Prevalence and Severity of Symptoms 3 Months After Infection With SARS-CoV-2 Compared to Test-Negative and Population Controls in the Netherlands.

BACKGROUND: This prospective study assesses symptoms 3 months after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection compared to test-negative and population controls, and the effect of vaccination prior to infection. METHODS: Participants enrolled after a positive (cases) or negative (test-negative controls) SARS-CoV-2 test, or after invitation from the general population (population controls). After 3 months, participants indicated presence of 41 symptoms and severity of 4 symptoms. Permutation tests were used to select symptoms significantly elevated in cases compared to controls and to compare symptoms between cases that were vaccinated or unvaccinated prior to infection. RESULTS: In total, 9166 cases, 1698 symptomatic but test-negative controls, and 3708 population controls enrolled. At 3 months, 13 symptoms, and severity of fatigue, cognitive impairment, and dyspnea were significantly elevated incases compared to controls. Of cases, 48.5% reported ≥1 significantly elevated symptom compared to 29.8% of test-negative controls and 26.0% of population controls. Effect of vaccination could be determined for cases aged <65 years, and was significantly protective for loss of smell and taste but not for other symptoms. DISCUSSION: Three months after SARS-CoV-2 infection, almost half of cases report symptoms, which was higher than background prevalence and test-negative prevalence. Vaccination prior to infection was protective against loss of smell and taste in cases aged <65 years.

COVID-19 Vaccination Intent and Belief that Vaccination Will End the Pandemic.

High vaccination coverage is considered to be key in dealing with the coronavirus disease (COVID-19) pandemic. However, vaccine hesitancy can limit uptake. We examined the specific coronavirus beliefs that persons have regarding COVID-19 and COVID-19 vaccines and to what extent these beliefs explain COVID-19 vaccination intentions. We conducted a survey among 4,033 residents of the Netherlands that examined COVID-19 vaccination intentions and various beliefs. Random forest regression analysis explained 76% of the variance in vaccination intentions. The strongest determinant in the model was the belief the COVID-19 crisis will only end if many persons get vaccinated. Other strong determinants were beliefs about safety of vaccines, specifically in relation to vaccine development and approval process; (social) benefits of vaccination; social norms regarding vaccination behavior; and effectiveness of vaccines. We propose to address these specific beliefs in communications about COVID-19 vaccinations to stimulate vaccine uptake.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

A scenario modelling analysis to anticipate the impact of COVID-19 vaccination in adolescents and children on disease outcomes in the Netherlands, summer 2021.

BackgroundSince the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination.AimWe present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12-17-year-olds) and children (5-11-year-olds).MethodsWe developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per 100,000 people across vaccination scenarios, before the emergence of the Omicron variant.ResultsOur model projections showed that, on average, upon the release of all non-pharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30-49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups.ConclusionsWhile our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves.

A stochastic SIR network epidemic model with preventive dropping of edges.

A Markovian Susceptible [Formula: see text] Infectious [Formula: see text] Recovered (SIR) model is considered for the spread of an epidemic on a configuration model network, in which susceptible individuals may take preventive measures by dropping edges to infectious neighbours. An effective degree formulation of the model is used in conjunction with the theory of density dependent population processes to obtain a law of large numbers and a functional central limit theorem for the epidemic as the population size [Formula: see text], assuming that the degrees of individuals are bounded. A central limit theorem is conjectured for the final size of the epidemic. The results are obtained for both the Molloy-Reed (in which the degrees of individuals are deterministic) and Newman-Strogatz-Watts (in which the degrees of individuals are independent and identically distributed) versions of the configuration model. The two versions yield the same limiting deterministic model but the asymptotic variances in the central limit theorems are greater in the Newman-Strogatz-Watts version. The basic reproduction number [Formula: see text] and the process of susceptible individuals in the limiting deterministic model, for the model with dropping of edges, are the same as for a corresponding SIR model without dropping of edges but an increased recovery rate, though, when [Formula: see text], the probability of a major outbreak is greater in the model with dropping of edges. The results are specialised to the model without dropping of edges to yield conjectured central limit theorems for the final size of Markovian SIR epidemics on configuration-model networks, and for the size of the giant components of those networks. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations are good, even for moderate N.

