bluuebunny/crossref_metadata_2025 huggingface dataset:
Matrix mechanics, not hypoxia, modulate quiescin sulfhydryl oxidase 1 (QSOX1) in pancreatic tumor cells
Authors: Millar-Haskell Catherine S. , Thorpe Colin , Gleghorn Jason P.
Published: October 2022

Pancreatic ductal adenocarcinoma (PDAC) is the 4th leading cause of cancer-related deaths in the U.S., despite only being the 11th most common cancer. The high mortality rates of PDAC can be partially attributed to the tumor microenvironment. Unlike most carcinomas, PDAC is characterized by a strong desmoplastic reaction, or a fibrotic stiffening of the extracellular matrix (ECM) in response to chronic inflammation. The desmoplastic reaction is mediated by cancer-associated fibroblasts that deposit ECM proteins (collagens, laminins, fibronectin, etc.) and secrete matrix-remodeling proteins in the tumor parenchyma. Within the past decade, the enzyme quiescin sulfhydryl oxidase 1 (QSOX1) has gained recognition as a significant contributor to solid tumor pathogenesis, but its biological role remains uncertain. QSOX1 is a disulfide bond-generating catalyst that participates in oxidative protein folding in the mammalian cell. Current studies show that inhibiting or knocking down QSOX1 reduces pancreatic cancer cell migration and invasion, alters ECM deposition and organization, and decreases overall tumor growth in mice. However, it is unclear which features of the tumor microenvironment modulate QSOX1 and cause its overexpression in cancer. In this study, we explored potential regulators of QSOX1 expression and secretion by testing two major features of PDAC: hypoxia and mechanical stiffness. To induce hypoxia, we exposed pancreatic cancer cells to atmospheric (low O2) and chemical (CoCl2) hypoxia for up to 48 hours. QSOX1 gene and protein expression did not change in response to hypoxia. Substratum stiffness was modulated using polyacrylamide gels to represent the dynamic pathological range of elastic moduli found in PDAC tissue. We discovered that QSOX1 levels were decreased on softer surfaces compared to conventional tissue culture plastic. This paper presents new results and challenges prior findings on QSOX1 regulation in pancreatic tumor cells.
Long-range DNA end resection supports homologous recombination by checkpoint activation rather than extensive homology generation
Authors: Kimble Michael T , Johnson Matthew J , Nester Mattie R , Symington Lorraine S
Published: October 2022

Homologous recombination (HR), the error-free mechanism for double-strand break (DSB) repair, relies on DNA end resection by nucleolytic degradation of the 5′-terminated ends. However, the role of long-range resection mediated by Exo1 and/or Sgs1-Dna2 in HR is not fully understood. Here, we show that Exo1 and Sgs1 are dispensable for recombination between closely-linked repeats but are required for interchromosomal repeat recombination inSaccharomyces cerevisiae. This requirement for long-range resection is coupled to DNA damage checkpoint activation and the need for checkpoint proteins. Furthermore, artificial activation of the checkpoint partially restores interchromosomal recombination toexo1Δ sgs1Δcells. However, cell cycle delay is insufficient to rescue the interchromosomal recombination defect ofexo1Δ sgs1Δcells, suggesting an additional role for the checkpoint. Given that the checkpoint is necessary for DNA damage-induced chromosome mobility, we propose that the importance of the checkpoint, and therefore long-range resection, in interchromosomal recombination is due to a need to increase chromosome mobility to facilitate pairing of distant sites. The need for long-range resection is circumvented when the DSB and its repair template are in close proximity.
Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank
Authors: Hofmeister Robin J. , Ribeiro Diogo M. , Rubinacci Simone , Delaneau Olivier
Published: October 2022

The UK Biobank performed whole-genome sequencing (WGS) and whole-exome sequencing (WES) across hundreds of thousands of individuals, allowing researchers to study the effects of both common and rare variants. Haplotype phasing distinguishes the two inherited copies of each chromosome into haplotypes and unlocks novel analyses at the haplotype level. In this work, we describe a new phasing method, SHAPEIT5, that accurately and rapidly phases large sequencing datasets and illustrates its key features on the UK Biobank WGS and WES data. First, we show that it phases rare variants with high accuracy. For instance, variants found in 1 sample out of 100,000 in the WES data are phased with accuracy above 95%. Second, we show that it can phase singletons, although with moderate accuracy, thereby making their inclusion in downstream analyses possible. Third, we show that the use of UK Biobank as a reference panel increases the accuracy of genotype imputation, an increase that is more pronounced when phased with SHAPEIT5 compared to other methods. Finally, we screen the phased WES data for loss-of-function (LoF) compound heterozygous (CH) events and identify 549 genes in which both gene copies are found knocked out. This list of genes complements current knowledge of gene essentiality in the human genome. We provide SHAPEIT5 in an open-source format, providing researchers with the means to leverage haplotype information in genetic studies.
TF-Prioritizer: a java pipeline to prioritize condition-specific transcription factors
Authors: Hoffmann Markus , Trummer Nico , Schwartz Leon , Jankowski Jakub , Lee Hye Kyung , Willruth Lina-Liv , Lazareva Olga , Yuan Kevin , Baumgarten Nina , Schmidt Florian , Baumbach Jan , Schulz Marcel H. , Blumenthal David B. , Hennighausen Lothar , List Markus
Published: October 2022

Background

Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.

