bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolutionarily stable preferences
Authors: Alger Ingela
Published: March 2023

The 50-year old concept of an evolutionarily stable strategy provided a key tool for theorists to model ultimate drivers of behaviour in social interactions. For decades, economists ignored ultimate drivers and used models in which individuals choose strategies based on their preferences—a proximate mechanism for behaviour—and the distribution of preferences in the population was taken to be fixed and given. This article summarizes some key findings in the literature on evolutionarily stable preferences, which in the past three decades has proposed models that combine the two approaches: individuals inherit their preferences, the preferences determine their strategy choices, which in turn determine evolutionary success. One objective is to highlight complementarities and potential avenues for future collaboration between biologists and economists.

This article is part of the theme issue ‘Half a century of evolutionary games: a synthesis of theory, application and future directions’.
De-novo genome assembly for Akanthomyces muscarius, a biocontrol agent of insect agricultural pests
Authors: Erdos Zoltan , Studholme David John , Raymond Ben , Sharma Manmohan
Published: March 2023

The entomopathogenic fungus Akanthomyces muscarius is commonly used in agriculture to manage insect pests. Besides its use as a commercially important biological control agent, it also presents a potential model for studying host-pathogen interactions and virulence evolution in a laboratory setting. Here, we describe the first high-quality genome sequence for A. muscarius. We used long- and short-read sequencing to assemble a sequence of 36.1 Mb with an N50 of 4.9 Mb. Genome annotation predicts 12,347 genes, with 96.6 % completeness based on the core Hypocrealen gene set (Benchmarking Universal Single-Copy Orthologs). The high-quality assembly and annotation of A. muscarius presented in this study provide an essential tool for future research on this commercially important species.
Epidemiology and genomic analysis of Shiga toxin-producing Escherichia coli clonal complex 165 in the UK
Authors: Rodwell Ella V. , Vishram Bhavita , Smith Robert , Browning Lynda , Smith-Palmer Alison , Allison Lesley , Holmes Anne , Godbole Gauri , McCarthy Noel , Dallman Timothy J. , Jenkins Claire
Published: March 2023

Introduction. Shiga toxin-producing

Escherichia coli

(STEC) is a zoonotic, foodborne gastrointestinal pathogen that has the potential to cause severe clinical outcomes, including haemolytic uraemic syndrome (HUS). STEC-HUS is the leading cause of renal failure in children and can be fatal. Over the last decade, STEC clonal complex 165 (CC165) has emerged as a cause of STEC-HUS.

Gap Statement. There is a need to understand the pathogenicity and prevalence of this emerging STEC clonal complex in the UK, to facilitate early diagnosis, improve clinical management, and prevent and control outbreaks.

Aim. The aim of this study was to characterize CC165 through identification of virulence factors (VFs) and antimicrobial resistance (AMR) determinants in the genome and to integrate the genome data with the available epidemiological data to better understand the incidence and pathogenicity of this clonal complex in the UK.

Methodology. All isolates belonging to CC165 in the archives at the UK public health agencies were sequenced and serotyped, and the virulence gene and AMR profiles were derived from the genome using PHE bioinformatics pipelines and the Centre for Genomic Epidemiology virulence database.

Results. There were 48 CC165 isolates, of which 43 were STEC, four were enteropathogenic

E. coli

(EPEC) and one

E. coli

. STEC serotypes were predominately O80:H2 (n=28), and other serotypes included O45:H2 (n=9), O55:H9 (n=4), O132:H2 (n=1) and O180:H2 (n=1). All but one STEC isolate had Shiga toxin (stx) subtype stx2a or stx2d and 47/48 isolates had the eae gene encoding intimin involved in the intimate attachment of the bacteria to the human gut mucosa. We detected extra-intestinal virulence genes including those associated with iron acquisition (iro) and serum resistance (iss), indicating that this pathogen has the potential to translocate to extra-intestinal sites. Unlike other STEC clonal complexes, a high proportion of isolates (93%, 40/43) were multidrug-resistant, including resistance to aminoglycosides, beta-lactams, chloramphenicol, sulphonamides, tetracyclines and trimethoprim.

Conclusion. The clinical significance of this clonal complex should not be underestimated. Exhibiting high levels of AMR and a combination of STEC and extra-intestinal pathogenic

E. coli

(ExPEC) virulence profiles, this clonal complex is an emerging threat to public health.
Association analyses of predicted loss-of-function variants prioritized 15 genes as blood pressure regulators
Authors: Lecluze Estelle , Lettre Guillaume
Published: March 2023

Background

Hypertension, clinically defined by elevated blood pressure (BP), is an important cause of mortality and morbidity worldwide. Many risk factors for hypertension are known, including a positive family history, which suggests that genetics contribute to inter-individual BP variation. Genome-wide association studies (GWAS) have identified >1000 loci associated with BP, yet the identity of the genes responsible for these associations remains largely unknown.

