bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of key factors of a SARS-CoV-2 vaccination program: A mathematical modeling approach
Authors: Martínez-Rodríguez David , Gonzalez-Parra Gilberto , Villanueva-Micó Rafael-J.
Published: February 2021

The administration of vaccines against the coronavirus disease 2019 (COVID-19) just started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination programs in different regions may vary due to differences in implementation, for instance, simply the availability of the vaccine. In this article, we study the impact of the pace of vaccination and the intrinsic efficacy of the vaccine on prevalence, hospitalizations, and deaths related to the SARS-CoV-2 virus. Then we study different potential future scenarios regarding the burden of the COVID-19 pandemic in the near future. We construct a compartmental mathematical model and use computational methodologies to study these different scenarios. Thus, we are able identify some key factors to reach the aims of the vaccination programs. We use some metrics related to the outcomes of the COVID-19 pandemic in order to assess the impact of the efficacy of the vaccine and the pace of the vaccine inoculation. We found that both factors have a high impact on the outcomes. However, the rate of vaccine administration has a higher impact in reducing the burden of the COVID-19 pandemic. This result shows that health institutions need to focus in increasing the vaccine inoculation pace and create awareness in the population about the importance of COVID-19 vaccines.
CIITA G-286A promoter polymorphism impairs monocytes HLA-DR expression in septic shock and is rescued by interferon-γ
Authors: Miatello Jordi , Lukaszewicz Anne-Claire , Faivre Valérie , Hua Stéphane , Martinet Kim Zita , Bourgeois Christine , Quintana-Murci Lluis , Payen Didier , Boniotto Michele , Tissières Pierre
Published: February 2021

Monocyte HLA-DR is an increasingly recognized markers of sepsis-induced immunodepression, but its regulatory mechanisms remain poorly understood in sepsis. Several evidence for positive selection on the 5’ promoter region of HLA class II transactivator (CIITA) gene, the master regulator of MHC class II, have been gathered in the European population, and its role in sepsis has never been demonstrated, whilst suggested in autoimmune disease. We aim to describe the effect of rs3087456 polymorphism, localized on CIITA promoter III (pIII), on mortality of patients with septic shock, and investigate the mechanisms regulating HLA-DR expression. Genotyping of 203 patients with septic shock showed that, in A dominant model, GG genotype was associated with 28-day mortality (OR 2.29; 95%CI: 1.01 to 5.22; P = 0.043). Monocyte HLA-DR remained low in patients with GG genotype whereas it increases as early as at the end of the first week in intensive care in patients with AA or AG genotype. Using site-directed mutagenesis, in vitro reporter gene promoter activity of the pIII was decreased in GG genotype in monocyte cell line. Interferon-γ (IFN-γ) restored pIII activity in GG genotype as well as restore, in ex vivo experiment in healthy volunteers, CIITA pIII expression of GG genotype. Hereby, we demonstrated that rs3087456, a positively selected polymorphism of CIITA proximal promoter, significantly impact monocyte HLA-DR expression in patients with septic shock through CIITA promoter activity, that can be rescued using IFN-γ, offering a new perspective in genetic susceptibility to sepsis and targeted immunomodulatory therapy.

Keypoints

CIITA G-286A polymorphism reduces promotor activity and significantly impact monocyte HLA-DR expression and mortality in septic shock

Downregulatory effects of CIITA G-286A polymorphism on monocyte HLA-DR expression can be reverse by IFN-γ in patients with septic shock
SARS-CoV-2 disinfection in aqueous solution by UV222 from a krypton chlorine excilamp
Authors: Robinson Richard T. , Mahfooz Najmus , Rosas-Mejia Oscar , Liu Yijing , Hull Natalie M.
Published: February 2021

There is an urgent need for evidence-based development and implementation of engineering controls to reduce transmission of SARS-CoV-2, the etiological agent of COVID-19. Ultraviolet (UV) light can inactivate coronaviruses, but the practicality of UV light as an engineering control in public spaces is limited by the hazardous nature of conventional UV lamps, which are Mercury (Hg)-based and emit a peak wavelength (254 nm) that penetrates human skin and is carcinogenic. Recent advances in the development and production of Krypton Chlorine (KrCl) excimer lamps hold promise in this regard, as these emit a shorter peak wavelength (222 nm) and are recently being produced to filter out emission above 240 nm. However, the disinfection kinetics of KrCl UV excimer lamps against SARS-CoV-2 are unknown. Here we provide the first dose response report for SARS-CoV-2 exposed to a commercial filtered KrCl excimer light source emitting primarily 222 nm UV light (UV222), using multiple assays of SARS-CoV-2 viability. Plaque infectivity assays demonstrate the pseudo-first order rate constant of SARS-CoV-2 reduction of infectivity to host cells to be 0.64 cm2/mJ (R2 = 0.95), which equates to a D90 (dose for 1 log10 or 90% inactivation) of 1.6 mJ/cm2. Through RT-qPCR assays targeting the nucleocapsid (N) gene with a short (<100 bp) and long (∼1000 bp) amplicon in samples immediately after UV222 exposure, the reduction of ability to amplify indicated an approximately 10% contribution of N gene damage to disinfection kinetics. Through ELISA assay targeting the N protein in samples immediately after UV222 exposure, we found no dose response of the ability to damage the N protein. In both qPCR assays and the ELISA assay of viral outgrowth supernatants collected 3 days after incubation of untreated and UV222 treated SARS-CoV-2, molecular damage rate constants were similar, but lower than disinfection rate constants. These data provide quantitative evidence for UV222 doses required to disinfect SARS-CoV-2 in aqueous solution that can be used to develop further understanding of disinfection in air, and to inform decisions about implementing UV222 for preventing transmission of COVID19.