Results

We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.

Conclusion

TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Overground gait adaptability in older adults with diabetes in response to virtual targets and physical obstacles
Authors: Martin Suzanne , Taylor Simon B. , Shideler Blynn L. , Ogrin Rajna , Begg Rezaul
Published: October 2022

Background

To step over an unexpected obstacle, individuals adapt gait; they adjust step length in the anterior-posterior direction prior to the obstacle and minimum toe clearance height in the vertical direction. Inability to adapt gait may lead to falls in older adults with diabetes. Therefore, this study aimed to investigate gait adaptability in older adults with diabetes.

Research question

Does diabetes impair gait adaptability and increase sagittal foot adjustment errors?

Methods

Three cohorts of 16 people were recruited: young adults (Group I), healthy older adults (Group II), and older adults with diabetes (Group III). Participants walked in baseline at their comfortable speeds. They then walked and responded to what was presented in gait adaptability tests which included 40 trials with four random conditions: step shortening, step lengthening, obstacle avoiding, and walking through. Virtual step length targets were 40% of the baseline step length longer or shorter than the mean baseline step length; the actual obstacle was a 5-cm height across the walkway. A Vicon three-dimensional motion capture system and four A.M.T.I force plates were used to quantify spatiotemporal parameters of a gait cycle and sagittal foot adjustment errors (differences between desired and actual responses in the second step of the gait cycle). Analyses of variance (ANOVA) repeated measured tests were used to investigate group and condition effects on dependent gait parameters at a significance level of 0.05.

Results

Statistical analyses of Group I (n = 16), Group II (n = 14) and Group III (n = 13) revealed that gait parameters did not differ between groups in baseline. However, they were significantly different in adaptability tests. Group III significantly increased their stance and double support times in adaptability tests, but these adaptations did not improve their foot adjustments. They had the greatest step length errors and the lowest toe-obstacle clearance which might cause them to touch the obstacle the most.

Significance

The presented gait adaptability tests may serve as entry tests for falls prevention programs.
Persistence of the ecological niche in pond damselflies underlies a stable adaptive zone despite varying selection
Authors: Gupta Anjali , Svensson Erik I. , Frietsch Henrik , Tsuboi Masahito
Published: October 2022

Following the development of regression-based methods to estimate natural and sexual selection, evolutionary biologists have quantified the strength, mode and direction of selection in natural populations. Although this approach has been successful, its limitations include lack of replication across species, compromising the generality of the inferences beyond microevolutionary time scales. Here, we carried out a comparative study of selection on wing shape and body size across multiple populations of two closely related and ecologically similar pond damselflies:Enallagma cyathigerumandIschnura elegans(Odonata: Coenagrionidae). We found weak stabilizing selection on wing shape in both sexes, and no evidence that selection on this trait differed between the species. In contrast, selection on body size was curvilinear in males and directional in females, and they differed in form (males) and intensity (females) between these two species. By analyzing selection on the fine-grained spatial scale, we found that selection on male body size was shaped by the local mating system, and the relationship between mating system characteristics and directional selection was remarkably consistent across these species. Finally, we present a graphical model that links contemporary selection and macroevolution. Based on this model, we conclude that the persistence in ecological modes of life in pond damselflies offers a plausible explanation for why varying selection in nature may still result in a stable adaptive zone lasting millions of years.
Multiphase coexistence capacity in complex fluids
Authors: Shrinivas Krishna , Brenner Michael P.
Published: October 2022

Complex fluids like the cytoplasm comprise hundreds of species organized into many coexisting phases. How molecular interactions, reflecting sequence, design, or functional constraints, dictate multiphase coexistence is a major open question. To answer this, we consider models of multicomponent fluids with both designed and random interactions. When crosstalk is introduced, we show that coexisting phases lose specificity beyond a common threshold. In a sequence model, we demonstrate that phase capacity is limited by sequence length and grows logarithmically/linearly with sequence length/number. These results provide a general route to program multiphase coexistence from molecular features.
GrapHiC: An integrative graph based approach for imputing missing Hi-C reads
Authors: Murtaza Ghulam , Wagner Justin , Zook Justin M. , Singh Ritambhara
Published: October 2022

Hi-C experiments allow researchers to study and understand the 3D genome organization and its regulatory function. Unfortunately, sequencing costs and technical constraints severely restrict access to high-quality Hi-C data for many cell types. Existing frameworks rely on a sparse Hi-C dataset or cheaper-to-acquire ChIP-seq data to predict Hi-C contact maps with high read coverage. However, these methods fail to generalize to sparse or cross-cell-type inputs because they do not account for the contributions of epigenomic features or the impact of the structural neighborhood in predicting Hi-C reads. We propose GrapHiC, which combines Hi-C and ChIP-seq in a graph representation, allowing more accurate embedding of structural and epigenomic features. Each node represents a binned genomic region, and we assign edge weights using the observed Hi-C reads. Additionally, we embed ChIP-seq and relative positional information as node attributes, allowing our representation to capture structural neighborhoods and the contributions of proteins and their modifications for predicting Hi-C reads. Our evaluations show that GrapHiC generalizes better than the current state-of-the-art on cross-cell-type settings and sparse Hi-C inputs. Moreover, we can utilize our framework to impute Hi-C reads even when no Hi-C contact map is available, thus making high-quality Hi-C data more accessible for many cell types.