Methods

To pinpoint genes that causally impact BP variation in humans, we analyzed predicted loss-of-function (pLoF) variants in the UK Biobank whole-exome sequencing dataset (n=454,709 participants, 6% non-European ancestry). We analyzed genetic associations between systolic or diastolic BP (SBP/DBP) and single pLoF variants (additive and recessive genetic models) as well as with the burden of very rare pLoF variants (minor allele frequency [MAF] <0.01%).

Results

Single pLoF variants in ten genes associated with BP (ANKDD1B,ENPEP,PNCK, BTN3A2, C1orf145 [OBSCN-AS1],CASP9,DBH,KIAA1161 [MYORG],OR4X1, andTMC3). We also found a burden of rare pLoF variants in five additional genes associated with BP (TTN, NOS3, FES, SMAD6, COL21A1). Except forPNCK, which is located on the X-chromosome, these genes map near variants previously associated with BP by GWAS, validating the study of pLoF variants to prioritize causal genes at GWAS loci.

Conclusions

Our study highlights 15 genes that likely modulate BP in humans, including five genes that harbor pLoF variants associated with lower BP.
Mapping the dynamic genetic regulatory architecture ofHLAgenes at single-cell resolution
Authors: Kang Joyce B. , Shen Amber Z. , Sakaue Saori , Luo Yang , Gurajala Saisriram , Nathan Aparna , Rumker Laurie , Aguiar Vitor R. C. , Valencia Cristian , Lagattuta Kaitlyn , Zhang Fan , Jonsson Anna Helena , Yazar Seyhan , Alquicira-Hernandez Jose , Khalili Hamed , Ananthakrishnan Ashwin N. , Jagadeesh Karthik , Dey Kushal ,   Accelerating Medicines Partnership Program: Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE) Network, Daly Mark J. , Xavier Ramnik J. , Donlin Laura T. , Anolik Jennifer H. , Powell Joseph E. , Rao Deepak A. , Brenner Michael B. , Gutierrez-Arcelus Maria , Raychaudhuri Soumya
Published: March 2023

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation inHLAgenes has been extensively documented, regulatory genetic variation modulatingHLAexpression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classicalHLAgenes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specificcis-eQTLs for every classicalHLAgene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type.HLA-DQgenes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. DynamicHLAregulation may underlie important interindividual variability in immune responses.
Serum lipidome associates with neuroimaging features in patients with traumatic brain injury
Authors: Thomas Ilias , Newcombe Virginia F. J. , Dickens Alex M. , Richter Sophie , Posti Jussi P. , Maas Andrew I. R. , Tenovuo Olli , Hyötyläinen Tuulia , Büki András , Menon David K. , Orešič Matej ,   CENTER-TBI MR subgroup Participants and Investigators
Published: March 2023

Acute traumatic brain injury (TBI) is associated with substantial metabolic abnormalities, both centrally and in the periphery. We have previously reported extensive changes in the circulating metabolome resulting from TBI, including changes proportional to disease severity and associated with patient outcomes. The observed metabolome changes in TBI likely reflect several pathophysiological mechanisms supporting the concept that TBI is a systemic disease after the primary injury. However, one of the main metabolic changes we have observed following a TBI are changes in lipids, including the structural lipids that are known to be present in the myelin in the brain.

Here, we conducted a study to investigate the relationship between traumatic microstructural changes in white matter seen on magnetic resonance imaging (MRI) and quantitative lipidomic changes in the blood in a subset of patients with TBI recruited to the MRI sub-study of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study.

In total, there were 103 patients who had both a magnetic resonance imaging (MRI) scan and serum samples available for analysis. From serum, 201 known lipids were quantified. Diffusion tensor fitting generated fractional anisotropy (FA) and mean diffusivity (MD) maps for the MRI scans, in addition to volumetric data. Association matrices and partial correlation networks were built to elucidate the connections between the lipid groups and the maps.

We found that there are distinct directions of associations between the neuroimage data (FA and MD sets) and the concentrations of circulating lipids after injury. The FA and MD values were in inverse relationship with the severity of TBI (higher MD values, lower FA). We also observed that the lipid associations to FA and MD show different metabolic signatures. Lysophosphatidylcholines (LPC) associate mostly with FA while sphingomyelins (SM) associate with MD. Only phosphatidylcholines(PC) have strong associations with both as well as with the volumetric data. Finally, we found that the lipid changes are not associated with the number of regions with abnormalities.

In conclusion, we have identified groups of lipids which assocate with specific MRI imaging metrics following TBI. There appears to be consistent patterns of lipid changes associating with the specific microstructure changes in the CNS white matter. There is also a pattern of lipids with regional specficity, suggesting that blood-based lipidomics may provide an insight into the underlying disease mechanisms in TBI.
Evidence for a shared genetic contribution to loneliness and Borderline Personality Disorder
Authors: Schulze Anna , Streit Fabian , Zillich Lea , Awasthi Swapnil , Hall Alisha S M , Jungkunz Martin , Kleindienst Nikolaus , Frank Josef , Schwarze Cornelia E , Dahmen Norbert , Schott Björn H , Nöthen Markus , Mobascher Arian , Rujescu Dan , Lieb Klaus , Roepke Stefan , Herpertz Sabine C , Schmahl Christian , Bohus Martin , Ripke Stephan , Rietschel Marcella , Lis Stefanie , Witt Stephanie
Published: March 2023