ABSTRACT ART / TOC GRAPHIC
Nosocomial outbreak of SARS-CoV-2 in a “non-COVID-19” hospital ward: virus genome sequencing as a key tool to understand cryptic transmission
Authors: Borges Vítor , Isidro Joana , Macedo Filipe , Neves José , Silva Luís , Paiva Mário , Barata José , Catarino Judite , Ciobanu Liliana , Duarte Sílvia , Vieira Luís , Guiomar Raquel , Gomes João Paulo
Published: February 2021

Background

Dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare institutions affects both patients and health-care workers (HCW), as well as the institutional capacity to provide essential health services.

Methods

We conducted an investigation of a cluster of SARS-CoV-2 positive cases detected in a “non-COVID-19” hospital ward during Summer 2020. The magnitude of the nosocomial outbreak was disclosed by massive testing, challenging the retrospective reconstruction of the introduction and transmission events. An in-depth contact tracing investigation was carried out to identify the contacts network during the 15-day period before the screening. In parallel, positive SARS-CoV-2 RNA samples were subjected to virus genome sequencing.

Results

Of the 245 tested individuals, 48 (21 patients and 27 HCWs) tested positive for SARS-CoV-2. HCWs were mostly asymptomatic, but the mortality among the vulnerable patient group reached 57.1% (12/21). Phylogenetic reconstruction revealed that all cases were part of the same transmission chain, thus confirming a single origin behind this nosocomial outbreak. By combining vast epidemiological and genomic data, including analysis of emerging minor variants, we unveiled a scenario of silent SARS-CoV-2 dissemination within the hospital ward, mostly driven by the close contact within the HCWs group and between HCWs and patients. This investigation triggered enhanced prevention and control measures, leading to a more timely detection and containment of novel nosocomial outbreaks.

Conclusions

The present study shows the benefit of combining genomic and epidemiological data for the investigation of complex nosocomial outbreaks, and provides valuable data to minimize the risk of transmission of COVID-19 in healthcare facilities.

Short summary

SARS-CoV-2 nosocomial outbreaks are of utmost public health concern. Here, we performed an in-depth investigation of a high-fatality rate nosocomial outbreak by combining vast genomic and epidemiological data, providing valuable information to understand cryptic transmission of SARS-CoV-2 within healthcare institutions.
Prediction of type 1 diabetes at birth: cord blood metabolites versus genetic risk score in the MoBa cohort
Authors: Tapia German , Suvitaival Tommi , Ahonen Linda , Lund-Blix Nicolai A. , R. Njølstad Pål , Joner Geir , Skrivarhaug Torild , Legido-Quigley Cristina , Størdal Ketil , Stene Lars C.
Published: February 2021

Background and aim

Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes.

Methods

Using a targeted UHPLC-QQQ-MS platform, we quantified 27 low molecular weight metabolites (including amino acids, small organic acids and bile acids) in 166 children, who later developed type 1 diabetes, and 177 random control children in the Norwegian Mother, Father and Child (MoBa) cohort. We analysed the data using logistic regression (estimating odds ratios per standard deviation [aOR]), area under the receiver operating characteristic curve (AUC) and k-means clustering. Metabolites were compared to a genetic risk score based on 51 established non-HLA SNPs, and a four-category HLA risk group.

Results

The strongest associations for metabolites were aminoadipic acid (aOR=1.23,95%CI:0.97–1.55), indoxyl sulfate (aOR=1.15,95%CI:0.87–1.51), and tryptophan (aOR=0.84,95%CI:0.65–1.10), with other aORs close to 1.0, and none significantly associated with type 1 diabetes. K-means clustering identified six clusters, none of which were associated with type 1 diabetes. Cross-validated AUC showed no predictive value of metabolites (AUC 0.49), while the non-HLA genetic risk score AUC was 0.56 and the HLA risk group AUC was 0.78.

Conclusions

In this large study, we found no support of a predictive role of cord blood concentrations of selected bile acids and other small polar metabolites in the development of type 1 diabetes.

