bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing Metabolomics to Identify Potential Biomarkers and Perturbed Metabolic Pathways in Osteoarthritis: A Systematic Review
Authors: Pevenage Peyton Van , Birchmier Jaedyn T. , June Ronald K. 
Published: September 2022

AbstractPurposeOsteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and radiographic evidence of joint space narrowing. Currently, there are no laboratory findings that are specific to a diagnosis of OA. The purpose of this systematic review is to evaluate the state of current studies of metabolomic biomarkers that can aid in the diagnosis and treatment of OA.MethodsArticles were gathered from PubMed and Web of Science using the search terms “osteoarthritis” and “biomarkers” and “metabolomics”. Last search of databases took place July 20th, 2021. Duplicates were manually screened, along with any other results that were not original journal articles. Only original reports involving populations with diagnosed primary or secondary OA (human participants) or surgically induced OA (animal participants) and a healthy control group for comparison were considered for inclusion. Metabolites and metabolic pathways reported in included articles were then manually extracted and evaluated for significance based on reported a priori p-values and/or area under the receiver-operator curve (AUC).ResultsOf the 129 results that were returned in the database searches, 36 unique articles met the inclusion criteria. Articles were categorized based on body fluid analyzed: 6 studies on urine samples, 12 studies on plasma samples, 9 studies on synovial fluid (SF) samples, 8 studies on serum samples, and 1 study that involved both plasma and synovial fluid. To synthesize results, individual metabolites, as well as metabolic pathways that involve frequently reported metabolites, are presented for each study. Indications as to whether metabolite levels were increased or decreased are also included if this data was included in the original articles.ConclusionsThese studies clearly show that there are a wide range of metabolic pathways perturbed in OA. For this period, there was no consensus on a single metabolite, or panel of metabolites, that would be clinically useful in early diagnosis of OA or distinguishing OA from a healthy control. However, many common metabolic pathways were identified in the studies, including TCA cycle, fatty acid metabolism, amino acid metabolism (notably BCAA metabolism and tryptophan metabolism via kynurenine pathway), nucleotide metabolism, urea cycle, cartilage metabolism, and phospholipid metabolism. Future research is needed to define effective clinical biomarkers of osteoarthritis from metabolomic and other data.
Increasing Cases of SARS-CoV-2 Omicron Reinfection Reveals Ineffective Post-COVID-19 Immunity in Denmark and Conveys the Need for Continued Next-Generation Sequencing
Authors: Burkholz Scott , Rubsamen Michael , Blankenberg Luke , Carback Richard T. , Mochly-Rosen Daria , Harris Paul E. 
Published: September 2022

AbstractSARS-CoV-2 has extensively mutated creating variants of concern (VOC) resulting in global infection surges. The Omicron VOC reinfects individuals exposed to earlier variants of SARS-CoV-2 at a higher frequency than previously seen for non-Omicron VOC. An analysis of the sub-lineages associated with an Omicron primary infection and Omicron reinfection reveals that the incidence of Omicron-Omicron reinfections is occurring over a shorter time interval than seen after a primary infection with a non-Omicron VOC. Our analysis suggests that a single infection from SARS-CoV-2 may not generate the protective immunity required to defend against reinfections from emerging Omicron lineages. This analysis was made possible by Next-generation sequencing (NGS), specifically of a Danish cohort with clinical metadata on both infections occurring in the same individual. We suggest that the continuation of COVID-19 NGS and inclusion of clinical metadata is necessary to ensure effective surveillance of SARS-CoV-2 genomics, assist in treatment and vaccine development, and guide public health recommendations.
The persistent homology of mitochondrial ATP synthases
Authors: Sinha Savar D. , Wideman Jeremy G. 
Published: September 2022

AbstractWhile mitochondrial ATP synthase has been thoroughly studied in animals and fungi, relatively little is known about the structures of protists. Among those that have been studied, protist ATP synthases possess divergent structures distinct from those of yeast or animals. Therefore, we aimed to clarify the subunit composition and evolution of ATP synthase across all major eukaryotic lineages. We used sensitive homology detection methods and molecular modelling tools to demonstrate the persistence of a near-complete ancestral set of 17 subunits in most major eukaryotic taxa even despite major divergence. These data demonstrate that most eukaryotes possess an ancestral-like ATP synthase structure similar to those of animals, fungi, and plants, but a number have diverged drastically (e.g., ciliates, myzozoans, euglenozoans, and likely retarians and heteroloboseans). In addition, we identified the first synapomorphy of the SAR (stramenopile, alveolate, rhizaria) supergroup – a ~1 billion-year-old gene fusion between ATP synthase stator subunits. Our comparative approach highlights the persistence of ancestral subunits even amidst major structural changes. We conclude by urging that more ATP synthase structures (e.g., from jakobids, heteroloboseans, stramenopiles, rhizarians) are needed to provide a complete picture of the evolution of structural diversity of this ancient and essential complex.
Association of Whole-Person Eigen-Polygenic Risk Scores with Alzheimer’s Disease
Authors: Kharaghani Amin , Tio Earvin , Milic Milos , Bennett David A. , De Jager Philip L. , Schneider Julie A. , Sun Lei , Felsky Daniel 
Published: September 2022

AbstractLate-Onset Alzheimer’s Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the “whole person” genetic risk landscape of polygenic risk scores for 2,218 traits in 2,044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Principal component analyses of thousands of PRSs found generally poor global correlation among traits. However, component loadings confirmed covariance of clinically and biologically related traits and diagnoses, with the top PCs representing autoimmune traits, cardiovascular traits, and general pain medication prescriptions, depending on the PRS variant inclusion threshold. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) derived from these clusters were significantly associated with LOAD-related phenotypes and improved predictive model performance over the state-of-the-art LOAD PRS alone. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of brain-wide beta-amyloid burden by 1.7% (likelihood ratio test p=9.02×10−7). While many associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci, some modules (e.g. retinal defects, acidosis, colon health, ischaemic heart disease) showed associations at an unadjusted type I error rate. Our approach reveals new relationships between genetic risk for vascular, inflammatory, and other age-related traits and offers improvements over the existing single-trait PRS approach to capturing heritable risk for cognitive decline and beta-amyloid accumulation. Our results are catalogued for the scientific community, to aid in the generation of new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.
Diacammaants adjust liquid foraging strategies in response to biophysical constraints
Authors: Fujioka Haruna , Marchand Manon , LeBoeuf Adria C. 
Published: September 2022

AbstractAnt foragers need to provide food to the rest of the colony, which often requires transport over long distances. Foraging for liquid is especially challenging because it is difficult to transport and share. Many social insects store liquid food inside the crop to transport it to the nest, and then regurgitate this fluid to distribute it to nestmates through a behaviour called trophallaxis. Some ants instead transport fluids with a riskier behaviour called pseudotrophallaxis – holding a drop of liquid between the mandibles through surface tension. Ants can then share this droplet with nestmates without ingestion or regurgitation. Here, we hypothesised that ants optimise their liquid-collection approach depending on viscosity. Working with a ponerine ant that uses both trophallaxis and pseudotrophallaxis, we investigated why each liquid-collection behaviour might be favoured under different conditions by measuring biophysical properties, collection time, and reaction to food quality for typical and viscosity-altered sucrose solutions. We found that ants can collect more liquid food per unit time by mandibular grabbing than by drinking. At high viscosities, which in nature correspond to high sugar concentrations, ants switched their liquid collection method to mandibular grabbing in response to viscosity, and not to sweetness. Our results demonstrate that ants change their transport and sharing methods according to viscosity – a proxy for sugar concentration in nature – increasing the mass of sugar returned to the nest per trip.
Identification of interpretable clusters and associated signatures in breast cancer single cell data: a topic modeling approach
Authors: Gabriele Malagoli , Filippo Valle , Emmanuel Barillot , Michele Caselle , Loredana Martignetti 
Published: September 2022

