Quantum transport in double-gated graphene devices

Double-gated graphene devices provide an important platform for understanding electrical and optical properties of graphene. Here we present transport measurements of single layer, bilayer and trilayer graphene devices with suspended top gates. In zero magnetic fields, we observe formation of pnp junctions with tunable polarity and charge densities, as well as a tunable band gap in bilayer graphene and a tunable band overlap in trilayer graphene. In high magnetic fields, the devices' conductance are quantized at integer and fractional values of conductance quantum, and the data are in good agreement with a model based on edge state equilibration at pn interfaces

Abacavir inhibits but does not cause self-reactivity to HLA-B*57:01-restricted EBV specific T cell receptors

Pre-existing pathogen-specific memory T cell responses can contribute to multiple adverse outcomes including autoimmunity and drug hypersensitivity. How the specificity of the T cell receptor (TCR) is subverted or seconded in many of these diseases remains unclear. Here, we apply abacavir hypersensitivity (AHS) as a model to address this question because the disease is linked to memory T cell responses and the HLA risk allele, HLA-B*57:01, and the initiating insult, abacavir, are known. To investigate the role of pathogen-specific TCR specificity in mediating AHS we performed a genome-wide screen for HLA-B*57:01 restricted T cell responses to Epstein-Barr virus (EBV), one of the most prevalent human pathogens. T cell epitope mapping revealed HLA-B*57:01 restricted responses to 17 EBV open reading frames and identified an epitope encoded by EBNA3C. Using these data, we cloned the dominant TCR for EBNA3C and a previously defined epitope within EBNA3B. TCR specificity to each epitope was confirmed, however, cloned TCRs did not cross-react with abacavir plus self-peptide. Nevertheless, abacavir inhibited TCR interactions with their cognate ligands, demonstrating that TCR specificity may be subverted by a drug molecule. These results provide an experimental road map for future studies addressing the heterologous immune responses of TCRs including T cell mediated adverse drug reactions

The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems

There are numerous examples of morphogen gradients controlling long range signalling in developmental and cellular systems. The prospect of two such interacting morphogens instigating long range self-organisation in biological systems via a Turing bifurcation has been explored, postulated, or implicated in the context of numerous developmental processes. However, modelling investigations of cellular systems typically neglect the influence of gene expression on such dynamics, even though transcription and translation are observed to be important in morphogenetic systems. In particular, the influence of gene expression on a large class of Turing bifurcation models, namely those with pure kinetics such as the Gierer–Meinhardt system, is unexplored. Our investigations demonstrate that the behaviour of the Gierer–Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen oscillations and radical sensitivities to the duration of gene expression are observed and, at best, severely restrict the possible parameter spaces for feasible biological behaviour. These results also indicate that the behaviour of Turing pattern formation systems on the inclusion of gene expression time delays may provide a means of distinguishing between possible forms of interaction kinetics. Finally, this study also emphasises that sub-cellular and gene expression dynamics should not be simply neglected in models of long range biological pattern formation via morphogens

Aberrant behaviours of reaction diffusion self-organisation models on growing domains in the presence of gene expression time delays

Turing’s pattern formation mechanism exhibits sensitivity to the details of the initial conditions suggesting that, in isolation, it cannot robustly generate pattern within noisy biological environments. Nonetheless, secondary aspects of developmental self-organisation, such as a growing domain, have been shown to ameliorate this aberrant model behaviour. Furthermore, while in-situ hybridisation reveals the presence of gene expression in developmental processes, the influence of such dynamics on Turing’s model has received limited attention. Here, we novelly focus on the Gierer–Meinhardt reaction diffusion system considering delays due the time taken for gene expression, while incorporating a number of different domain growth profiles to further explore the influence and interplay of domain growth and gene expression on Turing’s mechanism. We find extensive pathological model behaviour, exhibiting one or more of the following: temporal oscillations with no spatial structure, a failure of the Turing instability and an extreme sensitivity to the initial conditions, the growth profile and the duration of gene expression. This deviant behaviour is even more severe than observed in previous studies of Schnakenberg kinetics on exponentially growing domains in the presence of gene expression (Gaffney and Monk in Bull. Math. Biol. 68:99–130, 2006). Our results emphasise that gene expression dynamics induce unrealistic behaviour in Turing’s model for multiple choices of kinetics and thus such aberrant modelling predictions are likely to be generic. They also highlight that domain growth can no longer ameliorate the excessive sensitivity of Turing’s mechanism in the presence of gene expression time delays. The above, extensive, pathologies suggest that, in the presence of gene expression, Turing’s mechanism would generally require a novel and extensive secondary mechanism to control reaction diffusion patterning

Revealing CO2-fixing SAR11 bacteria in the ocean by Raman-based single-cell metabolic profiling and genomics

The majority of marine microbes remain uncultured, which hinders the identification and mining of CO2-fixing genes, pathways, and chassis from the oceans. Here, we investigated CO2-fixing microbes in seawater from the euphotic zone of the Yellow Sea of China by detecting and tracking their 13C-bicarbonate (13C-HCO3-) intake via single-cell Raman spectra (SCRS) analysis. The target cells were then isolated by Raman-activated Gravity-driven Encapsulation (RAGE), and their genomes were amplified and sequenced at one-cell resolution. The single-cell metabolism, phenotype and genome are consistent. We identified a not-yet-cultured Pelagibacter spp., which actively assimilates 13C-HCO3-, and also possesses most of the genes encoding enzymes of the Calvin-Benson cycle for CO2 fixation, a complete gene set for a rhodopsin-based light-harvesting system, and the full genes necessary for carotenoid synthesis. The four proteorhodopsin (PR) genes identified in the Pelagibacter spp. were confirmed by heterologous expression in E. coli. These results suggest that hitherto uncultured Pelagibacter spp. uses light-powered metabolism to contribute to global carbon cycling

The Origin, Early Evolution and Predictability of Solar Eruptions

Coronal mass ejections (CMEs) were discovered in the early 1970s when space-borne coronagraphs revealed that eruptions of plasma are ejected from the Sun. Today, it is known that the Sun produces eruptive flares, filament eruptions, coronal mass ejections and failed eruptions; all thought to be due to a release of energy stored in the coronal magnetic field during its drastic reconfiguration. This review discusses the observations and physical mechanisms behind this eruptive activity, with a view to making an assessment of the current capability of forecasting these events for space weather risk and impact mitigation. Whilst a wealth of observations exist, and detailed models have been developed, there still exists a need to draw these approaches together. In particular more realistic models are encouraged in order to asses the full range of complexity of the solar atmosphere and the criteria for which an eruption is formed. From the observational side, a more detailed understanding of the role of photospheric flows and reconnection is needed in order to identify the evolutionary path that ultimately means a magnetic structure will erupt

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century