Availability

https://github.com/rsinghlab/GrapHiC

ACM Reference Format

Ghulam Murtaza, Justin Wagner, Justin M. Zook, and Ritambhara Singh. 2018. GrapHiC: An integrative graph based approach for imputing missing Hi-C reads. InProceedings of 22nd International Workshop on Data Mining in Bioinformatics (BioKDD ‘23). ACM, New York, NY, USA, 16 pages. https://doi.org/XXXXXXX.XXXXXXX
Targeted Vibration-Induced Necrosis in Cancer Cells using Paramagnetic Microrobots
Authors: Mallick Sudipta , Sokolich Max , Rivas David , Das Sambeeta
Published: October 2022

Therapeutic delivery of anti-cancer drugs is a major goal of modern medicine. In particular, microrobots (MRs) have recently been studied for their ability to navigate difficult-to-reach regions in the human body to deliver therapeutics for microscopically localized interventions. However, the control of individual and swarms of MRs to precisely target localized cellular regions remains a significant challenge, preventing their applications as delivery systems in cancer research. In this study, magnetic MRs were used to target cancer cells and create localized magnetic oscillations which resulted in magnetolysis of cancer cells. The magnetic MRs were selectively steered towards Hepatocarcinoma cells (HepG2 cells) using our custom-built magnetic controller under a rotating magnetic field at different frequencies. After internalization of the microrobots by cancer cells, magnetic oscillation of varying dosages was applied to disrupt the internal structure of cancer cells which leads to subsequent cell death.
Associations of microbial diversity with age and other clinical variables among pediatric chronic rhinosinusitis (CRS) patients
Authors: Lim Shen Jean , Jithpratuck Warit , Wasylik Kathleen , Sriaroon Panida , Dishaw Larry J.
Published: October 2022

Chronic rhinosinusitis (CRS) is a heterogenous disease that causes persistent paranasal sinus inflammation in children. Microorganisms are thought to contribute to the etiology and progression of CRS. Culture-independent microbiome analysis offers deeper insights on sinonasal microbial diversity and microbe-disease associations than culture-based methods. To date, CRS-related microbiome studies have mostly focused on the adult population, and only one study has characterized the pediatric CRS microbiome. In this study, we analyzed the bacterial diversity of adenoid tissue, adenoid swab, maxillary sinus, and sinus wash samples from 45 pediatric CRS patients recruited from the Johns Hopkins All Children’s Hospital (JHACH) in St Petersburg, FL, USA. The alpha diversity in these samples was associated with baseline nasal steroid use, leukotriene receptor antagonist (LTRA) use, and total serum immunoglobulin (Ig) E (IgE) level.Streptococcus, Moraxella, andHaemophilusspp. were most frequently identified from sinus cultures and the sequenced 16S rRNA gene content. Comparative analyses combining our samples with the samples from the previous microbiome study revealed differentially abundant genera between patients with pediatric CRS and healthy controls, includingCutibacteriumandMoraxella. Additionally, the abundances ofStreptobacillusandStaphylococcuswere consistently correlated with age in both adenoid- and sinus-derived samples. Our study uncovers new associations of alpha diversity with clinical parameters, as well as associations of specific genera with disease status and age, that can be further investigated.
Bayesian linear models with unknown design over finite alphabets
Authors: Wang Yuexuan , Futschik Andreas , Dutta Ritabrata
Published: October 2022

Our topic is the reconstruction of the unknown matricesSandωfor the multivariate linear modelY=Sω+εunder the assumption that the entries ofSare drawn from the finite alphabet 𝔄 = 0, 1 andωis a weight matrix. While a frequentist method has recently been proposed for this purpose, a Bayesian approach seems also desirable. We therefore provide a new hierarchical Bayesian method for this inferential task. Our approach provides estimates of the posterior that may be used to quantify uncertainty. Since matching permutations in bothSandωlead to the same reconstructionSω, we introduce an order-preserving shrinkage prior to establish identifiability with respect to permutations.
Revisiting Macromolecular Hydration with HullRadSAS
Authors: Fleming Patrick J. , Correia John J. , Fleming Karen G.
Published: October 2022