ABSTRACTTopic modeling is a popular technique in machine learning and natural language processing, where a corpus of text documents is classified into themes or topics using word frequency analysis. This approach has proven successful in various biological data analysis applications, such as predicting cancer subtypes with high accuracy and identifying genes, enhancers, and stable cell types simultaneously from sparse single cell epigenomics data. The advantage of using a topic model is that it not only serves as a clustering algorithm, but it can also explain clustering results by providing word probability distributions over topics.Our study proposes a novel topic modeling approach for clustering single cells and detecting topics (gene signatures) in single-cell datasets that measure multiple omics simultaneously. We applied this approach to examine the transcriptional heterogeneity of luminal and triple negative breast cancer cells using patient-derived xenograft models with acquired resistance to chemotherapy and targeted therapy. Through this approach, we identified protein-coding genes and long noncoding RNAs (lncRNAs) that group thousands of cells into biologically similar clusters, accurately distinguishing drug-sensitive and resistant breast cancer types. In comparison to standard state-of-the-art clustering analyses, our approach offers optimal partitioning of genes into topics and cells into clusters simultaneously, producing easily interpretable clustering outcomes. Additionally, we demonstrate that an integrative clustering approach, which combines the information from mRNAs and lncRNAs treated as disjoint omics layers, enhances the accuracy of cell classification.
Submicron-sized in-situ osmotic pressure sensors for in-vitro applications in biology
Authors: Zhang Wenbo , Bertinetti Luca , Yavuzsoy Efe Cuma , Gao Changyou , Schneck Emanuel , Fratzl Peter 
Published: September 2022

AbstractPhysical forces are important cues in determining the development and the normal function of biological tissues. While forces generated by molecular motors have been widely studied, forces resulting from osmotic gradients have been less considered in this context. A possible reason is the lack of direct in-situ measurement methods that can be applied to cell and organ culture systems. Herein, novel kinds of FRET (resonance energy transfer)-based liposomal sensors are developed, so that their sensing range and sensitivity can be adjusted to satisfy physiological osmotic conditions. Several types of sensors are prepared, either based on PEGylated liposomes with steric stabilization and stealth property or on crosslinked liposomes capable of enduring relatively harsh environments for liposomes (e.g. in the presence of biosurfactants). The sensors are demonstrated to be effective in the measurement of osmotic pressures in pre-osteoblastic in-vitro cell culture systems by means of FRET microscopy. This development paves the way towards the in-situ sensing of osmotic pressures in biological culture systems.
Dissecting the Thermodynamics of ATP Binding to GroEL One Nucleotide at a Time
Authors: Walker Thomas , Sun He Mirabel , Gunnels Tiffany , Wysocki Vicki , Laganowsky Arthur , Rye Hays , Russell David 
Published: September 2022

AbstractUnderstanding how large, oligomeric protein complexes respond to the binding of small ligands and other proteins is essential for describing the molecular basis of life. This in turn requires a complete characterization of the binding energetics and correlation of thermodynamic data with interacting structures, including effects of small molecules and solvent. However, the size of many protein oligomers, the myriad intermediate ligation states they can populate, and their often complex allosteric regulation typically restrict analysis by traditional methods to low resolution, ensemble averages. Here, we employ variabletemperature electrospray ionization native mass spectrometry to determine the thermodynamics for stepwise binding of up to ATP molecules to the 801 kDa GroEL complex, a tetradecamer chaperonin complex. Binding thermodynamics reveal strong enthalpy-entropy compensation (EEC) and high degrees of cooperativity are observed for formation of GroEL-ATP7and GroEL-ATP14. These are evidenced by entropically favored ATP binding to thecisring (formation of GroEL-ATP1-7), with variations in EEC for subsequent binding of ATP to thetransring (GroEL-ATP8-14), as expected for negative inter-ring cooperativity. Entropy driven ATP binding to the GroEL tetradecamer is consistent with ligand induced conformational changes of the GroEL tetradecamer, though the magnitude of the entropy change suggests that reorganization of GroEL-hydrating water molecules and/or expulsion of water from the GroEL cavity may also play a key role. By determining the thermodynamic signatures for individual ligand binding reactions to the large, nearly MDa GroEL complex, we expand our fundamental view of chaperonin functional chemistry. Moreover, this work and related studies of protein-ligand interactions illustrate unparalleled capabilities of vT-ESI-nMS for thermodynamics studies of protein interactions with ligands, and other molecules, such as proteins and drugs.
The intrinsically disordered protein glue of myelin: Linking AlphaFold2 predictions to experimental data
Authors: Krokengen Oda C. , Raasakka Arne , Kursula Petri 
Published: September 2022

