Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity

C-Terminal Region of EBNA-2 Determines the Superior Transforming Ability of Type 1 Epstein-Barr Virus by Enhanced Gene Regulation of LMP-1 and CXCR7

Type 1 Epstein-Barr virus (EBV) strains immortalize B lymphocytes in vitro much more efficiently than type 2 EBV, a difference previously mapped to the EBNA-2 locus. Here we demonstrate that the greater transforming activity of type 1 EBV correlates with a stronger and more rapid induction of the viral oncogene LMP-1 and the cell gene CXCR7 (which are both required for proliferation of EBV-LCLs) during infection of primary B cells with recombinant viruses. Surprisingly, although the major sequence differences between type 1 and type 2 EBNA-2 lie in N-terminal parts of the protein, the superior ability of type 1 EBNA-2 to induce proliferation of EBV-infected lymphoblasts is mostly determined by the C-terminus of EBNA-2. Substitution of the C-terminus of type 1 EBNA-2 into the type 2 protein is sufficient to confer a type 1 growth phenotype and type 1 expression levels of LMP-1 and CXCR7 in an EREB2.5 cell growth assay. Within this region, the RG, CR7 and TAD domains are the minimum type 1 sequences required. Sequencing the C-terminus of EBNA-2 from additional EBV isolates showed high sequence identity within type 1 isolates or within type 2 isolates, indicating that the functional differences mapped are typical of EBV type sequences. The results indicate that the C-terminus of EBNA-2 accounts for the greater ability of type 1 EBV to promote B cell proliferation, through mechanisms that include higher induction of genes (LMP-1 and CXCR7) required for proliferation and survival of EBV-LCLs

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

GC-Rich DNA Elements Enable Replication Origin Activity in the Methylotrophic Yeast <i>Pichia pastoris</i>

<div><p>The well-studied DNA replication origins of the model budding and fission yeasts are A/T-rich elements. However, unlike their yeast counterparts, both plant and metazoan origins are G/C-rich and are associated with transcription start sites. Here we show that an industrially important methylotrophic budding yeast, <i>Pichia pastoris</i>, simultaneously employs at least two types of replication origins—a G/C-rich type associated with transcription start sites and an A/T-rich type more reminiscent of typical budding and fission yeast origins. We used a suite of massively parallel sequencing tools to map and dissect <i>P. pastoris</i> origins comprehensively, to measure their replication dynamics, and to assay the global positioning of nucleosomes across the genome. Our results suggest that some functional overlap exists between promoter sequences and G/C-rich replication origins in <i>P. pastoris</i> and imply an evolutionary bifurcation of the modes of replication initiation.</p></div

Replication timing of the <i>P. pastoris</i> genome.

<p>(A) Genomic DNA from G1 and S phase cells was sheared and sequenced. Normalized S/G1 DNA copy ratios (in 1 kbp windows) were smoothed and plotted against chromosomal coordinates. Peaks correspond to positions of replication initiation. The profile of chromosome 4 is shown (all chromosomes are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004169#pgen.1004169.s006" target="_blank">Figure S6</a>) with ARS locations indicated by open (AT-ARSs) and shaded (GC-ARSs) circles. Un-smoothed ratio data for one of the replicates is shown are grey. Coordinates of replication timing peaks are indicated by dashed vertical lines. (B) The distributions of smoothed S/G1 ratio data. The distribution of all ratios (“Genome”) is shown adjacent to the distribution of values at bins containing midpoints of GC-ACSs (“GC”) or AT-ARSs (“AT”). Values for ARSs that have no other ARSs within 40 kb in both directions are shown on the right (“isolated”). (C) The complete genomic ratio distribution is shown relative to distributions after removal of data within 60 kb ranges centered on AT-ARSs (“AT”), GC-ARSs (“GC”), or all ARSs (“all ARS”). (D) For each ARS, the distance to the nearest replication peak was calculated. The ARS-peak distances are shown as distributions separately for GC-ARSs (blue) and AT-ARSs (orange). Peak distances from simulated random sets of loci are shown in grey.</p

Sequence features of GC-ARSs.

<p>(A) Average nucleotide frequencies around 107 GC-ARS sites (top) and twenty-eight non-ARS intergenic occurrences of the GC-ACS (bottom), centered on the best match of the GC-ACS. The nucleotide frequencies are calculated at all flanking regions around the motif independent of whether the flanking region is present in ARS contigs or cores. (B) The distribution of distances between the GC-ACS motif (in the orientation shown) and the TSS for adjacent genes transcribing away from the ARS with available TSS annotations. Distances to the 5′ side of the motif are shown in blue; distances to the 3′ side of the motif are shown in red. (C) The distribution of sequence lengths between the GC-ACS and the end of the inferred functional core region for each GC-ARS. The 5′ distance is indicated in blue; the 3′ distance is indicated in red. Numbers indicate the upper limit of the bin.</p

The GC-ACS is required for GC-ARS function.

<p>Wild type (WT) and mutant (MUT) alleles of the twelve ARSs indicated were cloned into a <i>URA3</i> ARS-less vector and used to transform <i>ura3</i> yeast on selective medium plates lacking uracil. Plates were grown at 30°C for five days before pictures were taken. Colony formation indicates plasmid maintenance and ARS activity. The GC-ACS was positioned <15 bp away from the 5′ endpoint in all ARS sequences. The sequences of the fragments tested are listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004169#pgen.1004169.s012" target="_blank">Table S4</a>.</p