Hydration of biological macromolecules is important for their stability and function. Historically, attempts have been made to describe the degree of macromolecular hydration using a single parameter over a narrow range of values. Here, we describe a method to calculate two types of hydration: surface shell water and entrained water. A consideration of these two types of hydration helps to explain the “hydration problem” in hydrodynamics. The combination of these two types of hydration allows accurate calculation of hydrodynamic volume and related macromolecular properties such as sedimentation and diffusion coefficients, intrinsic viscosities, and the concentration dependent non-ideality identified with sedimentation velocity experiments.
Glutarate regulates T cell function and metabolism
Authors: Minogue Eleanor , Cunha Pedro P. , Quaranta Alessandro , Zurita Javier , Teli Shiv Sah , Wadsworth Brennan J. , Hughes Rob , Grice Guinevere L. , Velica Pedro , Bargiela David , Barbieri Laura , Wheelock Craig E. , Nathan James A. , Koivunen Peppi , Foskolou Iosifina P. , Johnson Randall S.
Published: October 2022

T cell function is influenced by several metabolites; some acting through enzymatic inhibition of α-KG-dependent dioxygenases (αKGDDs), others, through post-translational modification of lysines in important targets. We show here that glutarate, a product of amino acid catabolism, has the capacity to do both, with effects on T cell function and differentiation. Glutarate exerts those effects through αKGDD inhibition and through direct regulation of T cell metabolism via post-translational modification of the pyruvate dehydrogenase E2 subunit. Diethyl-glutarate, a cell-permeable form of glutarate, alters CD8+T cell differentiation and increases cytotoxicity against target cells.In vivoadministration of the compound reduces tumor growth and is correlated with increased levels of both peripheral and intratumoral cytotoxic CD8+T cells. These results demonstrate that glutarate regulates both T cell metabolism and differentiation, with a potential role in the improvement of T cell immunotherapy.
DGH-GO: Dissecting the Genetic Heterogeneity of complex diseases using Gene Ontology
Authors: Asif M , Martiniano Hugo F. , Lamurias Andre , Kausar Samina , Couto Francisco M.
Published: October 2022

Complex diseases such as neurodevelopmental disorders (NDDs) lack biological markers for their diagnosis and are phenotypically heterogeneous, which makes them difficult to diagnose at early-age. The genetic heterogeneity corresponds to their clinical phenotype variability and, because of this, complex diseases exhibit multiple etiologies. The multi-etiological aspects of complex-diseases emerge from distinct but functionally similar group of genes. Different diseases sharing genes of such groups show related clinical outcomes that further restrict our understanding of disease mechanisms, thus, limiting the applications of personalized medicine or systems biomedicine approaches to complex genetic disorders.

Here, we present an interactive and user-friendly application, DGH-GO that allows biologists to dissect the genetic heterogeneity of complex diseases by stratifying the putative disease-causing genes into clusters that may lead to or contribute to a specific disease traits development. The application can also be used to study the shared etiology of complex-diseases.

DGH-GO creates a semantic similarity matrix of putative disease-causing genes or known-disease genes for multiple disorders using Gene Ontology (GO). The resultant matrix can be visualized in a 2D space using different dimension reduction methods (T-SNE, Principal component analysis and Principal coordinate analysis). Functional similarities assessed through GO and semantic similarity measure can be used to identify clusters of functionally similar genes that may generate a disease specific traits. This can be achieved by employing four different clustering methods (K-means, Hierarchical, Fuzzy and PAM). The user may change the clustering parameters and see their effect on stratification results immediately.

DGH-GO was applied to genes disrupted by rare genetic variants in Autism Spectrum Disorder (ASD) patients. The analysis confirmed the multi-etiological nature of ASD by identifying the four clusters that were enriched for distinct biological mechanisms and phenotypic terms. In the second case study, the analysis of genes shared by different NDDs showed that genes involving in multiple disorders tend to aggregate in similar clusters, indicating a possible shared etiology. In summary, functional similarities, dimension reduction and clustering methods, coupled with interactive visualization and control over analysis allows biologists to explore and analyze their datasets without requiring expert knowledge on these methods.

The source code of proposed application is available athttps://github.com/Muh-Asif/DGH-GO

Graphical abstract
Structure and mechanics of the human Nuclear Pore Complex basket
Authors: Vial Anthony , Costa Luca , Dosset Patrice , Rosso Pietro , Boutières Gaëlle , Faklaris Orestis , Haschke Heiko , Milhiet Pierre-Emmanuel , Doucet Christine M.
Published: October 2022

Nuclear pore complexes (NPCs) are the only gateways between the nucleus and cytoplasm in eukaryotic cells. They restrict free diffusion to molecules below 5 nm while facilitating the active transport of selected cargoes, sometimes as large as the pore itself. This versatility implies an important pore plasticity. Recently, cryo-EM and AI-based protein modeling revealed with acute precision how most NPC constituents are arranged. But the basket, a fish trap-like structure capping the nucleoplasmic side of the pore, remains the missing piece in this puzzle. Here by Atomic Force Microscopy (AFM) coupled to Single Molecule Localization Microscopy (SMLM) we revealed that the basket is very soft and explores a large conformational landscape: apart from its canonical shape, it dives into the central pore channel or opens, with filaments reaching to the pore sides. Our observations enlighten how this structure can adapt and let morphologically diverse cargoes shuttling through NPCs.
Intra-V1 functional networks predict observed stimuli
Authors: Ontivero-Ortega Marlis , Iglesias-Fuster Jorge , Perez-Hidalgo Jhoanna , Marinazzo Daniele , Valdes-Sosa Mitchell , Valdes-Sosa Pedro
Published: October 2022