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Predicting childhood type 1 diabetes with cord blood biomarkers: genetic risk score works but metabolites do not

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THE ASSOCIATION OF OPENING K-12 SCHOOLS WITH THE SPREAD OF COVID-19 IN THE UNITED STATES: COUNTY-LEVEL PANEL DATA ANALYSIS
Authors: Chernozhukov Victor , Kasahara Hiroyuki , Schrimpf Paul
Published: February 2021

Abstract

This paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using data on foot traffic and K-12 school opening plans, we analyze how an increase in visits to schools and opening schools with different teaching methods (in-person, hybrid, and remote) is related to the 2-weeks forward growth rate of confirmed COVID-19 cases. Our debiased panel data regression analysis with a set of county dummies, interactions of state and week dummies, and other controls shows that an increase in visits to both K-12 schools and colleges is associated with a subsequent increase in case growth rates. The estimates indicate that fully opening K-12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the positive association of K-12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These results have a causal interpretation in a structural model with unobserved county and time confounders. Sensitivity analysis shows that the baseline results are robust to timing assumptions and alternative specifications.
Self-testing for the detection of SARS-CoV-2 infection with rapid antigen tests
Authors: Stohr J. J.J.M. , Zwart V. F. , Goderski G. , Meijer A. , Nagel-Imming C. R.S. , Kluytmans-van den Bergh M.F.Q. , Pas S. D. , van den Oetelaar F. , Hellwich M. , Gan K. H. , Rietveld A. , Verweij J.J. , Murk J. L. , van den Bijllaardt W. , Kluytmans J. A. J. W.
Published: February 2021

Introduction

Self-testing for COVID-19 infection with lateral flow assay SARS-CoV-2 rapid antigen detection tests (RDT), provides rapid results and could enable frequent and extensive testing in the community, thereby improving the control of SARS-CoV-2. The objective of this study is to evaluate the performance of self-testing using RDT without assistance.

Methods

Participants visiting a municipal SARS-CoV-2 testing centre, received self-testing kits containing either the BD Veritor System (BD RDT) or Roche SARS-CoV-2 antigen detection test (Roche RDT). Oro-nasopharyngeal swabs were collected from the participants for qRT-PCR testing. As a proxy for contagiousness, viral culture was performed on a selection of qRT-PCR positive samples to determine the Ct-value at which the chance of a positive culture was dropping below 0.5 (Ct-value cut-off). Sensitivity and specificity of self-testing were compared to qRT-PCR with a Ct-value below the Ct value cut-off. Determinants independently associated with a false-negative self-test result were determined.

Results

A total of 3,215 participants were included (BD RDT n=1604; Roche RDT n=1611). Sensitivity and specificity of self-testing compared to the qRT-PCR results with Ct-value below the Ct-value cut-off was 78.0% (95% CI:72.5-82.8) and 99.4% (95%CI: 99.0-99.6) respectively. Determinants independently associated with a false-negative self-testing results were: higher age, low viral load and finding self-testing difficult.

Discussion

Self-testing using currently available RDT’s has a high specificity and relatively high sensitivity to identify individuals with a high probability of contagiousness. The performance of two tests were comparable. This application has the potential for frequent and extensive testing which may be an aid to lift restrictions to society while controlling the spread of SARS-CoV-2.
The spatio-temporal distribution of COVID-19 infection in England between January and June 2020
Authors: Elson Richard , Davies Tilman M. , Lake Iain R. , Vivancos Roberto , Blomquist Paula B. , Charlett Andre , Dabrera Gavin
Published: February 2021

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.

A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.

Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rdMarch 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.

In terms of controlling transmission, the most important practical application is the accurate identification of areaswithinregions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.
Prognostic value and peripheral immunologic correlates of early FDG PET response imaging in a phase II trial of risk-adaptive chemoradiation for unresectable non-small cell lung cancer
Authors: Bowen Stephen R. , Hippe Daniel S. , Thomas Hannah M. , Sasidharan Balukrishna , Lampe Paul D. , Baik Christina S. , Eaton Keith D. , Lee Sylvia , Martins Renato G. , Santana-Davila Rafael , Chen Delphine , Kinahan Paul E. , Miyaoka Robert S. , Vesselle Hubert J. , Houghton A. McGarry , Rengan Ramesh , Zeng Jing
Published: February 2021

Introduction

We hypothesized that FDG PET imaging during chemoradiation for unresectable non-small cell lung cancer (NSCLC) is prognostic for survival, and that tumor PET response is correlated with peripheral T-cell function.

Methods

45 patients with AJCCv7 stage IIB-IIIB NSCLC enrolled on the phase II FLARE-RT trial and received platinum-doublet chemotherapy concurrent with 6 weeks of radiation (NCT02773238). FDG PET imaging was performed prior to treatment start and after 24 Gy of radiation (week 3). PET response status was prospectively defined by multifactorial radiologic interpretation. PET responders received 60 Gy in 30 fractions, while non-responders received concomitant boosts to 74 Gy in 30 fractions. Peripheral blood was drawn synchronously with PET imaging, from which germline DNA sequencing, T-cell receptor (TCR) sequencing, and plasma cytokines analysis were performed.

