The surface of insects is coated in cuticular hydrocarbons (CHCs); variations in the composition of this layer affect a range of traits including adaptation to arid environments and defence against pathogens and toxins. In the African malaria vector, Anopheles gambiae quantitative and qualitative variance in CHC composition have been associated with speciation, ecological habitat and insecticide resistance. Understanding how these modifications arise will inform us of how mosquitoes are responding to climate change and vector control interventions. CHCs are synthesised in sub-epidermal cells called oenocytes that are very difficult to isolate from surrounding tissues. Here we utilise a transgenic line with fluorescent oenocytes to purify these cells for the first time. Comparative transcriptomics revealed the enrichment of biological processes related to long chain fatty acyl-CoA biosynthesis and elongation of mono-, poly-unsaturated and saturated fatty acids and enabled us to delineate, and partially validate, the hydrocarbon biosynthetic pathway in An. gambiae.
Transcriptome sequencing has been deposited in the European Nucleotide Archive (ENA), under PRJEB37240 project.All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1,2,3 and 5.
- Linda Grigoraki
- Linda Grigoraki
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Malcolm J McConville, The University of Melbourne, Australia
© 2020, Grigoraki et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Detecting factors associated with transmission is important to understand disease epidemics, and to design effective public health measures. Clustering and terminal branch lengths (TBL) analyses are commonly applied to genomic data sets of Mycobacterium tuberculosis (MTB) to identify sub-populations with increased transmission. Here, I used a simulation-based approach to investigate what epidemiological processes influence the results of clustering and TBL analyses, and whether differences in transmission can be detected with these methods. I simulated MTB epidemics with different dynamics (latency, infectious period, transmission rate, basic reproductive number R0, sampling proportion, sampling period, and molecular clock), and found that all considered factors, except for the length of the infectious period, affect the results of clustering and TBL distributions. I show that standard interpretations of this type of analyses ignore two main caveats: (1) clustering results and TBL depend on many factors that have nothing to do with transmission, (2) clustering results and TBL do not tell anything about whether the epidemic is stable, growing, or shrinking, unless all the additional parameters that influence these metrics are known, or assumed identical between sub-populations. An important consequence is that the optimal SNP threshold for clustering depends on the epidemiological conditions, and that sub-populations with different epidemiological characteristics should not be analyzed with the same threshold. Finally, these results suggest that different clustering rates and TBL distributions, that are found consistently between different MTB lineages, are probably due to intrinsic bacterial factors, and do not indicate necessarily differences in transmission or evolutionary success.
In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.