Dangerous connections: on binding site models of infectious disease dynamics.

We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the 'outside world' on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of 'binding sites' for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as [Formula: see text], r, the final size, and the endemic equilibrium, in terms of the corresponding variables.

Computational approach to predict species-specific type III secretion system (T3SS) effectors using single and multiple genomes.

BACKGROUND: Many gram-negative bacteria use type III secretion systems (T3SSs) to translocate effector proteins into host cells. T3SS effectors can give some bacteria a competitive edge over others within the same environment and can help bacteria to invade the host cells and allow them to multiply rapidly within the host. Therefore, developing efficient methods to identify effectors scattered in bacterial genomes can lead to a better understanding of host-pathogen interactions and ultimately to important medical and biotechnological applications. RESULTS: We used 21 genomic and proteomic attributes to create a precise and reliable T3SS effector prediction method called Genome Search for Effectors Tool (GenSET). Five machine learning algorithms were trained on effectors selected from different organisms and a trained (voting) algorithm was then applied to identify other effectors present in the genome testing sets from the same (GenSET Phase 1) or different (GenSET Phase 2) organism. Although a select group of attributes that included the codon adaptation index, probability of expression in inclusion bodies, N-terminal disorder, and G + C content (filtered) were better at discriminating between positive and negative sets, algorithm performance was better when all 21 attributes (unfiltered) were used. Performance scores (sensitivity, specificity and area under the curve) from GenSET Phase 1 were better than those reported for six published methods. More importantly, GenSET Phase 1 ranked more known effectors (70.3%) in the top 40 ranked proteins and predicted 10-80% more effectors than three available programs in three of the four organisms tested. GenSET Phase 2 predicted 43.8% effectors in the top 40 ranked proteins when tested on four related or unrelated organisms. The lower prediction rates from GenSET Phase 2 may be due to the presence of different translocation signals in effectors from different T3SS families. CONCLUSIONS: The species-specific GenSET Phase 1 method offers an alternative approach to T3SS effector prediction that can be used with other published programs to improve effector predictions. Additionally, our approach can be applied to predict effectors of other secretion systems as long as these effectors have translocation signals embedded in their sequences.

Identification and functional characterization of the novel Edwardsiella tarda effector EseJ.

Edwardsiella tarda is a Gram-negative enteric pathogen that causes hemorrhagic septicemia in fish and gastro- and extraintestinal infections in humans. The type III secretion system (T3SS) of E. tarda has been identified as a key virulence factor that contributes to pathogenesis in fish. However, little is known about the associated effectors translocated by this T3SS. In this study, by comparing the profile of secreted proteins of the wild-type PPD130/91 and its T3SS ATPase ΔesaN mutant, we identified a new effector by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry. This effector consists of 1,359 amino acids, sharing high sequence similarity with Orf29/30 of E. tarda strain EIB202, and is renamed EseJ. The secretion and translocation of EseJ depend on the T3SS. A ΔeseJ mutant strain adheres to epithelioma papillosum of carp (EPC) cells 3 to 5 times more extensively than the wild-type strain does. EseJ inhibits bacterial adhesion to EPC cells from within bacterial cells. Importantly, the ΔeseJ mutant strain does not replicate efficiently in EPC cells and fails to replicate in J774A.1 macrophages. In infected J774A.1 macrophages, the ΔeseJ mutant elicits higher production of reactive oxygen species than wild-type E. tarda. The replication defect is consistent with the attenuation of the ΔeseJ mutant in the blue gourami fish model: the 50% lethal dose (LD50) of the ΔeseJ mutant is 2.34 times greater than that of the wild type, and the ΔeseJ mutant is less competitive than the wild type in mixed infection. Thus, EseJ represents a novel effector that contributes to virulence by reducing bacterial adhesion to EPC cells and facilitating intracellular bacterial replication.

SI infection on a dynamic partnership network: characterization of R0.