Loneliness, influenced by genetic and environmental factors such as childhood maltreatment, is one aspect of interpersonal dysfunction in Borderline Personality Disorder (BPD). Numerous studies link loneliness and BPD and twin studies indicate a genetic contribution to this association. The aim of our study was to investigate whether genetic predisposition for loneliness and BPD risk overlap and whether genetic risk for loneliness contributes to higher loneliness reported by BPD patients, using genome-wide genotype data. We assessed the genetic correlation of genome-wide association studies (GWAS) of loneliness and BPD using linkage disequilibrium score regression and tested whether a polygenic score for loneliness (loneliness-PGS) was associated with case-control status in two independent genotyped samples of BPD patients and healthy controls (HC; Witt2017-sample: 998 BPD, 1545 HC; KFO-sample: 187 BPD, 261 HC). In the KFO-sample, we examined associations of loneliness-PGS with reported loneliness, and whether the loneliness-PGS influenced the association between childhood maltreatment and loneliness. We found a genetic correlation between the GWAS of loneliness and BPD in the Witt2017-sample (rg = .23,p= .015), a positive association of loneliness–PGS with BPD case-control status (Witt2017-sample: NkR² = 2.3%,p= 2.7*10-12; KFO-sample: NkR² = 6.6%,p= 4.4*10-6), and a positive association between loneliness-PGS and loneliness across patient and control groups in the KFO-sample (β= .185,p= .002). The loneliness-PGS did not moderate the association between childhood maltreatment and loneliness in BPD. Our study is the first to use genome-wide genotype data to show that the genetic factors underlying variation in loneliness in the general population and the risk for BPD overlap. The loneliness-PGS was associated with reported loneliness. Further research is needed to investigate which genetic mechanisms and pathways are involved in this association and whether a genetic predisposition for loneliness contributes to BPD risk.
Individual fixel-based white matter abnormalities in the epilepsies
Authors: Mito Remika , Pedersen Mangor , Pardoe Heath , Parker Donna , Smith Robert E. , Cameron Jillian , Scheffer Ingrid E. , Berkovic Samuel F. , Vaughan David N. , Jackson Graeme D.
Published: March 2023

Diffusion MRI has provided insight into the widespread structural connectivity changes that characterise the epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualised approach to a novel technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualised fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, Progressive Myoclonus Epilepsy, Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values computed within select tracts-of-interest. Scanner harmonised and normalised data were then used to compute Z-scores for individual patients with epilepsy. Microstructural white matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were largely in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g., hippocampal sclerosis, periventricular nodular heterotopia, bottom-of-sulcus dysplasia), microstructural abnormalities were concordant with lesion location. This study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localising structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study, so that individualised white matter changes can be explored robustly in larger cohorts in future work.
DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Accurate Protein-Ligand Interaction Prediction
Authors: Zhang Haiping , Saravanan Konda Mani , Zhang John Z.H.
Published: March 2023

The core of large-scale drug virtual screening is to accurately and efficiently select the binders with high affinity from large libraries of small molecules in which nonbinders are usually dominant. The protein pocket, ligand spatial information, and residue types/atom types play a pivotal role in binding affinity. Here we used the pocket residues or ligand atoms as nodes and constructed edges with the neighboring information to comprehensively represent the protein pocket or ligand information. Moreover, we find that the model with pre-trained molecular vectors performs better than the onehot representation. The main advantage of DeepBindGCN is that it is non-dependent on docking conformation and concisely keeps the spatial information and physical-chemical feature. Notably, the DeepBindGCN_BC has high precision in many DUD.E datasets, and DeepBindGCN_RG achieve a very low RMSE value in most DUD.E datasets. Using TIPE3 and PD-L1 dimer as proof-of-concept examples, we proposed a screening pipeline by integrating DeepBindGCN_BC, DeepBindGCN_RG, and other methods to identify strong binding affinity compounds. In addition, a DeepBindGCN_RG_x model has been used for comparing performance with other methods in PDBbind v.2016 and v.2013 core set. It is the first time that a non-complex dependent model achieves an RMSE value of 1.3843 and Pearson-R value of 0.7719 in the PDBbind v.2016 core set, showing comparable prediction power with the state-of-the-art affinity prediction models that rely upon the 3D complex. Our DeepBindGCN provides a powerful tool to predict the protein-ligand interaction and can be used in many important large-scale virtual screening application scenarios.
De novomutation rates in sticklebacks
Authors: Zhang Chaowei , Reid Kerry , Sands Arthur F. , Fraimout Antoine , Schierup Mikkel Heide , Merilä Juha
Published: March 2023