Several studies suggest that the pattern of co-fluctuations of neural activity within V1 (measured with fMRI) changes with variations in attention/perceptual organization of observed stimuli. Here we used multivariate pattern analysis of intra-V1 correlation matrices to predict the level and shape of the observed Navon letters. We examined the inter-individual stability of network topologies and then tested if they contained intra-individual information about stimulus shape or level that was tolerant to changes in the irrelevant feature. The inter-individual classification was accurate for all specific level and letter-shape tests. These results indicate that the association of V1 topologies and perceptual states is stable across participants. Intra-participant cross-classification of level (ignoring shape) was accurate but failed for shape (ignoring level). Cross-classification of stimulus level was more accurate when the stimulus-evoked response was suppressed in the fMRI time series and not present for correlations based on raw time series, stimulus-evoked beta-series, or simulations of the effects of eye movements measured in a control group. Furthermore, cross-classification weight maps evinced asymmetries of link strengths across the visual field that mirrored perceptual asymmetries. We hypothesize that feedback about level information drives the intra-V1 networks based on fMRI background activity. These intra-V1 networks can shed light on the neural basis of attention and perceptual organization.
Cell Surface-localized CsgF Condensate is a Gatekeeper in Bacterial Curli Subunit Secretion
Authors: Swasthi Hema M. , Basalla Joseph L. , Dudley Claire E. , Vecchiarelli Anthony G. , Chapman Matthew R.
Published: October 2022

Curli are functional amyloids present on the outer membrane ofE. coli. Cell-surface aggregation of CsgA, the major subunit of curli, is a well-orchestrated process. CsgB, the minor subunit of curli, nucleates the aggregation of CsgA while CsgF, a curli accessory protein, ensures proper anchoring of CsgB to the cell surface. The molecular basis of the interactions between CsgF and curli subunits is unclear. Here, we show that CsgF undergoes phase separationin vitroand that the ability of CsgF variants to phase separate tightly correlated with CsgF function in cells during curli biogenesis. Substitution of phenylalanine residues in the CsgF N-terminus both reduced the propensity of CsgF to phase-separate and impaired curli biogenesis. Exogenous addition of purified CsgF complementedcsgF−cells. This exogenous addition assay was used to assess the ability of CsgF variants to complementcsgF−cells. The presence of CsgF on the cell surface modulated the secretion of CsgA to the cell surface. We also found that the CsgB nucleator protein is a CsgF client. CsgB can form SDS-insoluble aggregates within the dynamic CsgF condensate, and we propose that these multi-component CsgF-B condensates form a nucleation-competent complex that templates CsgA amyloid formation on the cell surface. Together, our study provides insight into the ability of CsgF to phase separate, regulate CsgA secretion, and promote CsgB aggregation in curli assembly.
Comparison of the risk of hospitalisation among BA.1 and BA.2 COVID-19 cases treated with Sotrovimab in the community in England
Authors: Harman Katie , Nash Sophie G , Webster Harriet H , Groves Natalie , Hardstaff Jo , Bridgen Jessica , Blomquist Paula B , Hope Russell , Ashano Efejiro , Myers Richard , Rokadiya Sakib , Hopkins Susan , Brown Colin S , Chand Meera , Dabrera Gavin , Thelwall Simon
Published: October 2022

Objectives

Sotrovimab is one of several therapeutic agents that have been licensed to treat people at risk of severe outcomes following COVID-19 infection. However, there are concerns that it has reduced efficacy to treat people with the BA.2 sub-lineage of the Omicron (B.1.1.529) SARS-CoV-2 variant. We compared individuals with the BA.1 or BA.2 sub-lineage of the Omicron variant treated Sotrovimab in the community to assess their risk of hospital admission.

Methods

We performed a retrospective cohort study of individuals treated with Sotrovimab in the community and either had BA.1 or BA.2 variant classification.

Results

Using a Stratified Cox regression model it was estimated that the hazard ratios (HR) of hospital admission with a length of stay of two or more days was 1.17 for BA.2 compared to BA.1 (95% CI 0.74-1.86) and for such admissions where COVID-19 ICD-10 codes was recorded the HR was 0.98 (95% CI 0.58-1.65).