We model the spread of an SI (Susceptible → Infectious) sexually transmitted infection on a dynamic homosexual network. The network consists of individuals with a dynamically varying number of partners. There is demographic turnover due to individuals entering the population at a constant rate and leaving the population after an exponentially distributed time. Infection is transmitted in partnerships between susceptible and infected individuals. We assume that the state of an individual in this structured population is specified by its disease status and its numbers of susceptible and infected partners. Therefore the state of an individual changes through partnership dynamics and transmission of infection. We assume that an individual has precisely n 'sites' at which a partner can be bound, all of which behave independently from one another as far as forming and dissolving partnerships are concerned. The population level dynamics of partnerships and disease transmission can be described by a set of (n +1)(n +2) differential equations. We characterize the basic reproduction ratio R0 using the next-generation-matrix method. Using the interpretation of R0 we show that we can reduce the number of states-at-infection n to only considering three states-at-infection. This means that the stability analysis of the disease-free steady state of an (n +1)(n +2)-dimensional system is reduced to determining the dominant eigenvalue of a 3 × 3 matrix. We then show that a further reduction to a 2 × 2 matrix is possible where all matrix entries are in explicit form. This implies that an explicit expression for R0 can be found for every value of n.

Horizontal plasmid transfer promotes antibiotic resistance in selected bacteria in Chinese frog farms.

The emergence and dissemination of antibiotic resistance genes (ARGs) in the ecosystem are global public health concerns. One Health emphasizes the interconnectivity between different habitats and seeks to optimize animal, human, and environmental health. However, information on the dissemination of antibiotic resistance genes (ARGs) within complex microbiomes in natural habitats is scarce. We investigated the prevalence of antibiotic resistant bacteria (ARB) and the spread of ARGs in intensive bullfrog (Rana catesbeiana) farms in the Shantou area of China. Antibiotic susceptibilities of 361 strains, combined with microbiome analyses, revealed Escherichia coli, Edwardsiella tarda, Citrobacter and Klebsiella sp. as prevalent multidrug resistant bacteria on these farms. Whole genome sequencing of 95 ARB identified 250 large plasmids that harbored a wide range of ARGs. Plasmid sequences and sediment metagenomes revealed an abundance of tetA, sul1, and aph(3″)-Ib ARGs. Notably, antibiotic resistance (against 15 antibiotics) highly correlated with plasmid-borne rather than chromosome-borne ARGs. Based on sequence similarities, most plasmids (62%) fell into 32 distinct groups, indicating a potential for horizontal plasmid transfer (HPT) within the frog farm microbiome. HPT was confirmed in inter- and intra-species conjugation experiments. Furthermore, identical mobile ARGs, flanked by mobile genetic elements (MGEs), were found in different locations on the same plasmid, or on different plasmids residing in the same or different hosts. Our results suggest a synergy between MGEs and HPT to facilitate ARGs dissemination in frog farms. Mining public databases retrieved similar plasmids from different bacterial species found in other environmental niches globally. Our findings underscore the importance of HPT in mediating the spread of ARGs in frog farms and other microbiomes of the ecosystem.

Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing.

During the COVID-19 pandemic, contact tracing was used to identify individuals who had been in contact with a confirmed case so that these contacted individuals could be tested and quarantined to prevent further spread of the SARS-CoV-2 virus. Many countries developed mobile apps to find these contacted individuals faster. We evaluate the epidemiological effectiveness of the Dutch app CoronaMelder, where we measure effectiveness as the reduction of the reproduction number R. To this end, we use a simulation model of SARS-CoV-2 spread and contact tracing, informed by data collected during the study period (December 2020 - March 2021) in the Netherlands. We show that the tracing app caused a clear but small reduction of the reproduction number, and the magnitude of the effect was found to be robust in sensitivity analyses. The app could have been more effective if more people had used it, and if notification of contacts could have been done directly by the user and thus reducing the time intervals between symptom onset and reporting of contacts. The model has two innovative aspects: i) it accounts for the clustered nature of social networks and ii) cases can alert their contacts informally without involvement of health authorities or the tracing app.

Two-component PhoB-PhoR regulatory system and ferric uptake regulator sense phosphate and iron to control virulence genes in type III and VI secretion systems of Edwardsiella tarda.