Results

Median follow-up was 18.8 months, 1-year overall survival (OS) 82%, 1-year progression-free survival (PFS) 53%, and 1-year locoregional control (LRC) 88%. Higher mid-treatment PET total lesion glycolysis was detrimental to OS (1-yr 87% vs. 63%, p<0.001), PFS (1-yr 60% vs. 26%, p=0.044) and LRC (1-yr 94% vs. 65%, p=0.012), even after adjustment for clinical/treatment factors. Higher PD-L1 tumor proportion score (TPS) was correlated with PET response (p=0.017): 6/6 patients with high PD-L1 (TPS>50%) were classified as PET responders, while 4/5 patients classified as PET non-responders had negative PD-L1 (TPS<1%). Higher TCR richness and clone distribution slope was associated with improved OS (p=0.018-0.035); clone distribution slope was correlated with PET response (p=0.031). Germline DNA alterations in immunologic pathways had an outsized effect on OS and PET response; of the top 30 SNPs ranked by association with PET response status (p<0.016), a plurality (13/30) came from immunologic pathways.

Conclusions

Mid-chemoradiation PET imaging is prognostic for survival; PET response may be linked to tumor and peripheral T-cell biomarkers.
Simple Scoring Tool to Estimate Risk of Hospitalization and Mortality in Ambulatory and Emergency Department Patients with COVID-19
Authors: Webb Brandon J. , Levin Nicholas M. , Grisel Nancy , Brown Samuel M. , Peltan Ithan D. , Spivak Emily S. , Shah Mark , Stenehjem Eddie , Bledsoe Joseph
Published: February 2021

Background

Accurate methods of identifying patients with COVID-19 who are at high risk of poor outcomes has become especially important with the advent of limited-availability therapies such as monoclonal antibodies. Here we describe development and validation of a simple but accurate scoring tool to classify risk of hospitalization and mortality.

Methods

All consecutive patients testing positive for SARS-CoV-2 from March 25-October 1, 2020 within the Intermountain Healthcare system were included. The cohort was randomly divided into 70% derivation and 30% validation cohorts. A multivariable logistic regression model was fitted for 14-day hospitalization. The optimal model was then adapted to a simple, probabilistic score and applied to the validation cohort and evaluated for prediction of hospitalization and 28-day mortality.

Results

22,816 patients were included; mean age was 40 years, 50.1% were female and 44% identified as non-white race or Hispanic/Latinx ethnicity. 6.2% required hospitalization and 0.4% died. Criteria in the simple model included: age (0.5 points per decade); high-risk comorbidities (2 points each): diabetes mellitus, severe immunocompromised status and obesity (body mass index≥30); non-white race/Hispanic or Latinx ethnicity (2 points), and 1 point each for: male sex, dyspnea, hypertension, coronary artery disease, cardiac arrythmia, congestive heart failure, chronic kidney disease, chronic pulmonary disease, chronic liver disease, cerebrovascular disease, and chronic neurologic disease. In the derivation cohort (n=16,030) area under the receiver-operator characteristic curve (AUROC) was 0.82 (95% CI 0.81-0.84) for hospitalization and 0.91 (0.83-0.94) for 28-day mortality; in the validation cohort (n=6,786) AUROC for hospitalization was 0.8 (CI 0.78-0.82) and for mortality 0.8 (CI 0.69-0.9).

Conclusion

A prediction score based on widely available patient attributes accurately risk stratifies patients with COVID-19 at the time of testing. Applications include patient selection for therapies targeted at preventing disease progression in non-hospitalized patients, including monoclonal antibodies. External validation in independent healthcare environments is needed.
A rapid review of equity considerations in large-scale testing campaigns during infectious disease epidemics
Authors: Ost Katarina , Duquesne Louise , Duguay Claudia , Traverson Lola , Mathevet Isadora , Ridde Valéry , Zinszer Kate
Published: February 2021

Context

Large-scale testing is an intervention that is instrumental for infectious disease control and a central tool for the COVID-19 pandemic. Our rapid review aimed to identify if and how equity has been considered in large-scale testing initiatives.

Methods

We searched Web of Science and PubMed in November 2020 and followed PRISMA recommendations for scoping reviews. Articles were analyzed using descriptive and thematic analysis.

Results

Our search resulted in 291 studies of which 41 were included for data extraction after full article screening. Most of the included articles (83%) reported on HIV-related screening programs, while the remaining programs focused on other sexually transmitted infections (n=3) or COVID-19 (n=4). None of the studies presented a formal definition of (in)equity in testing, however, 23 articles did indirectly include elements of equity in the program or intervention design, largely through the justification of their target population.