Conclusion

These results suggest that the risk of hospital admission is similar between BA.1 and BA.2 cases treated with Sotrovimab in the community.
Exploring the Gut-Brain Connection in Gastroparesis with Autonomic and Gastric Myoelectric Monitoring
Authors: Subramanian Sandya , Kunkel David C. , Nguyen Linda , Coleman Todd P.
Published: October 2022

Objective

The goal of this study was to identify autonomic and gastric myoelectric biomarkers from throughout the day that differentiate patients with gastroparesis, diabetics without gastroparesis, and healthy controls, while providing insight into etiology.

Methods

We collected 19 24-hour recordings of electrocardiogram (ECG) and electrogastrogram (EGG) data from healthy controls and patients with diabetic or idiopathic gastroparesis. We used physiologically and statistically rigorous models to extract autonomic and gastric myoelectric information from the ECG and EGG data respectively. From these, we constructed quantitative indices which differentiated the different groups and demonstrated their application in automatic classification paradigms and as quantitative summary scores.

Results

We identified several differentiators that separate healthy controls from gastroparetic patient groups, specifically around sleep and meals. We also demonstrated the downstream utility of these differentiators in automatic classification and quantitative scoring paradigms. Even with this small pilot dataset, automated classifiers achieved an accuracy of 79% separating autonomic phenotypes and 65% separating gastrointestinal phenotypes. We also achieved 89% accuracy separating controls from gastroparetic patients in general and 90% accuracy separating diabetics with and without gastroparesis. These differentiators also suggested varying etiologies for different phenotypes.

Conclusion

The differentiators we identified were able to successfully distinguish between several autonomic and gastrointestinal (GI) phenotypes using data collected while at-home with non-invasive sensors.

Significance

Autonomic and gastric myoelectric differentiators, obtained using at-home recording of fully non-invasive signals, can be the first step towards dynamic quantitative markers to track severity, disease progression, and treatment response for combined autonomic and GI phenotypes.
Association between Serum Biomarker Profile and Real-World Evidence of Disability in Multiple Sclerosis
Authors: Zhu Wen , Chen Chenyi , Zhang Lili , Hoyt Tammy , Walker Elizabeth , Venkatesh Shruthi , Zhang Fujun , Qureshi Ferhan , Foley John F. , Xia Zongqi
Published: October 2022

Objective

Biomarkers could inform disease worsening and severity in people with MS (pwMS). Few studies have examined blood biomarkers informative of patient-reported outcome (PRO) of disability in pwMS. In this study we examine the associations between serum protein biomarker profiles and patient-reported disability in pwMS.

Methods

This cross-sectional study included adults with a neurologist-confirmed diagnosis of MS from the University of Pittsburgh Medical Center (Pittsburgh, PA) and the Rocky Mountain MS Clinic (Salt Lake City, Utah) between 2017 and 2020. For exposure, we included 19 serum protein biomarkers potentially associated with MS inflammatory disease activity and 7 key clinical factors (age at sample collection, sex, race/ethnicity, disease subtype, disease duration, disease-modifying treatment, and time interval between sample collection and closest PRO assessment). Using 6 machine learning approaches (Least Absolute Shrinkage and Selection Operator [LASSO] regression, Random Forest [RF], XGBoost, Support-Vector Machines [SVM], stacking ensemble learning, and stacking classification algorithm), we examined model performance in predicting Patient Determined Disease Steps (PDDS) as the primary outcome. We assessed model prediction of Patient-Reported Outcomes Measurement Information System (PROMIS) physical function in a subgroup. We reported model performance using the held-out testing set.

Results

We included 431 unique participants (mean age 49 years, 81% women, 94% non-Hispanic White). Using binary outcomes, models comprising both routine clinical factors and the 19 proteins as features consistently outperformed base models (containing clinical features alone or clinical features plus single protein) in predicting severe (PDDS≥4, PROMIS<35) versus mild/moderate (PDDS<4, PROMIS≥35) disability for all machine learning approaches, with LASSO achieving the best area under the curve (AUCPDDS=0.91, AUCPROMIS=0.90). Using ordinal/continuous outcomes, LASSO models with combined clinical factors and 19 proteins as features (R2PDDS=0.31, R2PROMIS=0.35) again outperformed base models. The four LASSO models (PDDS, PROMIS; both binary and ordinal/continuous) with combined clinical and protein features shared 2 clinical features (disease subtype, disease duration) and 4 protein biomarkers (CDCP1, IL-12B, NEFL, PRTG).

Conclusions

Serum protein biomarker profiles improve the prediction of real-world MS disability status beyond clinical profile alone or clinical profile plus individual protein biomarker, reaching clinically actionable performance.
Metabolic consequences of various fruit-based diets in a generalist insect species
Authors: Olazcuaga Laure , Baltenweck Raymonde , Leménager Nicolas , Maia-Grondard Alessandra , Claudel Patricia , Hugueney Philippe , Foucaud Julien
Published: October 2022