Inorganic phosphate (P(i)) and iron are essential nutrients that are depleted by vertebrates as a protective mechanism against bacterial infection. This depletion, however, is sensed by some pathogens as a signal to turn on the expression of virulence genes. Here, we show that the PhoB-PhoR two-component system senses changes in P(i) concentration, whereas the ferric uptake regulator (Fur) senses changes in iron concentration in Edwardsiella tarda PPD130/91 to regulate the expression of type III and VI secretion systems (T3SS and T6SS) through an E. tarda secretion regulator, EsrC. In sensing low P(i) concentration, PhoB-PhoR autoregulates and activates the phosphate-specific transport operon, pstSCAB-phoU, by binding directly to the Pho box in the promoters of phoB and pstS. PhoB also binds with EsrC simultaneously on the promoter of an E. tarda virulence protein, evpA, to regulate directly the transcription of genes from T6SS. In addition, PhoB requires and interacts with PhoU to activate esrC and suppress fur indirectly through unidentified regulators. Fur, on the other hand, senses high iron concentration and binds directly to the Fur box in the promoter of evpP to inhibit EsrC binding to the same region. In addition, Fur suppresses transcription of phoB, pstSCAB-phoU, and esrC indirectly via unidentified regulators, suggesting negative cross-talk with the Pho regulon. Physical interactions exist between Fur and PhoU and between Fur and EsrC. Our findings suggest that T3SS and T6SS may carry out distinct roles in the pathogenicity of E. tarda by responding to different environmental factors.

Modelling varicella vaccination - What does a lack of surge in herpes zoster incidence tell us about exogenous boosting?

BACKGROUND: For decades, assessments of the impact of universal varicella vaccination on the epidemiology of varicella and herpes zoster (HZ) have been made using mathematical modelling. Decreased virus circulation and the resulting diminished exogenous boosting have been predicted to lead to a surge in HZ incidence. Lately, the exogenous boosting hypothesis has been challenged due to a lack of an extensive surge in HZ incidence in countries with, by now long-standing universal varicella vaccination. METHODS: In a deterministic compartmental transmission model of varicella zoster virus disease, we model various levels and duration of protection from boosting to explore the impact of successful childhood varicella vaccination on HZ incidence. RESULTS: Considering total HZ incidence, lifelong and strong protection from boosting give a stable incidence of HZ for about 60 years followed by a decline, whereas lifelong intermediate protection leads to a decline. So does weak protection of intermediate duration. Full and short protection, lead to a small surge, while full and intermediate protection lead to the largest HZ surge. HZ incidence by age group show that total incidence is the result of opposing increasing and decreasing trends in the various age groups over time. CONCLUSIONS: The absence of an extensive surge in HZ incidence after varicella vaccination can, especially during the first 20-30 years, occur in either strong, intermediate or weak boosting scenarios. The impact seems to depend on an interplay of the protective level and duration of the protection in determining the basic reactivation rate and the proportion of the population that is susceptible at the start of vaccination. However, the picture depends on whether the entire population or specific age groups are observed.

Versatile lifestyles of Edwardsiella: Free-living, pathogen, and core bacterium of the aquatic resistome.

Edwardsiella species in aquatic environments exist either as individual planktonic cells or in communal biofilms. These organisms encounter multiple stresses, include changes in salinity, pH, temperature, and nutrients. Pathogenic species such as E. piscicida, can multiply within the fish hosts. Additionally, Edwardsiella species (E. tarda), can carry antibiotic resistance genes (ARGs) on chromosomes and/or plasmids, that can be transmitted to the microbiome via horizontal gene transfer. E. tarda serves as a core in the aquatic resistome. Edwardsiela uses molecular switches (RpoS and EsrB) to control gene expression for survival in different environments. We speculate that free-living Edwardsiella can transition to host-living and vice versa, using similar molecular switches. Understanding such transitions can help us understand how other similar aquatic bacteria switch from free-living to become pathogens. This knowledge can be used to devise ways to slow down the spread of ARGs and prevent disease outbreaks in aquaculture and clinical settings.

Prevalence and determinants of persistent symptoms after infection with SARS-CoV-2: protocol for an observational cohort study (LongCOVID-study).