Conclusion

The studies included in our rapid review did not explicitly consider equity in their design or evaluation. It is imperative that equity is incorporated into the design of infectious disease testing programs and serves as an important reminder of how equity considerations are needed for SARS-CoV-2 testing and vaccination programs.
High-resolution longitudinal serum proteome trajectories in COVID-19 reveal patients-specific seroconversion
Authors: Geyer Philipp E. , Arend Florian M. , Doll Sophia , Louiset Marie-Luise , Winter Sebastian Virreira , Müller-Reif Johannes B. , Torun Furkan M. , Weigand Michael , Eichhorn Peter , Bruegel Mathias , Strauss Maximilian T. , Holdt Lesca M. , Mann Matthias , Teupser Daniel
Published: February 2021

Biomarkers for COVID-19 are urgently needed. Here we bring the powerful technology of mass spectrometry (MS)-based proteomics to bear on this challenge. We measured serum proteomes of COVID-19 patients and symptomatic, but PCR-negative controls, in a time-resolved manner. In 262 controls and 458 longitudinal samples (average of 31 days) of 31 patients, hospitalized for COVID-19, a remarkable 26% of proteins changed significantly. Bioinformatics analyses revealed co-regulated groups and shared biological functions. Proteins of the innate immune system such as CRP, SAA1, CD14, LBP and LGALS3BP decreased early in the time course. In contrast, regulators of coagulation (APOH, FN1, HRG, KNG1, PLG) and lipid homeostasis (APOA1, APOC1, APOC2, APOC3, PON1) increased over the course of the disease. A global correlation map provides a systems-wide functional association between proteins, biological processes and clinical chemistry parameters. Importantly, five SARS-CoV-2 immunoassays against antibodies revealed excellent correlations with an extensive range of immunoglobulin regions, which were quantified by MS-based proteomics. The high-resolution profile of all immunoglobulin regions showed individual-specific differences and commonalities of potential pathophysiological relevance.

Graphical Abstract

Highlights

A total of 720 proteomes of 262 symptomatic controls and 458 longitudinal samples (average 31 days) of hospitalized COVID-19 cases were analyzed

26% of the 502 quantified proteins significantly changed in COVID-19 patients

The innate immune and the coagulation system were strongly regulated

MS-based profiles of immunoglobulin regions allow the detection of seroconversion in a highly detailed fashion on the patient level

ITIH4 may be a prospective marker of COVID-19 mortality
Estimating DNA methylation potential energy landscapes from nanopore sequencing data
Authors: Abante Jordi , Kambhampati Sandeep , Feinberg Andrew P. , Goutsias John
Published: February 2021

High-throughput third-generation sequencing devices, such as the Oxford Nanopore Technologies (ONT) MinION sequencer, can generate long reads that span thousands of bases. This new technology opens the possibility of considering a wide range of epigenetic modifications and provides the capability of interrogating previously inaccessible regions of the genome, such as highly repetitive regions, as well as of performing comprehensive allele-specific methylation analysis, among other applications. It is well-known, however, that detection of DNA methylation from nanopore data results in a substantially reduced per-read accuracy when comparing to WGBS, due to noise introduced by the sequencer and its underlying chemistry. It is therefore imperative that methods are developed for the reliable modeling and analysis of the DNA methylation landscape using nanopore data. Here we introduce such method that takes into account the presence of noise introduced by the ONT sequencer and, by using simulations, we provide evidence of its potential. The proposed approach establishes a solid foundation for the development of a comprehensive framework for the statistical analysis of DNA methylation, and possibly of other epigenetic marks, using third-generation sequencing.
The role of memory in non-genetic inheritance and its impact on cancer treatment resistance
Authors: Cassidy Tyler , Nichol Daniel , Robertson-Tessi Mark , Craig Morgan , Anderson Alexander R.A.
Published: February 2021

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

Author summary

We propose a simple mathematical model to understand the role of phenotypic plasticity and non-genetic inheritance in driving therapy resistance in cancer. We identify the role of non-genetic inheritance on treatment resistance and use a variety of analytical and numerical techniques to understand the impact of phenotypic plasticity on population fitness and dynamics. We further use our model to study the role of phenotypic heterogeneity in therapeutic resistance in a genetically identical non-small cell lung cancer population. Finally, we combine analytical perspectives and techniques from the theory of structured populations, renewal equations and infinite dimensional dynamical systems to derive a model informed therapeutic strategy that both drives tumour eradication while avoiding competitive release of a drug-tolerant subpopulation. These results exemplify the potential of using mathematical techniques to identify therapeutic strategies to guide the evolution of a heterogeneous tumour.
Reanalysis of deep-sequencing data from Austria points towards a small SARS-COV-2 transmission bottleneck on the order of one to three virions
Authors: Martin Michael A. , Koelle Katia
Published: February 2021

An early analysis of SARS-CoV-2 deep-sequencing data that combined epidemiological and genetic data to characterize the transmission dynamics of the virus in and beyond Austria concluded that the size of the virus’s transmission bottleneck was large – on the order of 1000 virions. We performed new computational analyses using these deep-sequenced samples from Austria. Our analyses included characterization of transmission bottleneck sizes across a range of variant calling thresholds and examination of patterns of shared low-frequency variants between transmission pairs in cases wherede novogenetic variation was present in the recipient. From these analyses, among others, we found that SARS-CoV-2 transmission bottlenecks are instead likely to be very tight, on the order of 1-3 virions. These findings have important consequences for understanding how SARS-CoV-2 evolves between hosts and the processes shaping genetic variation observed at the population level.
The contribution of electrostatics to hydrogen exchange in the unfolded protein state
Authors: Dass Rupashree , Corlianò Enrico , Mulder Frans A. A.
Published: February 2021

