evolving landscape of proteomics and emerging fields like immunopeptidomics necessitate a more versatile approach that extends beyond the analysis of tryptic peptides. In this article, we present a significant update to the underlying index structure of Unipept, which is now powered by a Sparse Suffix Array index. This advancement enables the analysis of semi-tryptic peptides, peptides with missed cleavages, and non-tryptic peptides such as those encountered in other research fields such as immunopeptidomics (e.g. MHC- and HLA-peptides). This new index benefits all tools in the Unipept ecosystem such as the web application, desktop tool, API and command line interface. A benchmark study highlights significantly improved performance in handling missed cleavages, preserving the same level of accuracy.For TOC Only
A complex between IF2 and NusA links transcription and translation
Authors: Metelev Mikhail , Johansson Magnus 
Published: September 2024

ABSTRACTThe main function of translation initiation factors is to assist ribosomes in selecting the correct reading frame on an mRNA. This process has been extensively studied with the help of reconstituted in vitro systems, but the dynamics in living cells have not been characterized. In this study, we performed single-molecule tracking of the bacterial initiation factors IF2, IF3, as well as the initiator fMet-tRNAfMetdirectly in growingEscherichia colicells. Our results reveal the kinetics of factor association with the ribosome and, among other things, highlight the respective antagonistic roles of IF2 and IF3 in the process. Importantly, our comparisons of in vivo binding kinetics of the two naturally occurring isoforms of IF2 reveal that the longer IF2α isoform directly interacts with the transcriptional factor NusA, a finding further corroborated by pull-down and cross-linking experiments. We further show that cells with compromised binding between IF2α and NusA display slow adaptation to new growth conditions. Taken together, these results suggest a novel coupling mechanism between transcription and translation initiation, important for the rewiring of the transcriptome during a shift of growth media.