INTRODUCTION: A substantial proportion of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), report persisting symptoms weeks and months following acute infection. Estimates on prevalence vary due to differences in study designs, populations, heterogeneity of symptoms and the way symptoms are measured. Common symptoms include fatigue, cognitive impairment and dyspnoea. However, knowledge regarding the nature and risk factors for developing persisting symptoms is still limited. Hence, in this study, we aim to determine the prevalence, severity, risk factors and impact on quality of life of persisting symptoms in the first year following acute SARS-CoV-2 infection. METHODS AND ANALYSIS: The LongCOVID-study is both a prospective and retrospective cohort study being conducted in the Netherlands, with a one year follow-up. Participants aged 5 years and above, with self-reported positive or negative tests for SARS-CoV-2 will be included in the study. The primary outcome is the prevalence and severity of persistent symptoms in participants that tested positive for SARS-CoV-2 compared with controls. Symptom severity will be assessed for fatigue (Checklist Individual Strength (CIS subscale fatigue severity)), pain (Rand-36/SF-36 subscale bodily pain), dyspnoea (Medical Research Council (mMRC)) and cognitive impairment (Cognitive Failure Questionnaire (CFQ)). Secondary outcomes include effect of vaccination prior to infection on persistent symptoms, loss of health-related quality of life (HRQoL) and risk factors for persisting symptoms following infection with SARS-CoV-2. ETHICS AND DISSEMINATION: The Utrecht Medical Ethics Committee (METC) declared in February 2021 that the Medical Research Involving Human Subjects Act (WMO) does not apply to this study (METC protocol number 21-124/C). Informed consent is required prior to participation in the study. Results of this study will be submitted for publication in a peer-reviewed journal.

Temperature and Mg2+ sensing by a novel PhoP-PhoQ two-component system for regulation of virulence in Edwardsiella tarda.

The PhoP-PhoQ two-component system is commonly used by bacteria to sense environmental factors. Here we show that the PhoP-PhoQ system of Edwardsiella tarda detects changes in environmental temperature and Mg(2+) concentration as well as regulates the type III and VI secretion systems through direct activation of esrB. Protein secretion is activated from 23 to 35 °C or at low Mg(2+) concentrations, but it is suppressed at or below 20 °C, at or above 37 °C, or at high Mg(2+) concentrations. The effects of temperature and Mg(2+) concentration are additive. The PhoQ sensor domain has a low T(m) of 37.9 °C, and it detects temperatures through a conformational change of its secondary structure. Mutation of specific Pro or Thr residues increased the stability of the PhoQ sensor drastically, altering its temperature-sensing ability. The PhoQ sensor detects Mg(2+) concentration through the direct binding of Mg(2+) to a cluster of acidic residues (DDDSAD) and through changes that likely affect its tertiary structure. Here, we describe for the first time the use of PhoP-PhoQ as a temperature sensor for bacterial virulence control.

Burkholderiaceae and Multidrug Resistance Genes Are Key Players in Resistome Development in a Germfree Soil Model.

Assembly of a resistome in parallel with the establishment of a microbial community is not well understood. Germfree models can reveal microbiota interactions and shed light on bacterial colonization and resistance development under antibiotic pressure. In this study, we exposed germfree soil (GS), GS with diluted nontreated soil (DS), and nontreated soil (NS) to various concentrations of tetracycline (TET) in a nongermfree environment for 10 weeks, followed by 2 weeks of exposure to water. High-throughput sequencing was used to profile bacterial communities and antibiotic resistance genes (ARGs) in the soils. The initial bacterial loads were found to shape the profiles of bacterial communities and the resistomes. GS and DS treated with TET and the same soils left untreated had similar profiles, whereas NS showed different profiles. Soils with the same initial bacterial loads had their profiles shifted by TET treatment. Multidrug resistance (MDR) genes were the most abundant ARG types in all soils, with multidrug efflux pump genes being the discriminatory ARGs in GS regardless of different TET treatments and in GS, DS, and NS after TET. Furthermore, MDR genes were significantly enriched by TET treatment. In contrast, tetracycline resistance genes were either absent or low in relative abundance. The family Burkholderiaceae was predominant in all soils (except in NS treated with water) and was positively selected for by TET treatment. Most importantly, Burkholderiaceae were the primary carrier of ARGs, including MDR genes. IMPORTANCE This is the first study to examine how resistomes develop and evolve using GS. GS can be used to study the colonization and establishment of bacterial communities under antibiotic selection. Surprisingly, MDR genes were the main ARGs detected in GS, and TET treatments did not positively select for specific tetracycline resistance genes. Additionally, Burkholderiaceae were the key bacterial hosts for MDR genes in the current GS model under the conditions investigated. These results show that the family Burkholderiaceae underpins the development of resistome and serves as a source of ARGs. The ease of establishment of Burkholderiaceae and MDR genes in soils has serious implications for human health, since these bacteria are versatile and ubiquitous in the environment.