Although electrostatics have long been recognized to play an important role in hydrogen exchange (HX) with solvent, the quantitative assessment of its magnitude in the unfolded state has hitherto been lacking. This limits the utility of HX as a quantitative method to study protein stability, folding and dynamics. Using the intrinsically disordered human protein α-synuclein as a proxy for the unfolded state, we show that a hybrid mean-field approach can effectively compute the electrostatic potential at all backbone amide positions along the chain. From the electrochemical potential a fourfold reduction in hydroxide concentration near the protein backbone is predicted for the C-terminal domain, a prognosis that is in direct agreement with experimentally-derived protection factors from NMR spectroscopy. Thus, impeded HX for the C-terminal region of α-synuclein is not the result of intramolecular hydrogen bonding and/or structure formation.
Comparative analysis of host-associated variation in Phytophthora cactorum
Authors: Nellist Charlotte F. , Armitage Andrew D. , Bates Helen J. , Sobczyk Maria K. , Luberti Matteo , Lewis Laura A. , Harrison Richard J.
Published: February 2021

Phytophthora cactorum is often described as a generalist pathogen, with isolates causing disease in a range of plant species. It is the causative agent of two diseases in the cultivated strawberry, crown rot (CR; causing whole plant collapse) and leather rot (LR; affecting the fruit). In the cultivated apple, P. cactorum causes girdling bark rots on the scion (collar rot) and rootstock (crown rot), as well as necrosis of the fine root system (root rot) and fruit rots. We investigated evidence for host specialisation within P. cactorum through comparative genomic analysis of 18 isolates. Whole genome phylogenetic analysis provided genomic support for discrete lineages within P. cactorum, with well supported non-recombing clades for strawberry CR and apple infecting isolates specialised to strawberry crowns and apple tissue. Isolates of strawberry CR are genetically similar globally, while there is more diversity in apple-infecting isolates. We sought to identify the genetic basis of host specialisation, demonstrating gain and loss of effector complements within the P. cactorum phylogeny, representing putative determinants of host boundaries. Transcriptomic analysis highlighted that those effectors found to be specific to a single host or expanded in the strawberry lineage are amongst those most highly expressed during infection of strawberry and give a wider insight into the key effectors active during strawberry infection. Many effectors that had homologs in other Phytophthoras that have been characterised as avirulence genes were present but not expressed in our tested isolate. Our results highlight several RxLR-containing effectors that warrant further investigation to determine whether they are indeed virulence factors and host-specificity determinants for strawberry and apple. Furthermore, additional work is required to determine whether these effectors are suitable targets to focus attention on for future resistance breeding efforts.
Small-RNA sequencing reveals altered skeletal muscle microRNAs and snoRNAs signatures in weanling male offspring from mouse dams fed a low protein diet during lactation
Authors: Kanakis Ioannis , Alameddine Moussira , Folkes Leighton , Moxon Simon , Myrtziou Ioanna , Ozanne Susan E. , Peffers Mandy J. , Goljanek-Whysall Katarzyna , Vasilaki Aphrodite
Published: February 2021

Nutrition plays a key role in pre- and postnatal growth of the musculoskeletal system. Maternal diet during gestation and lactation affects the development of skeletal muscles in the offspring and determines muscle health in later life, however, the molecular mechanisms that govern these effects are largely unknown. In this study, we aim to describe the association between maternal low protein diet-induced changes in offspring skeletal muscle and the differential expression (DE) of small non-coding RNAs (sncRNAs). We used a mouse model of maternal protein restriction to characterise the impact of early-life undernutrition on skeletal muscle morphology in male offspring at weaning. Mouse dams were fed either a normal (N, 20%) or a low protein (L, 8%) diet during gestation and newborn pups were cross-fostered to N or L lactating dams, resulting in the generation of NN, NL and LN offspring groups. Total body and tibialis anterior (TA) weights were decreased in NL males but not different in the LN group, as compared to NN, although neonates from low protein fed dams were smaller at birth than those born to dams fed a normal protein. However, histological evaluation of TA muscle revealed reduced muscle fibre size in both groups at the end of lactation. Small RNA-seq analysis demonstrated DE of multiple classes of sncRNAs, including miRs, snoRNAs and snRNAs. Bioinformatic analyses of miRs-15a, −34a, −122 and −199a, in combination with known myomiRs, confirmed their implication in key muscle-specific biological processes and cellular functions and suggest a promising set of miRs in muscle physiology studies. To our knowledge, this is the first comprehensive report for the DE of sncRNAs in nutrition-associated programming of skeletal muscle development, highlighting the need for further research.
Genetic mapping and identification of a QTL determining tolerance to freezing stress inFragaria vescaL.
Authors: Davik Jahn , Wilson Robert C. , Njah Relindis G. , Grini Paul E. , Randall Stephen K. , Alsheik Muath K. , Sargent Daniel James
Published: February 2021