AbstractNumerous human proteins are either partially or fully classified as intrinsically disordered proteins (IDPs). Due to their properties, high-resolution structural information about IDPs is generally lacking. On the other hand, IDPs are known to adopt local ordered structures upon interactions with ligands, which could bee.g. other proteins or lipid membrane surfaces. While recent developments in protein structure prediction have been revolutionary, their impact on IDP research at high resolution remains limited. We took a specific example of two myelin-specific IDPs, the myelin basic protein (MBP) and the cytoplasmic domain of myelin protein zero (P0ct). Both of these IDPs are known to be crucial for normal nervous system development and function, and while they are disordered in solution, upon membrane binding, they partially fold into helices, being embedded into the lipid membrane. We carried out AlphaFold2 predictions of both proteins and analysed the models in light of previously published data related to solution structure and molecular interactions. We observe that the predicted models have helical segments that closely correspond to the characterised membrane-binding sites on both proteins. We furthermore analyse the fits of the models to SAXS data from the same IDPs. Artificial intelligence-based models of IDPs appear to be able to provide detailed information on the ligand-bound state of these proteins, instead of the form dominating free in solution. We further discuss the implications of the predictions for normal mammalian nervous system myelination and their relevance to understanding disease aspects of these IDPs.
Convergent community assembly among globally separated acidic cave biofilms
Authors: Jones Daniel , Schaperdoth Irene , Northup Diana E. , Gómez-Cruz Rodolfo , Macalady Jennifer L. 
Published: September 2022

AbstractAcidophilic bacteria and archaea inhabit extreme geochemical ‘islands’ that can tell us when and how geographic barriers affect the biogeography of microorganisms. Here we describe microbial communities from extremely acidic (pH 0-1) biofilms known as “snottites” from hydrogen sulfide-rich caves around the world. Given the extreme acidity and subsurface location of these biofilms, and in light of earlier work showing strong geographic patterns among snottite Acidithiobacillus populations, we investigated their structure and diversity in order to understand how geography might impact community assembly. We used 16S rRNA gene cloning and fluorescence in situ hybridization (FISH) to investigate 26 snottite samples from four sulfidic caves in Italy and Mexico. All samples had very low biodiversity and were dominated by sulfur-oxidizing bacteria in the genus Acidithiobacillus. Ferroplasma and other archaea in the Thermoplasmatales ranged from 0 to 50% of total cells, and relatives of the bacterial genera Acidimicrobium and Ferrimicrobium were up to 15% of total cells. Rare phylotypes included Sulfobacillus spp. and members of the Dependentiae and Saccharibacteria (formerly TM6 and TM7). Although the same genera of acidophiles occurred in snottites on separate continents, most members of those genera represent substantially divergent populations with 16S rRNA genes that are only 95-98% similar. Our findings are consistent with a model of community assembly where sulfidic caves are stochastically colonized by microorganisms from local sources, which are strongly filtered through selection for extreme acid tolerance, and these different colonization histories are maintained by dispersal restrictions within and among caves.ImportanceMicroorganisms that are adapted to extremely acidic conditions, known as extreme acidophiles, are catalysts for rock weathering, metal cycling, and mineral formation in naturally acidic environments. They are also important drivers of large-scale industrial processes such as biomining and contaminant remediation. Understanding the factors that govern their ecology and distribution can help us better predict and utilize their activities in natural and engineered systems. However, extremely acidic habitats are unusual in that they are almost always isolated within circumneutral landscapes. So where did their acid-adapted inhabitants come from, and how do new colonists arrive and become established? In this study, we took advantage of a unique natural experiment in Earth’s subsurface to show how isolation may have played a role in the colonization history, community assembly, and diversity of highly acidic microbial biofilms.
Validation and Establishment of a SARS-CoV-2 Lentivirus Surrogate Neutralization Assay as a pre-screening tool for the Plaque Reduction Neutralization Test
Authors: Merluza John , Ung Johnny , Makowski Kai , Robinson Alyssia , Manguiat Kathy , Mueller Nicole , Audet Jonathan , Chen Julie Chih-Yu , Strong James E , Wood Heidi , Bello Alexander 
Published: September 2022

