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

The Vietnam Initiative on Zoonotic Infections (VIZIONS): A Strategic Approach to Studying Emerging Zoonotic Infectious Diseases

The effect of newly emerging or re-emerging infectious diseases of zoonotic origin in human populations can be potentially catastrophic, and large-scale investigations of such diseases are highly challenging. The monitoring of emergence events is subject to ascertainment bias, whether at the level of species discovery, emerging disease events, or disease outbreaks in human populations. Disease surveillance is generally performed post hoc, driven by a response to recent events and by the availability of detection and identification technologies. Additionally, the inventory of pathogens that exist in mammalian and other reservoirs is incomplete, and identifying those with the potential to cause disease in humans is rarely possible in advance. A major step in understanding the burden and diversity of zoonotic infections, the local behavioral and demographic risks of infection, and the risk of emergence of these pathogens in human populations is to establish surveillance networks in populations that maintain regular contact with diverse animal populations, and to simultaneously characterize pathogen diversity in human and animal populations. Vietnam has been an epicenter of disease emergence over the last decade, and practices at the human/animal interface may facilitate the likelihood of spillover of zoonotic pathogens into humans. To tackle the scientific issues surrounding the origins and emergence of zoonotic infections in Vietnam, we have established The Vietnam Initiative on Zoonotic Infections (VIZIONS). This countrywide project, in which several international institutions collaborate with Vietnamese organizations, is combining clinical data, epidemiology, high-throughput sequencing, and social sciences to address relevant one-health questions. Here, we describe the primary aims of the project, the infrastructure established to address our scientific questions, and the current status of the project. Our principal objective is to develop an integrated approach to the surveillance of pathogens circulating in both human and animal populations and assess how frequently they are exchanged. This infrastructure will facilitate systematic investigations of pathogen ecology and evolution, enhance understanding of viral cross-species transmission events, and identify relevant risk factors and drivers of zoonotic disease emergence

Orientational Effects and Random Mixing in 1-Alkanol + Alkanone Mixtures

1-Alkanol + alkanone systems have been investigated through the data analysis of molar excess functions, enthalpies, isobaric heat capacities, volumes and entropies, and using the Flory model and the formalism of the concentrationconcentration structure factor (SCC(0)). The enthalpy of the hydroxyl-carbonyl interactions has been evaluated. These interactions are stronger in mixtures with shorter alcohols (methanol-1-butanol) and 2-propanone or 2-butanone. However, effects related to the self-association of alcohols and to solvation between unlike molecules are of minor importance when compared with those which arise from dipolar interactions. Physical interactions are more relevant in mixtures with longer 1-alkanols. The studied systems are characterized by large structural effects. The variation of the molar excess enthalpy with the alcohol size along systems with a given ketone or with the alkanone size in solutions with a given alcohol are discussed in terms of the different contributions to this excess function. Mixtures with methanol show rather large orientational effects. The random mixing hypothesis is attained to a large extent for mixtures with 1-alkanols ≠ methanol and 2-alkanones. Steric effects and cyclization lead to stronger orientational effects in mixtures with 3-pentanone, 4-heptanone, or cyclohexanone. The increase of temperature weakens orientational effects. Results from SCC(0) calculations show that homocoordination is predominant and support conclusions obtained from the Flory model.Ministerio de Ciencia e Innovación, under Project FIS2010-1695

‘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

Cross Adaptation - Heat and Cold Adaptation to Improve Physiological and Cellular Responses to Hypoxia

To prepare for extremes of heat, cold or low partial pressures of O2, humans can undertake a period of acclimation or acclimatization to induce environment specific adaptations e.g. heat acclimation (HA), cold acclimation (CA), or altitude training. Whilst these strategies are effective, they are not always feasible, due to logistical impracticalities. Cross adaptation is a term used to describe the phenomenon whereby alternative environmental interventions e.g. HA, or CA, may be a beneficial alternative to altitude interventions, providing physiological stress and inducing adaptations observable at altitude. HA can attenuate physiological strain at rest and during moderate intensity exercise at altitude via adaptations allied to improved oxygen delivery to metabolically active tissue, likely following increases in plasma volume and reductions in body temperature. CA appears to improve physiological responses to altitude by attenuating the autonomic response to altitude. While no cross acclimation-derived exercise performance/capacity data have been measured following CA, post-HA improvements in performance underpinned by aerobic metabolism, and therefore dependent on oxygen delivery at altitude, are likely. At a cellular level, heat shock protein responses to altitude are attenuated by prior HA suggesting that an attenuation of the cellular stress response and therefore a reduced disruption to homeostasis at altitude has occurred. This process is known as cross tolerance. The effects of CA on markers of cross tolerance is an area requiring further investigation. Because much of the evidence relating to cross adaptation to altitude has examined the benefits at moderate to high altitudes, future research examining responses at lower altitudes should be conducted given that these environments are more frequently visited by athletes and workers. Mechanistic work to identify the specific physiological and cellular pathways responsible for cross adaptation between heat and altitude, and between cold and altitude, is warranted, as is exploration of benefits across different populations and physical activity profiles

.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