Mutation rate is a fundamental parameter in population genetics. Apart from being an important scaling parameter for demographic and phylogenetic inference, it allows one to understand at what rate new genetic diversity is generated and what is the expected level of genetic diversity in a population at equilibrium. However, except for well-established model organisms, accurate estimates ofde novomutation rates are available for a very limited number of organisms from the wild. We estimated mutation rates (µ) in two marine populations of the nine-spined stickleback (Pungitius pungitius) with the aid of several 2- and 3-generational family pedigrees, deep (>50×) whole genome re-sequencing and a high-quality reference genome. After stringent filtering, we discovered 295 germline mutations from 106 offspring translating toµ= 4.64 × 10−9andµ= 4.08 × 10−9per base, per generation, in the two populations, respectively. Twenty percent of the mutations were shared by full-sibs showing that the level of parental mosaicism was relatively high. Since the estimatedµwas 3.2 times smaller than the commonly used substitution rate, recalibration withµled to substantial increase in estimated divergence times between different stickleback species. Our estimates ofde novomutation rate should provide a useful resource for research focused on fish population genetics and that of sticklebacks in particular.
Mathematical Modeling of PCR with Variable Concentrations of DNA andTaqPolymerase
Authors: Ahmad Fraz , Zia Saeeda , Saif Rashid , Raza Muhammad Hassan
Published: March 2023

Polymerase Chain Reaction (PCR) is one of the important techniques in molecular biology for many diagnostics and research applications. In this current theoretical PCR optimization research, out of its seven recipe reagents, two of the important constituents e.g., DNA which might be very rare in forensic cases and polymerase enzyme due to its high cost were mathematically modeled and computationally simulated using MATLAB programming platform. Chemical equations of PCR stages were established using the law of mass action followed by differential equations derivations from each of the DNA amplification phases. Firstly, a mathematical model ofTaqpolymerase enzyme with its variable concentrations ranging from 0.05-0.35IU/μLwas formulated which showed the best PCR product of 0.61ng/μLobtained with 0.2IU/μLof polymerase. Similarly, by fixing the optimal polymerase concentration obtained in the previous simulation, the prime-DNA variable concentrations ranging from 0.5-3.5ng/μLwere further simulated which showed the best PCR product of 0.94ng/μLat 2.0ng/μLof DNA. PCR wet-lab experimentation and gel-electrophoresis visualization validated mathematically simulated optimized concentrations of the aforementioned two reagents which vary the PCR product considerably. Current findings indicate that mathematically optimized concentrations ofTaq-polymerase and template-DNA may reduce the PCR cost, time and energy, but other factors of target-sequence specificity, purity/concentrations of the other reagents, working hygiene, technical intricacies, biosafety and biosecurity factors may also contribute the desired yield of the amplicon.
Single-cell Electrochemical Aptasensor Array
Authors: Li Shuo , Coffinier Yannick , Lagadec Chann , Cleri Fabrizio , Nishiguchi Katsuhiko , Fujiwara Akira , Kim Soo Hyeon , Clément Nicolas
Published: March 2023

Despite several demonstrations of electrochemical devices with limits of detection (LOD) of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to the challenges of scaling up. In this study, we show that the recently introduced nanopillar array technology combined with redox-labelled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array, based on Brownian-fluctuating redox species, opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

For Table of Contents only
Neoepitope formation through the generation of RNA-derived “editopes”
Authors: Casati Beatrice , Pinamonti Veronica , Pecori Riccardo , Lindner John M. , Papavasiliou Fotini Nina
Published: March 2023

Treatment-resistant tumors are frequently characterized by a low tumor mutational burden (TMB) and poor T-cell infiltration into the tumor microenvironment. Conversely, good responses to immunotherapy have been associated with high TMB and T-cell infiltration. This may imply that at least a subset of mutations in TMB-high tumors result in the generation of neoepitopes that are recognized (and cleared) by T cells. Currently, methods that specifically mutate MHC-presented tumor epitopes, while preserving genomic integrity, do not exist. Here, we have employed site-directed RNA editing to specifically alter MHC-presented tumor epitopes at the transcript level, with no modification to the genomic DNA, to modulate their antigenicity and recognition by cognate T-cell receptors (TCR). We demonstrate that RNA editing can be employed as a precision tool to specifically modulate antigenicity through the formation of RNA editing derived neoepitopes, which we have termed “editopes”. In particular, we show potent induction of a T-cell response to an optimally edited peptide (40%) compared to a non-immunogenic mutant peptide (<2%) and its WT counterpart (20%). This study shows the potential of RNA editing as a method to improve tumor recognition by T cells and to favor tumor clearance.
REAL-TIME AT-LINE MONITORING OF INFLUENZA VIRUS IN CELL CULTURE BY A SURFACE PLASMON RESONANCE BIOSENSOR
Authors: Durous Laurent , Padey Blandine , Traversier Aurélien , Chupin Caroline , Julien Thomas , Blum Loïc J. , Marquette Christophe A. , Rosa-Calatrava Manuel , Petiot Emma
Published: March 2023