AbstractNeutralization assays are important in understanding and quantifying neutralizing antibody responses towards SARS-CoV-2. The SARS-CoV-2 Lentivirus Surrogate Neutralization Assay (SCLSNA) can be used in biosafety level 2 (BSL-2) laboratories and has been shown to be a reliable, alternative approach to the plaque reduction neutralization test (PRNT). In this study, we optimized and validated the SCLSNA to assess its ability as a comparator and pre-screening method to support the PRNT. Comparability between the PRNT and SCLSNA was determined through clinical sensitivity and specificity evaluations. Clinical sensitivity and specificity produced acceptable results with 100% (95% CI: 94-100) specificity and 100% (95% CI: 94-100) sensitivity against ancestral Wuhan spike pseudotyped lentivirus. The sensitivity and specificity against B.1.1.7 spike pseudotyped lentivirus resulted in 88.3% (95% CI: 77.8 to 94.2) and 100% (95% CI: 94-100), respectively. Assay precision measuring intra-assay variability produced acceptable results for High (1:≥ 640 PRNT50), Mid (1:160 PRNT50) and Low (1:40 PRNT50) antibody titer concentration ranges based on the PRNT50, with %CV of 14.21, 12.47, and 13.28 respectively. Intermediate precision indicated acceptable ranges for the High and Mid concentrations, with %CV of 15.52 and 16.09, respectively. However, the Low concentration did not meet the acceptance criteria with a %CV of 26.42. Acceptable ranges were found in the robustness evaluation for both intra-assay and inter-assay variability. In summary, the validation parameters tested met the acceptance criteria, making the SCLSNA method fit for its intended purpose, which can be used to support the PRNT.
Antibodies against the flotillin-1/2 complex in patients with multiple sclerosis
Authors: Lleixà Cinta , Caballero-Ávila Marta , Pascual-Goñi Elba , Martín-Aguilar Lorena , Vidal Nuria , Tejada Clara , Valdés-Hevia Eduardo , Zárate Elisa , Vesperinas Ana , Collet Roger , Franco Teresa , Martínez-Martínez Laura , Cortés-Vicente Elena , Rojas-García Ricard , Gómez-Anson Beatriz , Gil Anna , González Cristina , Brieva Luis , Martínez-Yélamos Sergio , Querol Luis 
Published: September 2022

ABSTRACTMultiple sclerosis (MS) is a tissue-specific autoimmune disease of the central nervous system in which the antigen(s) remains elusive. Antibodies targeting the flotillin-1/2 (FLOT–1/2) complex have been described in 1-2% of the patients in a recent study. Other candidate antigens as anoctamin-2 (ANO2) or neurofascin-155 (NF155) have been previously described in MS patients, although their clinical relevance remains uncertain. Our study aims to analyse the frequency and clinical relevance of antibodies against NF155, ANO2 and the FLOT-1/2 complex in MS.Serum (n=252) and CSF (n=50) samples from 282 MS patients were included in the study. The control group was composed of 260 serum samples (71 healthy donors and 189 with other neuroinflammatory disorders). Anti-FLOT1/2, anti-ANO2 and anti-NF155 antibodies were tested by cell-based assays using transfected-HEK293 cells. We identified 6 MS patients with antibodies against the FLOT-1/2 complex (2.1%) and 1 MS patient with antibodies against ANO2 (0.35%). All MS patients were negative for anti-NF155 antibodies. Three of the anti-FLOT1/2 positive patients showed anti-FLOT-1/2 positivity in other serum samples extracted at different moments of their disease. IgG subclasses of anti-FLOT-1/2 antibodies were predominantly IgG1 and IgG3.We confirm that antibodies targeting the Flotillin-1/2 complex are present in a subgroup of patients with MS. Further studies are needed to understand the clinical and pathological relevance of anti-FLOT-1/2 autoantibodies in MS.