Mitra, R. M. | Search bioRxiv

bioRxiv2021

Stratified Random Sampling Methodology for Observing Community Mask Use within Indoor Settings: Results from Louisville, Kentucky during the COVID-19 Pandemic

Wearing a facial mask can limit COVID-19 transmission. Measurements of communities mask use behavior have mostly relied on self-report. This studys objective was to devise a method for measuring the prevalence of mask-wearing and proper mask use in indoor public areas without relying on self-report. A stratified random sample of retail trade stores (public areas) in Louisville, Kentucky, USA, was selected and targeted for observation by trained surveyors during December 14-20, 2020. The stratification allowed for investigating mask use behavior by city district, retail trade group, and public area size. The average mask use prevalence among observed visitors of the 382 visited public areas was 96%, while the average prevalence of proper use was 86%. In 17% of the public areas, at least one unmasked visitor was among the observed visitors; in 48%, at least one improperly masked visitor was observed. The average mask use among staff was 92%, but unmasked staff were observed in fewer public areas, as an unmasked staff member was observed in 11% of the visited public areas. The average prevalence of proper make use among staff was 87%, similar to the average among visitors. However, the percentage of public areas where at least one improperly masked staff was observed was 33. Significant disparities in mask use and its proper use were observed among both visitors and staff by public area size, retail trade type, and geographical area. Observing unmasked and incorrectly masked visitors was more common in small (less than 1500 square feet) public areas than larger ones, also in food and grocery stores than other retail stores. Also, the majority of the observed unmasked persons were male and middle age adults.

scientific communication and education↗

bioRxiv2019

EffectorK, a comprehensive resource to mine for pathogen effector targets in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogens own benefit. However, effectors can also be recognized by host immune proteins leading to the activation of defense responses. Effectors are thus essential components in determining the outcome of plant-pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal and animal pathogens. This network contains our experimental data and protein-protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis-Arabidopsis and 1,300 Arabidopsis-effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis targets suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector targets, particularly effector hubs and bacterial core effector targets, occupy important positions for network organization as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data. Author summaryPlant pests and diseases caused by bacteria, oomycetes, fungi or animals are threatening food security worldwide. Understanding how these pathogens infect and manipulate the host is key to develop sustainable crop resistance in the long term. Effector proteins are secreted by pathogens to subvert the host immune responses. The roles of several effector proteins have been described; however, it is yet poorly understood how effectors interact with host proteins at a global level. To address this issue, we have generated EffectorK, an interactive database focused on the model plant species Arabidopsis thaliana. This database contains manually curated Arabidopsis-effector protein interactions from the available literature on a wide variety of pathogens. It also contains new experimental data on effectors from two vascular pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. This work integrates all the gathered knowledge over the last decades and allows to identify general patterns of how effectors interact with the host proteome. This knowledge is easily accessible and searchable at www.effectork.org.

plant biology↗