Planetary science and exploration in the deep subsurface: results from the MINAR Program, Boulby Mine, UK

The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research – MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining

SIRT1 Promotes N-Myc Oncogenesis through a Positive Feedback Loop Involving the Effects of MKP3 and ERK on N-Myc Protein Stability

The N-Myc oncoprotein is a critical factor in neuroblastoma tumorigenesis which requires additional mechanisms converting a low-level to a high-level N-Myc expression. N-Myc protein is stabilized when phosphorylated at Serine 62 by phosphorylated ERK protein. Here we describe a novel positive feedback loop whereby N-Myc directly induced the transcription of the class III histone deacetylase SIRT1, which in turn increased N-Myc protein stability. SIRT1 binds to Myc Box I domain of N-Myc protein to form a novel transcriptional repressor complex at gene promoter of mitogen-activated protein kinase phosphatase 3 (MKP3), leading to transcriptional repression of MKP3, ERK protein phosphorylation, N-Myc protein phosphorylation at Serine 62, and N-Myc protein stabilization. Importantly, SIRT1 was up-regulated, MKP3 down-regulated, in pre-cancerous cells, and preventative treatment with the SIRT1 inhibitor Cambinol reduced tumorigenesis in TH-MYCN transgenic mice. Our data demonstrate the important roles of SIRT1 in N-Myc oncogenesis and SIRT1 inhibitors in the prevention and therapy of N-Myc–induced neuroblastoma

Preclinical Models for Neuroblastoma: Establishing a Baseline for Treatment

Preclinical models of pediatric cancers are essential for testing new chemotherapeutic combinations for clinical trials. The most widely used genetic model for preclinical testing of neuroblastoma is the TH-MYCN mouse. This neuroblastoma-prone mouse recapitulates many of the features of human neuroblastoma. Limitations of this model include the low frequency of bone marrow metastasis, the lack of information on whether the gene expression patterns in this system parallels human neuroblastomas, the relatively slow rate of tumor formation and variability in tumor penetrance on different genetic backgrounds. As an alternative, preclinical studies are frequently performed using human cell lines xenografted into immunocompromised mice, either as flank implant or orthtotopically. Drawbacks of this system include the use of cell lines that have been in culture for years, the inappropriate microenvironment of the flank or difficult, time consuming surgery for orthotopic transplants and the absence of an intact immune system.Here we characterize and optimize both systems to increase their utility for preclinical studies. We show that TH-MYCN mice develop tumors in the paraspinal ganglia, but not in the adrenal, with cellular and gene expression patterns similar to human NB. In addition, we present a new ultrasound guided, minimally invasive orthotopic xenograft method. This injection technique is rapid, provides accurate targeting of the injected cells and leads to efficient engraftment. We also demonstrate that tumors can be detected, monitored and quantified prior to visualization using ultrasound, MRI and bioluminescence. Finally we develop and test a "standard of care" chemotherapy regimen. This protocol, which is based on current treatments for neuroblastoma, provides a baseline for comparison of new therapeutic agents.The studies suggest that use of both the TH-NMYC model of neuroblastoma and the orthotopic xenograft model provide the optimal combination for testing new chemotherapies for this devastating childhood cancer

A Cre-conditional MYCN-driven neuroblastoma mouse model as an improved tool for preclinical studies

Neuroblastoma, a childhood cancer that originates from neural crest-derived cells, is the most common deadly solid tumor of infancy. Amplification of the MYCN oncogene, which occurs in approximately 20-25% of human neuroblastomas, is the most prominent genetic marker of high-stage disease. The availability of valid preclinical in vivo models is a prerequisite to develop novel targeted therapies. We here report on the generation of transgenic mice with Cre-conditional induction of MYCN in dopamine β-hydroxylase-expressing cells, termed LSL-MYCN;Dbh-iCre. These mice develop neuroblastic tumors with an incidence of >75%, regardless of strain background. Molecular profiling of tumors revealed upregulation of the MYCN-dependent miR-17-92 cluster as well as expression of neuroblastoma marker genes, including tyrosine hydroxylase and the neural cell adhesion molecule 1. Gene set enrichment analyses demonstrated significant correlation with MYC-associated expression patterns. Array comparative genome hybridization showed that chromosomal aberrations in LSL-MYCN;Dbh-iCre tumors were syntenic to those observed in human neuroblastomas. Treatment of a cell line established from a tumor derived from a LSL-MYCN;Dbh-iCre mouse with JQ1 or MLN8237 reduced cell viability and demonstrated oncogene addiction to MYCN. Here we report establishment of the first Cre-conditional human MYCN-driven mouse model for neuroblastoma that closely recapitulates the human disease with respect to tumor localization, histology, marker expression and genomic make up. This mouse model is a valuable tool for further functional studies and to assess the effect of targeted therapies

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine