Glycans in pathogenic bacteria - potential for targeted covalent therapeutics and imaging agents

A substantial obstacle to the existing treatment of bacterial diseases is the lack of specific probes that can be used to diagnose and treat pathogenic bacteria in a selective manner while leaving the microbiome largely intact. To tackle this problem, there is an urgent need to develop pathogen-specific therapeutics and diagnostics. Here, we describe recent evidence that indicates distinctive glycans found exclusively on pathogenic bacteria could form the basis of targeted therapeutic and diagnostic strategies. In particular, we highlight the use of metabolic oligosaccharide engineering to covalently deliver therapeutics and imaging agents to bacterial glycans. © 2014 The Partner Organisations

The freshwater Sponge Ephydatia Fluviatilis harbours diverse pseudomonas species (Gammaproteobacteria, Pseudomonadales) with broad-spectrum antimicrobial activity

Bacteria are believed to play an important role in the fitness and biochemistry of sponges (Porifera). Pseudomonas species (Gammaproteobacteria, Pseudomonadales) are capable of colonizing a broad range of eukaryotic hosts, but knowledge of their diversity and function in freshwater invertebrates is rudimentary. We assessed the diversity, structure and antimicrobial activities of Pseudomonas spp. in the freshwater sponge Ephydatia fluviatilis. Polymerase Chain Reaction - Denaturing Gradient Gel Electrophoresis (PCR-DGGE) fingerprints of the global regulator gene gacA revealed distinct structures between sponge-associated and free-living Pseudomonas communities, unveiling previously unsuspected diversity of these assemblages in freshwater. Community structures varied across E. fluviatilis specimens, yet specific gacA phylotypes could be detected by PCR-DGGE in almost all sponge individuals sampled over two consecutive years. By means of whole-genome fingerprinting, 39 distinct genotypes were found within 90 fluorescent Pseudomonas isolates retrieved from E. fluviatilis. High frequency of in vitro antibacterial (49%), antiprotozoan (35%) and anti-oomycetal (32%) activities was found among these isolates, contrasting less-pronounced basidiomycetal (17%) and ascomycetal (8%) antagonism. Culture extracts of highly predation-resistant isolates rapidly caused complete immobility or lysis of cells of the protozoan Colpoda steinii. Isolates tentatively identified as P. jessenii, P. protegens and P. oryzihabitans showed conspicuous inhibitory traits and correspondence with dominant sponge-associated phylotypes registered by cultivation-independent analysis. Our findings suggest that E. fluviatilis hosts both transient and persistent Pseudomonas symbionts displaying antimicrobial activities of potential ecological and biotechnological value.European Regional Development Fund (ERDF) through the COMPETE (Operational Competitiveness Programme); national funds through FCT (Foundation for Science and Technology) [PEst-C/MAR/LA0015/2011]; FCT-funded project [PTDC/BIA-MIC/3865/2012]; Federation of European Microbiological Societies (FEMS)info:eu-repo/semantics/publishedVersio

Concern with COVID-19 pandemic threat and attitudes towards immigrants: The mediating effect of the desire for tightness

Tightening social norms is thought to be adaptive for dealing with collective threat yet it may have negative consequences for increasing prejudice. The present research investigated the role of desire for cultural tightness, triggered by the COVID-19 pandemic, in increasing negative attitudes towards immigrants. We used participant-level data from 41 countries (N = 55,015) collected as part of the PsyCorona project, a crossnational longitudinal study on responses to COVID-19. Our predictions were tested through multilevel and SEM models, treating participants as nested within countries. Results showed that people’s concern with COVID19 threat was related to greater desire for tightness which, in turn, was linked to more negative attitudes towards immigrants. These findings were followed up with a longitudinal model (N = 2,349) which also showed that people’s heightened concern with COVID-19 in an earlier stage of the pandemic was associated with an increase in their desire for tightness and negative attitudes towards immigrants later in time. Our findings offer insight into the trade-offs that tightening social norms under collective threat has for human groups

‘We are all in the same boat’ : how societal discontent affects intention to help during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has caused a global health crisis. Consequently, many countries have adopted restrictive measures that caused a substantial change in society. Within this framework, it is reasonable to suppose that a sentiment of societal discontent, defined as generalized concern about the precarious state of society, has arisen. Literature shows that collectively experienced situations can motivate people to help each other. Since societal discontent is conceptualized as a collective phenomenon, we argue that it could influence intention to help others, particularly those who suffer from coronavirus. Thus, in the present study, we aimed (a) to explore the relationship between societal discontent and intention to help at the individual level and (b) to investigate a possible moderating effect of societal discontent at the country level on this relationship. To fulfil our purposes, we used data collected in 42 countries (N = 61,734) from the PsyCorona Survey, a cross-national longitudinal study. Results of multilevel analysis showed that, when societal discontent is experienced by the entire community, individuals dissatisfied with society are more prone to help others. Testing the model with longitudinal data (N = 3,817) confirmed our results. Implications for those findings are discussed in relation to crisis management. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement

.Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individuallevel injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant

Using Machine Learning to Identify Important Predictors of COVID-19 Infection Prevention Behaviors During the Early Phase of the Pandemic

Before vaccines for COVID-19 became available, a set of infection prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection prevention behavior in 56,072 participants across 28 countries, administered in March-May 2020. The machine- learning model predicted 52% of the variance in infection prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual- level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically-derived predictors were relatively unimportant

Politicization of COVID-19 health-protective behaviors in the United States: Longitudinal and cross-national evidence

During the initial phase of the COVID-19 pandemic, U.S. conservative politicians and the media downplayed the risk of both contracting COVID-19 and the effectiveness of recommended health behaviors. Health behavior theories suggest perceived vulnerability to a health threat and perceived effectiveness of recommended health-protective behaviors determine motivation to follow recommendations. Accordingly, we predicted that—as a result of politicization of the pandemic—politically conservative Americans would be less likely to enact recommended health-protective behaviors. In two longitudinal studies of U.S. residents, political conservatism was inversely associated with perceived health risk and adoption of health-protective behaviors over time. The effects of political orientation on health-protective behaviors were mediated by perceived risk of infection, perceived severity of infection, and perceived effectiveness of the health-protective behaviors. In a global cross-national analysis, effects were stronger in the U.S. (N = 10,923) than in an international sample (total N = 51,986), highlighting the increased and overt politicization of health behaviors in the U.S

COVID-19 stressors and health behaviors. A multilevel longitudinal study across 86 countries

Anxiety associated with the COVID-19 pandemic and home confinement has been associated with adverse health behaviors, such as unhealthy eating, smoking, and drinking. However, most studies have been limited by regional sampling, which precludes the examination of behavioral consequences associated with the pandemic at a global level. Further, few studies operationalized pandemic-related stressors to enable the investigation of the impact of different types of stressors on health outcomes. This study examined the association between perceived risk of COVID-19 infection and economic burden of COVID-19 with health-promoting and health-damaging behaviors using data from the PsyCorona Study: an international, longitudinal online study of psychological and behavioral correlates of COVID-19. Analyses utilized data from 7,402 participants from 86 countries across three waves of assessment between May 16 and June 13, 2020. Participants completed self-report measures of COVID-19 infection risk, COVID-19-related economic burden, physical exercise, diet quality, cigarette smoking, sleep quality, and binge drinking. Multilevel structural equation modeling analyses showed that across three time points, perceived economic burden was associated with reduced diet quality and sleep quality, as well as increased smoking. Diet quality and sleep quality were lowest among respondents who perceived high COVID-19 infection risk combined with high economic burden. Neither binge drinking nor exercise were associated with perceived COVID-19 infection risk, economic burden, or their interaction. Findings point to the value of developing interventions to address COVID-related stressors, which have an impact on health behaviors that, in turn, may 111 influence vulnerability to COVID-19 and other health outcomes