Distribution of antibiotic resistance genes in the environment.

The prevalence of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the microbiome is a major public health concern globally. Many habitats in the environment are under threat due to excessive use of antibiotics and evolutionary changes occurring in the resistome. ARB and ARGs from farms, cities and hospitals, wastewater treatment plants (WWTPs) or as water runoffs, may accumulate in water, soil, and air. We present a global picture of the resistome by examining ARG-related papers retrieved from PubMed and published in the last 30 years (1990-2020). Natural Language Processing (NLP) was used to retrieve 496,640 papers, out of which 9374 passed the filtering test and were further analyzed to determine the distribution and diversity of ARG subtypes. The papers revealed seven major antibiotic families together with their respective ARG subtypes in different habitats on six continents. Asia, especially China, had the highest number of ARGs related papers compared to other countries/regions/continents. ARGs belonging to multidrug, glycopeptide, and ß-lactam families were the most common in reports from hospitals and sulfonamide and tetracycline families were common in reports from farms, WWTPs, water and soil. We also highlight the 'omics' tools used in resistome research, describe some factors that shape the development of resistome, and suggest future work needed to better understand the resistome. The goal was to show the global nature of ARB and ARGs in order to encourage collaborate research efforts aimed at reducing the negative impacts of antibiotic resistance on the One Health concept.

EseG, an effector of the type III secretion system of Edwardsiella tarda, triggers microtubule destabilization.

Edwardsiella tarda is a Gram-negative enteric pathogen that causes hemorrhagic septicemia in fish and both gastrointestinal and extraintestinal infections in humans. A type III secretion system (T3SS) was recently shown to contribute to pathogenesis, since deletions of various T3SS genes increased the 50% lethal dose (LD(50)) by about 1 log unit in the blue gourami infection model. In this study, we report EseG as the first identified effector protein of T3SS. EseG shares partial homology with two Salmonella T3SS effectors (SseG and SseF) over a conserved domain (amino acid residues 142 to 192). The secretion of EseG is dependent on a functional T3SS and, in particular, requires the chaperone EscB. Experiments using TEM-1 ß-lactamase as a fluorescence-based reporter showed that EseG was translocated into HeLa cells at 35°C. Fractionation of infected HeLa cells demonstrated that EseG was localized to the host membrane fraction after translocation. EseG is able to disassemble microtubule structures when overexpressed in mammalian cells. This phenotype may require a conserved motif of EseG (EseG(142-192)), since truncated versions of EseG devoid of this motif lose their ability to cause microtubule destabilization. By demonstrating the function of EseG, our study contributes to the understanding of E. tarda pathogenesis. Moreover, the approach established in this study to identify type III effectors can be used to identify and characterize more type III and possible type VI effectors in Edwardsiella.

Identification and characterization of the lipid-binding property of GrlR, a locus of enterocyte effacement regulator.

Lipocalins are a broad family of proteins identified initially in eukaryotes and more recently in Gram-negative bacteria. The functions of lipocalin or lipid-binding proteins are often elusive and very diverse. Recently, we have determined the structure of GrlR (global regulator of LEE repressor), which plays a key role in the regulation of LEE (locus of enterocyte effacement) proteins. GrlR adopts a lipocalin-like fold that is composed of an eight-stranded beta-barrel followed by an alpha-helix at the C-terminus. GrlR has a highly hydrophobic cavity region and could be a potential transporter of lipophilic molecules. To verify this hypothesis, we carried out structure-based analysis of GrlR, determined the structure of the lipid-GrlR complex and measured the binding of lipid to recombinant GrlR by ITC (isothermal titration calorimetry). In addition, we identified phosphatidylglycerol and phosphatidylethanolamine as the endogenously bound lipid species of GrlR using electrospray-ionization MS. Furthermore, we have shown that the lipid-binding property of GrlR is similar to that of its closest lipocalin structural homologue, beta-lactoglobulin. Our studies demonstrate the hitherto unknown lipid-binding property of GrlR.