Since the early 2000’, regulation agencies have encouraged viral vaccine manufacturers to implement in-process and real-time monitoring tools in production processes. Even if more assays have been recently developed, none of the novel viral particle quantification technologies can monitor virus levels and their secretion kinetics within production vessels. Vaccine manufacturers still rely on offline cell-based infectivity assays and antigen amount quantification to monitor their processes. The present study describes the development of the first automated biosensor for at-line monitoring of influenza virus production. It involves coupling a fetuin-based SPRi quantitative biosensor with an automated sampler of culture broth and a consecutive clarification setup via an acoustic filter. The SPRi response of different viral strains produced in two distinct cell production platforms was qualified. We demonstrated that fetuin-based quantitative SPRi is a robust, potency-indicating, and universal analytical technology for quantifying bioactive influenza virus particles. It was validated with both purified and complex matrices. Finally, an influenza viral production kinetic was monitoredonlinefor three days. This novel online tool enabled the access in real-time to total bioactive viral particles from early production phases (8hpi).
Chemodiversity affects preference forTanacetum vulgarechemotypes in two aphid species
Authors: Neuhaus-Harr Annika , Ojeda-Prieto Lina , Eilers Elisabeth , Müller Caroline , Weisser Wolfgang W. , Heinen Robin
Published: March 2023

Plants of the same species often strongly differ in morphological traits, as well as in the abundance and composition of specialized metabolite profiles. Specialized metabolites can act as mediators of interactions on plants, and affect insect presence and abundance in the field. However, how specialized chemistry shapes plant attractiveness to herbivorous insects is not fully understood. Here we used common tansy (Tanacetum vulgareL., Asteraceae) – a perennial plant that is highly diverse in terpenoid composition and is known to have variable chemotypes – to test whether 1) plants with different chemotype profiles differ in attractiveness to two specialized aphids,Macrosiphoniella tanacetariaandUroleucon tanaceti, in pairwise choice assays. Furthermore, we tested whether 2) the diversity of the terpenoid blend affects aphid attractiveness. Lastly, we tested how 3) plant chemical traits relate to plant morphological traits, and which best explain aphid preference. We found thatM. tanacetariapreferred two out of five chemotypes, dominated by α-thujone/β-thujone and β-trans-chrysanthenyl acetate, respectively, while avoiding a chemotype dominated by α-pinene/sabinene.U. tanacetishowed no clear preference towards chemotypes, but when given the choice between chemotypes dominated by α-thujone/β-thujone and by α-pinene/sabinene, they preferred the former. Importantly, plant attractiveness to aphids tended to be negatively correlated with chemodiversity, i.e., the number of terpenoid compounds, inM. tanacetaria, but not inU. tanaceti. Interestingly, the approximate concentration and number of terpenoid compounds was generally higher in larger and bushier plants. Hence, we did not observe a trade-off between plant growth and defence. We conclude that plant chemical composition affects plant attractiveness to aphids and hence may contribute to variation in natural aphid colonization patterns on plants of the same species.
Stability and heterogeneity in the anti-microbiota reactivity of human milk-derived Immunoglobulin A
Authors: Johnson-Hence Chelseá B. , Gopalakrishna Kathyayini P. , Bodkin Darren , Coffey Kara E. , Burr Ansen H.P. , Rahman Syed , Rai Ali T. , Abbott Darryl A. , Sosa Yelissa A. , Tometich Justin T. , Das Jishnu , Hand Timothy W.
Published: March 2023

Immunoglobulin A (IgA) is secreted into breast milk and is critical to both protecting against enteric pathogens and shaping the infant intestinal microbiota. The efficacy of breast milk-derived maternal IgA (BrmIgA) is dependent upon its specificity, however heterogeneity in BrmIgA binding ability to the infant microbiota is not known. Using a flow cytometric array, we analyzed the reactivity of BrmIgA against bacteria common to the infant microbiota and discovered substantial heterogeneity between all donors, independent of preterm or term delivery. We also observed intra-donor variability in the BrmIgA response to closely related bacterial isolates. Conversely, longitudinal analysis showed that the anti-bacterial BrmIgA reactivity was relatively stable through time, even between sequential infants, indicating that mammary gland IgA responses are durable. Together, our study demonstrates that the anti-bacterial BrmIgA reactivity displays inter-individual heterogeneity but intra-individual stability. These findings have important implications for how breast milk shapes the development of the infant microbiota and protects against Necrotizing Enterocolitis.

We analyze the ability of breast milk-derived Immunoglobulin A (IgA) antibodies to bind the infant intestinal microbiota. We discover that each mother secretes into their breast milk a distinct set of IgA antibodies that are stably maintained over time.
VariPred: Enhancing Pathogenicity Prediction of Missense Variants Using Protein Language Models
Authors: Lin Weining , Wells Jude , Wang Zeyuan , Orengo Christine , Martin Andrew C.R.
Published: March 2023

Computational approaches for predicting the pathogenicity of genetic variants have advanced in recent years. These methods enable researchers to determine the possible clinical impact of rare and novel variants. Historically these prediction methods used hand-crafted features based on structural, evolutionary, or physiochemical properties of the variant. In this study we propose a novel framework that leverages the power of pre-trained protein language models to predict variant pathogenicity. We show that our approach VariPred (VariantimpactPredictor) outperforms current state-of-the-art methods by using an end-to-end model that only requires the protein sequence as input. By exploiting one of the best performing protein language models (ESM-1b), we established a robust classifier, VariPred, requiring no pre-calculation of structural features or multiple sequence alignments. We compared the performance of VariPred with other representative models including 3Cnet, EVE and ‘ESM variant’. VariPred outperformed all these methods on the ClinVar dataset achieving an MCC of 0.751vs. an MCC of 0.690 for the next closest predictor.
mosnareveals different types of cellular interactions predictive of response to immunotherapies and survival in cancer
Authors: Coullomb Alexis , Monsarrat Paul , Pancaldi Vera
Published: March 2023

