A perspective on the impacts of microplastics on mosquito biology and their vectorial capacity

Microplastics (plastic particles <5 mm) permeate aquatic and terrestrial ecosystems and constitute a hazard to animal life. Although much research has been conducted on the effects of microplastics on marine and benthic organisms, less consideration has been given to insects, especially those adapted to urban environments. Here, we provide a perspective on the potential consequences of exposure to microplastics within typical larval habitat on mosquito biology. Mosquitoes represent an ideal organism in which to explore the biological effects of microplastics on terrestrial insects, not least because of their importance as an infectious disease vector. Drawing on evidence from other organisms and knowledge of the mosquito life cycle, we summarise some of the more plausible impacts of microplastics including physiological, ecotoxicological and immunological responses. We conclude that although there remains little experimental evidence demonstrating any adverse effect on mosquito biology or pathogen transmission, significant knowledge gaps remain, and there is now a need to quantify the effects that microplastic pollution could have on such an important disease vector.

Molecular frustration: a hypothesis for regulation of viral infections

The recent revolution in imaging techniques and results from RNA footprinting in situ reveal how the bacteriophage MS2 genome regulates both particle assembly and genome release. We have proposed a model in which multiple packaging signal (PS) RNA-coat protein (CP) contacts orchestrate different stages of a viral life cycle. Programmed formation and release of specific PS contacts with CP regulates viral particle assembly and genome uncoating during cell entry. We hypothesize that molecular frustration, a concept introduced to understand protein folding, can be used to better rationalize how PSs function in both particle assembly and genome release. More broadly this concept may explain the directionality of viral life cycles, for example, the roles of host cofactors in HIV infection. We propose that this is a universal principle in virology that explains mechanisms of host-virus interaction and suggests diverse therapeutic interventions.

Conical shell X-ray beam tomosynthesis and micro-computed tomography for microarchitectural characterisation

Bone quality is commonly used to diagnose bone diseases such as osteoporosis, with many studies focusing on microarchitecture for fracture prediction. In this study a bovine distal femur was imaged using both micro-computed tomography (µCT) and tomosynthesis using focal construct geometry (FCG) for comparison of microarchitectural parameters. Six regions of interest (ROIs) were compared between the two imaging modalities, with both global and adaptive methods used to binarize the images. FCG images were downsampled to the same pixel size as the µCT images. Bone morphometrics were determined using BoneJ, for each imaging modality, binarization technique and ROI. Bone area/total area was found to have few significant differences between FCG and µCT (p < 0.05 for two of six ROIs). Fractal Dimension had only one significant difference (p < 0.05 for one of six ROIs) between µCT and downsampled FCG (where pixel size was equalized). Trabecular thickness and trabecular spacing were observed to follow trends as observed for the corresponding µCT images, although many absolute values were significantly different (p < 0.05 for between one and six ROIs depending on image types used). This study demonstrates the utility of tomosynthesis for measurement of microarchitectural morphometrics.

Persistence of SARS-CoV-2 and its surrogate, bacteriophage Phi6, on surfaces and in water

IMPORTANCE

The COVID-19 pandemic spurred research on the persistence of SARS-CoV-2 and its surrogates. Here we highlight the importance of evaluating viral surrogates and experimental methodologies when studying pathogen survival in the environment.

Variable microbiomes between mosquito lines are maintained across different environments

The composition of the microbiome is shaped by both environment and host in most organisms, but in the mosquito Aedes aegypti the role of the host in shaping the microbiome is poorly understood. Previously, we had shown that four lines of Ae. aegypti harbored different microbiomes when reared in the same insectary under identical conditions. To determine whether these lines differed from each other across time and in different environments, we characterized the microbiome of the same four lines of Ae. aegypti reared in the original insectary and at another institution. While it was clear that the environment influenced the microbiomes of these lines, we did still observe distinct differences in the microbiome between lines within each insectary. Clear differences were observed in alpha diversity, beta diversity, and abundance of specific bacterial taxa. To determine if the line specific differences in the microbiome were maintained across environments, pair-wise differential abundances of taxa was compared between insectaries. Lines were most similar to other lines from the same insectary than to the same line reared in a different insectary. Additionally, relatively few differentially abundant taxa identified between pairs of lines were shared across insectaries, indicating that line specific properties of the microbiome are not conserved across environments, or that there were distinct microbiota within each insectary. Overall, these results demonstrate that mosquito lines under the same environmental conditions have different microbiomes across microbially- diverse environments and host by microbe interactions affecting microbiome composition and abundance is dependent on environmentally available bacteria.

Image Reconstruction in Light-Sheet Microscopy: Spatially Varying Deconvolution and Mixed Noise

We study the problem of deconvolution for light-sheet microscopy, where the data is corrupted by spatially varying blur and a combination of Poisson and Gaussian noise. The spatial variation of the point spread function of a light-sheet microscope is determined by the interaction between the excitation sheet and the detection objective PSF. We introduce a model of the image formation process that incorporates this interaction and we formulate a variational model that accounts for the combination of Poisson and Gaussian noise through a data fidelity term consisting of the infimal convolution of the single noise fidelities, first introduced in L. Calatroni et al. (SIAM J Imaging Sci 10(3):1196-1233, 2017). We establish convergence rates and a discrepancy principle for the infimal convolution fidelity and the inverse problem is solved by applying the primal-dual hybrid gradient (PDHG) algorithm in a novel way. Numerical experiments performed on simulated and real data show superior reconstruction results in comparison with other methods.