Most phytophagous insect species exhibit a limited diet breadth and specialize on few or a single host plant. In contrast, some species display a remarkably large diet breadth, with host plants spanning several families and many species. It is unclear, however, whether this phylogenetic generalism is supported by a generic metabolic use of common host chemical compounds (‘metabolic generalism’) or alternatively by distinct uses of diet-specific compounds (‘multi-host metabolic specialism’)? Here, we simultaneously investigated the metabolomes of fruit diets and of individuals of a generalist phytophagous species,Drosophila suzukii, that developed on them. The direct comparison of metabolomes of diets and consumers enabled us to disentangle the metabolic fate of common and rarer dietary compounds. We showed that the consumption of biochemically dissimilar diets resulted in a canalized, generic response from generalist individuals, consistent with the metabolic generalism hypothesis. We also showed that many diet-specific metabolites, such as related to the particular color, odor or taste of diets, were not metabolized, and rather accumulated in consumer individuals, even when probably detrimental to fitness. As a result, while individuals were mostly similar across diets, the detection of their particular diet was straightforward. Our study thus supports the view that dietary generalism may emerge from a passive, opportunistic use of various resources, contrary to more widespread views of an active role of adaptation in this process. Such a passive stance towards dietary chemicals, probably costly in the short term, might favor the later evolution of new diet specializations.
Multi-Omic Analysis ofTyrophagus putrescentiaeReveals Insights into the Allergen Complexity of Storage Mites
Authors: Wan Angel Tsz-Yau , Xiong Qing , Xiao Xiaojun , Ao Kelvin Fu-Kiu , Jang Seok Woo , Wong Brian Shing-Hei , Wang Mingqiang , Cao Qin , Fung Cathy Sin-Hang , Chew Fook-Tim , Sun Baoqing , Ngai Sai Ming , Leung Ting-Fan , Jeong Kyoung Yong , Liu Xiaoyu , Tsui Stephen Kwok-Wing
Published: October 2022

Background

The storage miteTyrophagus putrescentiaeis one of the major mites causing allergies in Chinese and Korean populations, but its allergen profile in incomplete when compared with that of house dust mites. Multiple genome-based methods have been introduced into the allergen study of mites and have enabled a better understanding of these medically important organisms.

Objective

We sought to reveal a comprehensive allergen profile ofTyrophagus putrescentiaeand advance the allergen study of storage mites.

Methods

Based on a high-quality assembled and annotated genome, anin silicoanalysis was performed by searching reference sequences to identify allergens. Immunoassay ELISA assessed the allergenicities of recombinant proteins. MALDI-TOF mass spectrometry identified the IgE-binding proteins. Comparative genomics analysis was employed for the important allergen gene families.

Results

A complete allergen profile ofTyrophagus putrescentiaewas revealed, including thirty-seven allergen groups (up to Tyr p 42). Among them, five novel allergens were verified using the sera of allergy patients. Massive allergen homologs were identified as the result of gene duplications in genome evolution. Proteomic identification again revealed a wide range of allergen homologs. In the NPC2 family and GSTs, comparative analysis shed light on the expansion and diversification of the allergen groups.

Conclusion

Using multi-omic approaches, the comprehensive allergen profile including massive homologs was disclosed inTyrophagus putrescentiae, which revealed the allergen complexity of the storage mite and could ultimately facilitate the component-resolved diagnosis.
SARS-CoV-2 nsp3-4 suffice to form a pore shaping replication organelles
Authors: Zimmermann Liv , Zhao Xiaohan , Makroczyova Jana , Wachsmuth-Melm Moritz , Prasad Vibhu , Bartenschlager Ralf , Chlanda Petr
Published: October 2022

Coronavirus replication is associated with the remodeling of cellular membranes resulting in the formation of double-membrane vesicles (DMVs). Recently, a pore spanning DMV was identified as a putative portal for viral RNA transcription and replication products providing a novel target for antiviral intervention. However, the exact components and the structure of the SARS-CoV-2 pore remain to be determined. Here, we investigate the structure of DMV pores byin situcryo-electron tomography combined with subtomogram averaging. We reveal non-structural proteins (nsp) 3 and 4 as minimal components forming a DMV spanning pore and show that nsp3 Ubl1-Ubl2 domains are critical for inducing membrane curvature and DMV formation. Altogether, SARS-CoV-2 nsp3-4 has a dual role by driving the biogenesis of replication organelles and forming DMV-spanning replicopores.

One-Sentence Summary

Biogenesis of SARS-CoV-2 replication organelles is driven by nsp3-4 constituting the double-membrane vesicle spanning pore.
A systems approach evaluating the impact of SARS-CoV-2 variant of concern mutations on CD8+ T cell responses
Authors: Buckley Paul R. , Lee Chloe H. , Antanaviciute Agne , Simmons Alison , Koohy Hashem
Published: October 2022