Spatially resolved omics enable the discovery of tissue organization of biological or clinical importance. Despite the existence of several methods, performing a rational analysis including multiple algorithms while integrating different conditions such as clinical data is still not trivial. To make such investigations more accessible, we developedmosna, a Python package to analyze spatial omics data with respect to clinical or biological data and to gain insight on cell interaction patterns or tissue architecture of biological relevance.mosnais compatible with all spatial omics methods, it leveragestysserandto build accurate spatial networks, and is compatible with Squidpy. It proposes an analysis pipeline, in which increasingly complex features computed at each step can be explored in integration with clinical data, either with easy-to-use descriptive statistics and data visualization, or by seamlessly training machine learning models and identifying variables with the most predictive power.

mosnacan take as input any dataset produced by spatial omics methods, including sub-cellular resolved transcriptomics (MERFISH, seqFISH) and proteomics (CODEX, MIBI-TOF, low-plex immuno-fluorescence), as well as spot-based spatial transcriptomics (10x Visium). Integration with experimental metadata or clinical data is adapted to binary conditions, such as biological treatments or response status of patients, and to survival data. We demonstrate the proposed analysis pipeline on two spatially resolved proteomic datasets containing either binary response to immunotherapy or survival data. mosna identifies features describing cellular composition and spatial distribution that can provide biological insight regarding factors that affect response to immunotherapies or survival.

Availability and implementation

mosnais made publicly available to the community, together with relevant documentation and tutorials implemented as Jupyter notebooks to reproduce the result athttps://github.com/AlexCoul/mosna
Cell-Cell Separation Device: measurement of intercellular detachment forces
Authors: Eckert Julia , Matylitskaya Volha , Kasemann Stephan , Partel Stefan , Schmidt Thomas
Published: March 2023

Whether at the intramolecular or cellular scale in organisms, cell-cell adhesion adapt to external mechanical cues arising from the static environment of cells and from dynamic interactions between neighboring cells. Cell-cell adhesions need to resist detachment forces to secure the integrity and internal organization of organisms. In the past, various techniques have been developed to characterize adhesion properties of molecules and cellsin vitro,and to understand how cells sense and probe their environment. Atomic force microscopy and dual-pipette aspiration, where cells are mainly present in suspension, are common methods for studying detachment forces of cell-cell adhesions. How cell-cell adhesion forces are developed for adherent and environment-adapted cells, however, is less clear. Here, we designed the Cell-Cell Separation Device (CC-SD), a microstructured substrate that measures both intercellular forces and external stresses of cells towards the matrix. The design is based on micropillar arrays originally designed for cell traction-force measurements. We designed PDMS micropillar-blocks, to which cells could adhere and be able to connect to each other across the gap. Controlled stretching of the whole substrate changed the distance between blocks and increased gap size. That allowed us to apply strains to cell-cell contacts, eventually leading to cell-cell adhesion detachment, which was measured by pillar deflections. The CC-SD provided an increase of the gap between the blocks of up to 2.4-fold, which was sufficient to separate substrate-attached cells with fully developed F-actin network. Simultaneously measured pillar deflections allowed us to address cellular response to the intercellular strain applied. The CC-SD thus opens up possibilities for the analysis of intercellular force detachments and sheds light on the robustness of cell-cell adhesions in dynamic processes in tissue development.
Reconstructing the first COVID-19 pandemic wave with minimal data in the UK
Authors: Chen Siyu , Flegg Jennifer A , Lythgoe Katrina A , White Lisa J
Published: March 2023

Accurate measurement of exposure to SARS-CoV-2 in the population is crucial for understanding the dynamics of disease transmission and evaluating the impacts of interventions. However, it is particularly challenging to achieve this in the early phase of a pandemic because of the sparsity of epidemiological data. In our previous publication[1], we developed an early pandemic diagnostic tool that can link minimum datasets: seroprevalence, mortality and infection testing data to estimate the true exposure in different regions of England and found levels of SARS-CoV-2 population exposure are considerably higher than suggested by seroprevalence surveys. Here, we re-examined and evaluated the model in the context of reconstructing the first COVID-19 epidemic wave in England from three perspectives: validation from ONS Coronavirus Infection Survey, relationship between model performance and data abundance and time-varying case detection rate. We found that our model can recover the first but unobserved epidemic wave of COVID-19 in England from March 2020 to June 2020 as long as two or three serological measurements are given as model inputs additionally, with the second wave during winter of 2020 validated by the estimates from ONS Coronavirus Infection Survey. Moreover, the model estimated that by the end of October in 2020 the UK government’s official COVID-9 online dashboard reported COVID-19 cases only accounted for 9.1% (95%CrI (8.7%,9.8%)) of cumulative exposure, dramatically varying across two epidemic waves in England in 2020 (4.3% (95%CrI (4.1%, 4.6%)) vs 43.7% (95%CrI (40.7%, 47.3%))).
Novel Tools for Lassa Virus Surveillance in Peri-domestic Rodents
Authors: Smither Allison R. , Koninga James , Kanneh Franklyn B. , Foday Momoh , Boisen Matthew L. , Bond Nell G. , Momoh Mambu , Demby Sandi John , Kanneh Lansana , Alhasan Foday , Mustapha Kanneh Ibrahim , Yillah Mohamed S. , Grant Donald S. , Bush Duane J. , Nelson Diana K. S. , Cruz Kaitlin M. , Klitting Raphaëlle , Pauthner Matthias , Andersen Kristian G. , Shaffer Jeffrey G. , Cross Robert W. , Schieffelin John S. , Garry Robert F.
Published: March 2023