X-ray free-electron laser studies reveal correlated motion during isopenicillin N synthase catalysis

Isopenicillin N synthase (IPNS) catalyzes the unique reaction of l-δ-(α-aminoadipoyl)-l-cysteinyl-d-valine (ACV) with dioxygen giving isopenicillin N (IPN), the precursor of all natural penicillins and cephalosporins. X-ray free-electron laser studies including time-resolved crystallography and emission spectroscopy reveal how reaction of IPNS:Fe(II):ACV with dioxygen to yield an Fe(III) superoxide causes differences in active site volume and unexpected conformational changes that propagate to structurally remote regions. Combined with solution studies, the results reveal the importance of protein dynamics in regulating intermediate conformations during conversion of ACV to IPN. The results have implications for catalysis by multiple IPNS-related oxygenases, including those involved in the human hypoxic response, and highlight the power of serial femtosecond crystallography to provide insight into long-range enzyme dynamics during reactions presently impossible for nonprotein catalysts.

The impact of local assembly rules on RNA packaging in a T = 1 satellite plant virus

The vast majority of viruses consist of a nucleic acid surrounded by a protective icosahedral protein shell called the capsid. During viral infection of a host cell, the timing and efficiency of the assembly process is important for ensuring the production of infectious new progeny virus particles. In the class of single-stranded RNA (ssRNA) viruses, the assembly of the capsid takes place in tandem with packaging of the ssRNA genome in a highly cooperative co-assembly process. In simple ssRNA viruses such as the bacteriophage MS2 and small RNA plant viruses such as STNV, this cooperative process results from multiple interactions between the protein shell and sites in the RNA genome which have been termed packaging signals. Using a stochastic assembly algorithm which includes cooperative interactions between the protein shell and packaging signals in the RNA genome, we demonstrate that highly efficient assembly of STNV capsids arises from a set of simple local rules. Altering the local assembly rules results in different nucleation scenarios with varying assembly efficiencies, which in some cases depend strongly on interactions with RNA packaging signals. Our results provide a potential simple explanation based on local assembly rules for the ability of some ssRNA viruses to spontaneously assemble around charged polymers and other non-viral RNAs in vitro.

The microbiome and mosquito vectorial capacity: rich potential for discovery and translation

Microbiome research has gained considerable interest due to the emerging evidence of its impact on human and animal health. As in other animals, the gut-associated microbiota of mosquitoes affect host fitness and other phenotypes. It is now well established that microbes can alter pathogen transmission in mosquitoes, either positively or negatively, and avenues are being explored to exploit microbes for vector control. However, less attention has been paid to how microbiota affect phenotypes that impact vectorial capacity. Several mosquito and pathogen components, such as vector density, biting rate, survival, vector competence, and the pathogen extrinsic incubation period all influence pathogen transmission. Recent studies also indicate that mosquito gut-associated microbes can impact each of these components, and therefore ultimately modulate vectorial capacity. Promisingly, this expands the options available to exploit microbes for vector control by also targeting parameters that affect vectorial capacity. However, there are still many knowledge gaps regarding  mosquito-microbe interactions  that need to be addressed in order to exploit them efficiently. Here, we review current evidence of impacts of the microbiome on aspects of vectorial capacity, and we highlight likely opportunities for novel vector control strategies and areas where further studies are required. Video abstract.

Methods of Inactivation of SARS-CoV-2 for Downstream Biological Assays

The scientific community has responded to the coronavirus disease 2019 (COVID-19) pandemic by rapidly undertaking research to find effective strategies to reduce the burden of this disease. Encouragingly, researchers from a diverse array of fields are collectively working towards this goal. Research with infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is undertaken in high-containment laboratories; however, it is often desirable to work with samples at lower-containment levels. To facilitate the transfer of infectious samples from high-containment laboratories, we have tested methods commonly used to inactivate virus and prepare the sample for additional experiments. Incubation at 80°C, a range of detergents, Trizol reagents, and UV energies were successful at inactivating a high titer of SARS-CoV-2. Methanol and paraformaldehyde incubation of infected cells also inactivated the virus. These protocols can provide a framework for in-house inactivation of SARS-CoV-2 in other laboratories, ensuring the safe use of samples in lower-containment levels.

Gerrymandering and computational redistricting

Partisan gerrymandering poses a threat to democracy. Moreover, the complexity of the districting task may exceed human capacities. One potential solution is using computational models to automate the districting process by optimizing objective and open criteria, such as how spatially compact districts are. We formulated one such model that minimised pairwise distance between voters within a district. Using US Census Bureau data, we confirmed our prediction that the difference in compactness between the computed and actual districts would be greatest for states that are large and, therefore, difficult for humans to properly district given their limited capacities. The computed solutions highlighted differences in how humans and machines solve this task with machine solutions more fully optimised and displaying emergent properties not evident in human solutions. These results suggest a division of labour in which humans debate and formulate districting criteria whereas machines optimise the criteria to draw the district boundaries. We discuss how criteria can be expanded beyond notions of compactness to include other factors, such as respecting municipal boundaries, historic communities, and relevant legislation.