Extreme cold and frost cause significant stress to plants which can potentially be lethal. Low temperature freezing stress can cause significant and irreversible damage to plant cells and can induce physiological and metabolic changes that impact on growth and development. Low temperatures cause physiological responses including winter dormancy and autumn cold hardening in strawberry (Fragaria) species, and some diploidF. vescaaccessions have been shown to have adapted to low-temperature stresses. To study the genetics of freezing tolerance, aF. vescamapping population of 142 seedlings segregating for differential responses to freezing stress was raised. The progeny was mapped using ‘Genotyping-by-Sequencing’ and a linkage map of 2,918 markers at 851 loci was resolved. The mapping population was phenotyped for freezing tolerance response under controlled and replicated laboratory conditions and subsequent quantitative trait loci analysis using interval mapping revealed a single significant quantitative trait locus onFvb2in the physical interval 10.6 Mb and 15.73 Mb on theF. vescav4.0 genome sequence. This physical interval contained 896 predicted genes, several of which had putative roles associated with tolerance to abiotic stresses including freezing. Differential expression analysis of the 896 QTL-associated gene predictions in the leaves and crowns from ‘Alta’ and ‘NCGR1363’ parental genotypes revealed genotype-specific changes in transcript accumulation in response to low temperature treatment as well as expression differences between genotypes prior to treatment for many of the genes. The putative roles, and significant interparental differential expression levels of several of the genes reported here identified them as good candidates for the control of the effects of freezing tolerance at the QTL identified in this investigation and the possible role of these candidate genes in response to freezing stress is discussed.
Epigenetic rewriting at centromeric DNA repeats leads to increased chromatin accessibility and chromosomal instability
Authors: Decombe Sheldon , Loll François , Caccianini Laura , Affannoukoué Kévin , Izeddin Ignacio , Mozziconacci Julien , Escudé Christophe , Lopes Judith
Published: February 2021

Centromeric regions of human chromosomes contain large numbers of tandemly repeated α-satellite sequences. These sequences are covered with constitutive heterochromatin which is enriched in trimethylation of histone H3 on lysine 9 (H3K9me3). Although well studied using artificial chromosomes and global perturbations, the contribution of this epigenetic mark to chromatin structure and genome stability remains poorly known in a more natural context. Using transcriptional activator-like effectors (TALEs) fused to a histone lysine demethylase (JMJD2B), we were able to reduce the level of H3K9me3 on the α-satellites repeats of human chromosome 7. We show that the removal of H3K9me3 affects chromatin structure by increasing the accessibility of DNA repeats to the TALE protein. Tethering TALE-demethylase to centromeric repeats impairs the recruitment of HP1α and proteins of Chromosomal Passenger Complex (CPC) on this specific centromere. Finally, the epigenetic re-writing by the TALE-JMJD2B affects specifically the stability of chromosome 7 upon mitosis, highlighting the importance of H3K9me3 in centromere integrity and chromosome stability, mediated by the recruitment of HP1α and the CPC.
Trends in community- and nosocomial-acquired infections of carbapenem resistant Enterobacteriaceae (CRE), carbapenemase producing Enterobacteriaceae (CPE) and vancomycin resistant Enterococcus (VRE): a 10-year prospective observational study
Authors: Ubillus Arriola Gloria Maritza , Araujo Banchon William , Patiño Gabriel Lilian , Kolevic Lenka , del Carmen Quispe Manco María , Olivo Lopez José María , Barrientos Achata Armando , Revilla Velasquez Maria Elena , Bouzid Donia , Casalino Enrique
Published: February 2021

Introduction

CRE, CPE, and VRE are considered significant threats to public health.

Aim

To determine trends of nosocomial- and community-acquired infections.

Methods

A 10-year prospective observational non-interventional study was conducted. We used time-series analysis to evaluate trends in infections number.

Findings

Infection rate (%) were: CRE 2.48 (261/10,533), CPE 1.66 (175/10,533) and VRE 15.9 (121/761). We found diminishing trends for CRE (−19% [−31;−5], P=.03) and CPE (−22% [−30;−8], P=.04) but increasing trend for VRE (+48; [CI95% 34;75], P=.001). While we found decreasing trends for CRE and CPE in emergency (−71 [−122;−25], P=.001; −45 [−92;−27], P=.001) and hospitalization (−127 [−159; −85], P=.001; −56 [−98;−216], P=.01), we found increasing trends for VRE (+148 [113;192], P=.00001; +108[65;152], P=.003). Nosocomial-infections fell in CRE (−238 [−183;−316], P=.0001) and CPE (−163 [−96; −208], P=.001), but rose in VRE (+196 [151;242], P=.0001). We showed increasing trends in ambulatory and community-acquired infections in CRE (+134% [96;189]; P=.001; +77% [52;89]; P= .002), CPE (+288 [226;343]; P=.0001; +21% [−12;46]; P=.0.08) and VRE (+348 [295;458]; P=.0001; +66% [41;83]; P=.003). Direct admitted trends rose in all groups (CRE 16% [−8; 42]; P=.05), CPE 23% [−6; 48] (P=.05) and VRE (+241 [188; 301]; P=.0001).