T cell recognition of SARS-CoV-2 antigens after vaccination and/or natural infection has played a central role in resolving SARS-CoV-2 infections and generating adaptive immune memory. However, the clinical impact of SARS-CoV-2-specific T cell responses is variable and the mechanisms underlying T cell interaction with target antigens are not fully understood. This is especially true given the virus’ rapid evolution, which leads to new variants with immune escape capacity. In this study, we used the Omicron variant as a model organism and took a systems approach to evaluate the impact of mutations on CD8+ T cell immunogenicity. We computed an ‘immunogenicity potential’ score for each SARS-CoV-2 peptide antigen from the ancestral strain and Omicron, capturing both antigen presentation and T cell recognition probabilities. By comparing ancestral vs. Omicron immunogenicity scores, we reveal a divergent and heterogeneous landscape of impact for CD8+ T cell recognition of mutated targets in Omicron variants. While T cell recognition of Omicron peptides is broadly preserved, we observed mutated peptides with deteriorated immunogenicity that may assist breakthrough infection in some individuals. We then combined our scoring scheme with anin-silicomutagenesis, to characterise the position- and residue-specific theoretical mutational impact on immunogenicity. While we predict many escape trajectories from the theoretical landscape of substitutions, our study suggests that Omicron mutations in T cell epitopes did not develop under cell-mediated pressure. Our study provides a generalisable platform for fostering a deeper understanding of existing and novel variant impact on antigen-specific vaccine- and/or infection-induced T cell immunity.
In vitropersistence level reflectsin vivoantibiotic survival of naturalPseudomonas aeruginosaisolates in a murine lung infection model
Authors: Verstraete Laure , Aizawa Juliana , Govaerts Matthias , De Vooght Linda , Michiels Jan , Van den Bergh Bram , Cos Paul
Published: October 2022

Nowadays, clinicians are more and more confronted with the limitations of antibiotics to completely cure bacterial infections in patients. It has long been assumed that only antibiotic resistance plays a pivotal role in this. Indeed, the worldwide emergence of antibiotic resistance is considered as one of the major health threats of the 21stcentury. However, the presence of persister cells also has a significant influence on treatment outcomes. These antibiotic-tolerant cells are present in every bacterial population and are the result of the phenotypic switching of normal, antibiotic-sensitive cells. Persister cells complicate current antibiotic therapies and contribute to the development of resistance. In the past, extensive research has been performed to investigate persistence in laboratory settings, however, antibiotic tolerance in conditions that mimic the clinical setting is still poorly understood. In this study, we have optimized a mouse model for lung infections of the opportunistic pathogenPseudomonas aeruginosa. In this model, mice are intratracheally infected withP. aeruginosaembedded in seaweed alginate beads and subsequently treated with tobramycin via nasal droplets. A strain panel of 18P. aeruginosaisolates originating from environmental, human and animal clinical sources was selected to assess survival in the animal model. These survival levels were positively correlated with the survival levels determined via time-kill assays which is a common method to study persistence in the laboratory. We showed that both survival levels are comparable and thus that the classical persister assays are indicative for antibiotic tolerance in a clinical setting. The optimized animal model also allows us to test potential antipersister molecules and study persistence.

Importance

The importance of targeting persister cells in antibiotic therapies becomes more evident as these antibiotic-tolerant cells underlie relapsing infections and resistance development. Here, we studied persistence in a clinically relevant pathogen,Pseudomonas aeruginosa. It is one of the six ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, P. aeruginosa, Enterobacterspp.) that are considered as a major health threat.P. aeruginosais mostly known for causing chronic lung infections in cystic fibrosis patients. We mimicked these lung infections in a mouse model to study persistence in more clinical conditions. We showed that the survival levels of naturalP. aeruginosaisolates in this model are positively correlated with the survival levels measured in classical persistence assays. These results not only validate the use of our current techniques to study persistence, but also open opportunities to study new persistence mechanisms or evaluate new antipersister compoundsin vivo.
Plant spatial aggregation modulates the interplay between plant competition and pollinator attraction with contrasting outcomes of plant fitness
Authors: Hurtado María , Godoy Oscar , Bartomeus Ignasi
Published: October 2022

Ecosystem functions such as seed production are the result of a complex interplay between competitive plant-plant interactions and mutualistic pollinator-plant interactions. In this interplay, spatial plant aggregation could work in two different directions: it could increase intra- and interspecific competition, thus reducing seed production; but it could also attract pollinators increasing plant fitness. To shed light on how plant spatial arrangement modulates this balance, we conducted a field study in a Mediterranean annual grassland with three focal plant species with different phenology (Chamaemelum fuscatum(early phenology),Leontodon maroccanus(middle phenology) andPulicaria paludosa(late phenology)) and a diverse guild of pollinators (flies, bees, beetles, and butterflies). All three species showed spatial aggregation of conspecific individuals. Additionally, we found that the two mechanisms were working simultaneously: crowded neighborhoods reduced individual seed production via plant-plant competition, but they also made individual plants more attractive for some pollinator guilds, increasing visitation rates and plant fitness. The balance between these two forces varied depending on the focal species and the spatial scale considered. Therefore, our results indicate that mutualistic interactions not always effectively compensate for competitive interactions in situations of spatial aggregation of flowering plants, at least in our study system. We highlight the importance of explicitly considering the spatial structure at different spatial scales of multitrophic interactions to better understand individual plant fitness and community dynamics.