Background

Lassa fever (LF) is a rodent-borne disease endemic to West Africa. In the absence of licensed therapeutics or vaccines, rodent exclusion from living spaces remains the primary method of preventing LF. Zoonotic surveillance of Lassa virus (LASV), the etiologic agent of LF, can assess the burden of LASV in a region and guide public health measures against LF.

Methods

In this study, we adapted commercially available LASV human diagnostics to assess the prevalence of LASV in peri-domestic rodents in Eastern Sierra Leone. Small mammal trapping was conducted in Kenema district, Sierra Leone between November 2018-July 2019. LASV antigen was detected using a commercially available LASV NP antigen rapid diagnostic test. LASV IgG antibodies against LASV nucleoprotein (NP) and glycoprotein (GP) were tested by adapting a commercially available semi-quantitative enzyme linked immunosorbent assay (ELISA) for detection of mouse-related and rat-related species IgG.

Findings

Of the 373 tested specimens, 74 (20%) tested positive for LASV antigen. 40 (11%) specimens tested positive for LASV NP IgG, while an additional 12 (3%) specimens only tested positive for LASV GP IgG. Simultaneous antigen presence and IgG antibody presence was linked inMastomys sp. specimens (p< 0.01), but notRattus sp. specimens (p= 1). Despite the link between antigen presence and IgG antibody presence inMastomys sp., the strength of antigen response did not correlate with the strength of IgG response to either GP IgG or NP IgG.

Interpretation

The tools developed in this study can aid in the generation of valuable public health data for rapid field assessment of LASV burden during outbreak investigations and general LASV surveillance.

Funding

Funding for this work was supported by the National Institute of Allergy and Infectious Diseases National Institute of Health, Department of Health and Human Services under the following grants: International Collaboration in Infectious Disease Research on Lassa fever and Ebola - ICIDR - U19 AI115589, Consortium for Viral Systems Biology - CViSB - 5U19AI135995, West African Emerging Infectious Disease Research Center - WARN-ID - U01AI151812, West African Center for Emerging Infectious Diseases: U01AI151801.
Developing a blood cell-based diagnostic test for myalgic encephalomyelitis/chronic fatigue syndrome using peripheral blood mononuclear cells
Authors: Xu Jiabao , Lodge Tiffany , Kingdon Caroline , Strong James W L , Maclennan John , Lacerda Eliana , Kujawski Slawomir , Zalewski Pawel , Huang Wei E. , Morten Karl J.
Published: March 2023

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by debilitating fatigue that profoundly impacts patients’ lives. Diagnosis of ME/CFS remains challenging, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis, and many never receiving a clear diagnosis at all. In this study, we utilized a single-cell Raman platform and artificial intelligence to analyze blood cells from 98 human subjects, including 61 ME/CFS patients of varying disease severity and 37 healthy and disease controls. Our results demonstrate that Raman profiles of blood cells can distinguish between healthy individuals, disease controls, and ME/CFS patients with high accuracy (91%), and can further differentiate between mild, moderate, and severe ME/CFS patients (84%). Additionally, we identified specific Raman peaks that correlate with ME/CFS phenotypes and have the potential to provide insights into biological changes and support the development of new therapeutics. This study presents a promising approach for aiding in the diagnosis and management of ME/CFS, and could be extended to other unexplained chronic diseases such as long COVID and post-treatment Lyme disease syndrome, which share many of the same symptoms as ME/CFS.
Costs of digital adherence technologies for tuberculosis treatment support
Authors: Nsengiyumva Ntwali Placide , Khan Amera , Gler Maricelle Ma. Tarcela S. , Lopez Mariceif , Marcelo Danaida , Andrews Mark C. , Duverger Karine , Ahmed Shahriar , Ibrahim Tasmia , Morales Mona Lisa , Villanueva Andre , Efo Egwumo , Onajare Baraka , Celan Cristina , Schwartzman Kevin
Published: March 2023