Conclusions

We found a changing infection pattern with decreasing trends in in-hospital settings and nosocomial-acquired infections but increasing ambulatory and community-acquired infections. The observed increasing-trends in direct-admitted could be explained by community-onset infections diagnosed in the hospital. Our findings highlight the need to identify CRE/CPE/VRE community-acquired infections in ambulatory and in-hospital settings.
Analysing variations in pelage patterning among EuropeanFelis silvestris silvestrispopulations
Authors: Reher David , Stefen Clara
Published: February 2021

The pelage pattern of wildcats from six regions within the distribution range of the species is analysed to test the hypothesis that clear differences between different regions exist. In total, 98 furs were used, but with different distribution from the Eifel (Germany), Harz Mountains (Germany), Caucasus, Western Spain, Switzerland/France and Greece. Specimens were at least seven months old, sex was not considered. The characteristics used were adapted from the literature and included typical wildcat features like the tail and stripes on the neck. Polychoric correlations, as a binary version of Spearman’s rank correlation coefficient, were used as a measure of correlation between pelage characteristics. Pairwise tetrachoric correlations were computed with R 3.1.2., cluster analyses were conducted with SPSS 14.

No clear relationship between the pelage characteristics and the geographic distribution of the six studied wildcat populations were found, the hypothesis needs to be rejected. It is however suggested, that coat patterning of Caucasian wildcats to some degree differ from other European wildcat. The results, however, do not clearly corroborate this hypothesis as Caucasian wildcats were not grouped into closed clusters in all the cluster analyses. To a lesser extent, pelage characteristic differences may also exist between wildcats from Western Spain as well as South-Western Greece and other European regions, but the samples are too small to draw conclusions. To test these refined hypotheses, more specimens from the Caucasus, Western Spain and South-Western Greece (but also Switzerland/North-Eastern France) need to be collected and compared according to our protocol.
Dual proteomics ofDrosophila melanogasterhemolymph infected with the heritable endosymbiontSpiroplasma poulsonii
Authors: Masson Florent , Rommelaere Samuel , Marra Alice , Schüpfer Fanny , Lemaitre Bruno
Published: February 2021

Insects are frequently infected with heritable bacterial endosymbionts. Endosymbionts have a dramatic impact on their host physiology and evolution. Their tissue distribution is variable with some species being housed intracellularly, some extracellularly and some having a mixed lifestyle. The impact of extracellular endosymbionts on the biofluids they colonize (e.g. insect hemolymph) is however difficult to appreciate because biofluids composition can depend on the contribution of numerous tissues.

Here we address the question ofDrosophilahemolymph proteome response to the infection with the endosymbiontSpiroplasma poulsonii. S. poulsoniiinhabits the fly hemolymph and gets vertically transmitted over generations by hijacking the oogenesis in females. Using dual proteomics on infected hemolymph, we uncovered a low level and chronic activation of the Toll immune pathway byS. poulsoniithat was previously undetected by transcriptomics-based approaches. Using Drosophila genetics, we also identified candidate proteins putatively involved in controllingS. poulsoniigrowth. Last, we also provide a deep proteome ofS. poulsonii, which, in combination with previously published transcriptomics data, improves our understanding of the post-transcriptional regulations operating in this bacterium.

Summary statement

We report the changes inDrosophila melanogasterhemolymph proteome upon infection with the heritable bacterial endosymbiontSpiroplasma poulsonii.
Hierarchical cross-scale analysis identifies parallel ventral striatal networks coding for dynamic and stabilized olfactory reward predictions
Authors: Winkelmeier Laurens , Filosa Carla , Scheller Max , Hartig Renée , Sack Markus , Becker Robert , Wolf David , Reinwald Jonathan , Gerchen Martin Fungisai , Sartorius Alexander , Meyer-Lindenberg Andreas , Weber-Fahr Wolfgang , von Hohenberg Christian Clemm , Russo Eleonora , Kelsch Wolfgang
Published: February 2021

The unbiased identification of brain circuits responsible for behavior and their local cellular computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach from behavioral modeling and fMRI in task-performing mice to cellular network dynamics to identify how reward predictions are represented in the forebrain upon olfactory conditioning. fMRI identified functional segregation in reward prediction and error computations among olfactory cortices and subcortical circuits. Among them, the olfactory tubercle contributed both to dynamic reward predictions and prediction error. In this region, cellular recordings revealed two parallel neuronal populations for prediction coding. One population produced stabilized predictions as distributed stimulus-bound transient network activity; the other evolved during anticipatory waiting and fully reflected predicted value in single-units, dynamically integrating the recent cue-specific history of uncertain outcomes. Thus, the cross-scale approach revealed regional functional differentiation among the distributed forebrain circuits with a limbic hotspot for multiple non-redundant reward prediction coding.