Digital adherence technologies (DATs) are increasingly used for tuberculosis (TB) adherence support, but information about their costs remains limited. We used microcosting to estimate health system costs (in 2022 US dollars) of 99DOTS pill sleeves and video-observed treatment (VOT), implemented in demonstration projects during 2018-21. Local cost estimates for standard directly observed treatment (DOT) were also obtained. The estimated per-person costs of 99DOTS for drug-sensitive (DS-) TB were $98, $106, and $174 in Bangladesh (n=719), the Philippines (n=396), and Tanzania (n=976) respectively. The estimated per-person costs of VOT were $1 154, $304, $457, and $661 in Haiti (n=87 DS-TB), Moldova (n=173 DS-TB), Moldova (n=135 drug-resistant [DR]-TB) and the Philippines (n=110 DR-TB) respectively. Health system costs of 99DOTS may be similar to or cheaper than standard DOT. VOT is considerably more expensive; labor cost offsets and/or economies of scale may yield savings relative to standard DOT in some settings.

In diverse settings, health system costs of 99DOTS pill sleeves may be similar to or cheaper than standard directly observed treatment for TB; video-observed treatment is considerably more expensive, but labor cost offsets and/or economies of scale may yield savings.
Schwann cells modulate nociception in neurofibromatosis 1
Authors: Raut Namrata G.R. , Maile Laura A. , Oswalt Leila M. , Mitxelena Irati , Adlakha Aaditya , Sprague Kourtney L. , Rupert Ashley R. , Bokros Lane , Hofmann Megan C. , Patritti-Cram Jennifer , Rizvi Tilat A. , Queme Luis F. , Choi Kwangmin , Ratner Nancy , Jankowski Michael P.
Published: March 2023

Pain of unknown etiology is frequent in individuals with the tumor predisposition syndrome Neurofibromatosis 1 (NF1), even when tumors are absent. Schwann cells (SC) were recently shown to play roles in nociceptive processing, and we find that chemogenetic activation of SCs is sufficient to induce afferent and behavioral mechanical hypersensitivity in mice. In mouse models, animals show afferent and behavioral hypersensitivity when SC, but not neurons, lackNf1. Importantly, hypersensitivity corresponds with SC-specific upregulation of mRNA encoding glial cell line derived neurotrophic factor (GDNF), independent of the presence of tumors. Neuropathic pain-like behaviors in the NF1 mice were inhibited by either chemogenetic silencing of SC calcium or by systemic delivery of GDNF targeting antibodies. Together, these findings suggest that Nf1 loss in SCs causes mechanical pain by influencing adjacent neurons and, data may identify cell-specific treatment strategies to ameliorate pain in individuals with NF1.

Graphical Abstract

GDNF released from Schwann cells acts on sensory neurons leading to mechanical hypersensitivity and pain-like behaviors in preclinical models of NF1.
Protein-intrinsic properties and context-dependent effects regulate pioneer-factor binding and function
Authors: Gibson Tyler J. , Harrison Melissa M.
Published: March 2023

Chromatin is a barrier to the binding of many transcription factors. By contrast, pioneer factors access nucleosomal targets and promote chromatin opening. Despite binding to target motifs in closed chromatin, many pioneer factors display cell-type specific binding and activity. The mechanisms governing pioneer-factor occupancy and the relationship between chromatin occupancy and opening remain unclear. We studied threeDrosophilatranscription factors with distinct DNA-binding domains and biological functions: Zelda, Grainy head, and Twist. We demonstrated that the level of chromatin occupancy is a key determinant of pioneering activity. Multiple factors regulate occupancy, including motif content, local chromatin, and protein concentration. Regions outside the DNA-binding domain are required for binding and chromatin opening. Our results show that pioneering activity is not a binary feature intrinsic to a protein but occurs on a spectrum and is regulated by a variety of protein-intrinsic and cell-type-specific features.
Eliciting and prioritising determinants of improved care in Multiple Long Term Health Conditions (MLTC): A modified online Delphi study
Authors: Simpson Glenn , Stuart Beth , Hijryana Marisza , Akyea Ralph Kwame , Stokes Jonathan , Gibson Jon , Jones Karen , Morrison Leanne , Santer Miriam , Boniface Michael , Zlatev Zlatko , Farmer Andrew , Dambha-Miller Hajira
Published: March 2023

Introduction

Multiple Long Term Conditions (MLTC) are a major challenge to health and social care systems around the world. There is limited research exploring the wider contextual determinants that are important to improving care for people living with MLTC. In this study, we aimed to elicit and prioritise determinants of improved care in people with MLTC.

Methods

A three round online Delphi study was conducted in England with health and social care professionals, data scientists, researchers, people living with MLTC and their carers.

Results

Our findings suggest a care system which is still predominantly single condition focused. ‘Person-centred and holistic care’ and ‘coordinated and joined up care’, were highly rated determinants in relation to improved care for MLTC. We further identified a number of non-medical determinants that are important to providing holistic care for MLTC.

Conclusions

Further progress towards a holistic and patient centred model is needed to ensure that care more effectively addresses the complex range of medical and non-medical needs of people living with MLTC. This requires a move from a single condition focused biomedical model to a person-based biopsychosocial approach, which has yet to be achieved.