An ecological approach to assessing the epidemiology of antimicrobial resistance in animal and human populations

We examined long-term surveillance data on antimicrobial resistance (AMR) in Salmonella Typhimurium DT104 (DT104) isolates from concurrently sampled and sympatric human and animal populations in Scotland. Using novel ecological and epidemiological approaches to examine diversity, and phenotypic and temporal relatedness of the resistance profiles, we assessed the more probable source of resistance of these two populations. The ecological diversity of AMR phenotypes was significantly greater in human isolates than in animal isolates, at the resolution of both sample and population. Of 5200 isolates, there were 65 resistance phenotypes, 13 unique to animals, 30 unique to humans and 22 were common to both. Of these 22, 11 were identified first in the human isolates, whereas only five were identified first in the animal isolates. We conclude that, while ecologically connected, animals and humans have distinguishable DT104 communities, differing in prevalence, linkage and diversity. Furthermore, we infer that the sympatric animal population is unlikely to be the major source of resistance diversity for humans. This suggests that current policy emphasis on restricting antimicrobial use in domestic animals may be overly simplistic. While these conclusions pertain to DT104 in Scotland, this approach could be applied to AMR in other bacteria–host ecosystems.

Download Full-text

A Bayesian Latent Class Mixture Model With Censoring for Correlation Analysis in Antimicrobial Resistance Across Populations

10.21203/rs.3.rs-94417/v1 ◽

2020 ◽

Author(s):

Min Zhang ◽

Chong Wang ◽

Annette O'Connor

Keyword(s):

Antimicrobial Resistance ◽

Mixture Model ◽

Latent Class ◽

National Level ◽

Resistant Bacteria ◽

Human Populations ◽

Concentration Data ◽

Animal Populations ◽

Surveillance Programs ◽

And Control

Abstract Background: The emergence of antimicrobial resistance across populations is a global threat to public health. Surveillance programs often monitor human and animal populations to evaluate trends of emergence in these populations. Many national level antibiotic resistance surveillance programs quantify the proportion of resistant bacteria as a means of monitoring emergence and control measures. The reason for monitoring these different populations are many, including interest in similar changes in resistance which might provide insight into emergence and control options. Methods: In this research, we developed a method to quantify the correlation in antimicrobial resistance across populations, for the conventionally unnoticed mean shift of the susceptible bacteria. With the proposed Bayesian latent class mixture model with censoring and multivariate normal hierarchy, we address several challenges associated with analyzing the minimum inhibitory concentration data. Results: Application of this approach to the surveillance data from National Antimicrobial Resistance Monitoring System led to a detection of positive correlation in the central tendency of azithromycin resistance of the susceptible populations from Salmonella serotype Typhimurium across food animal and human populations. Conclusions: Our proposed approach has been shown to be accurate and superior to the naïve frequentist estimation by simulation studies. Further implementation of this Bayesian model could serve as a useful tool to indicate the co-existence of antimicrobial resistance, and potentially a need of clinical intervention.

Download Full-text

Elevated frequency of abnormalities in barn swallows from Chernobyl

Biology Letters ◽

10.1098/rsbl.2007.0136 ◽

2007 ◽

Vol 3 (4) ◽

pp. 414-417 ◽

Cited By ~ 50

Author(s):

A.P Møller ◽

T.A Mousseau ◽

F de Lope ◽

N Saino

Keyword(s):

Birth Defects ◽

Chernobyl Accident ◽

Long Term Results ◽

Human Populations ◽

Animal Population ◽

Free Living ◽

Morphological Abnormalities ◽

Barn Swallows ◽

Elevated Frequency

Ever since the Chernobyl accident in 1986, that contaminated vast areas in surrounding countries with radiation, abnormalities and birth defects have been reported in human populations. Recently, several studies suggested that the elevated frequency of such abnormalities can be attributed to poverty and stress in affected human populations. Here, we present long-term results for a free-living population of barn swallows, Hirundo rustica , demonstrating the presence of 11 morphological abnormalities in populations around Chernobyl, but much less frequently in an uncontaminated Ukrainian control population and three more distant control populations. The presence of these abnormalities in barn swallows is associated with reduced viability. These findings demonstrate a link between morphological abnormalities and radiation in an animal population that cannot be attributed to poverty and stress. The most parsimonious hypothesis for abnormalities in animal and human populations alike is that the effects are caused by the same underlying cause, viz. radiation derived from the Chernobyl accident.

Download Full-text

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

PLoS ONE ◽

10.1371/journal.pone.0244413 ◽

2021 ◽

Vol 16 (1) ◽

pp. e0244413

Author(s):

Beneditta Suwono ◽

Tim Eckmanns ◽

Heike Kaspar ◽

Roswitha Merle ◽

Benedikt Zacher ◽

...

Keyword(s):

Escherichia Coli ◽

Cluster Analysis ◽

One Health ◽

Average Distance ◽

Companion Animals ◽

Clinical Isolates ◽

Human Populations ◽

Animal Populations ◽

Routine Surveillance ◽

Animal Isolates

Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics—ampicillin, cefotaxime, ciprofloxacin and gentamicin–for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.

Download Full-text

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

10.21203/rs.3.rs-30292/v2 ◽

2020 ◽

Author(s):

Beneditta Suwono ◽

Tim Eckmanns ◽

Heike Kaspar ◽

Roswitha Merle ◽

Benedikt Zacher ◽

...

Keyword(s):

Escherichia Coli ◽

Cluster Analysis ◽

Average Distance ◽

Companion Animals ◽

Clinical Isolates ◽

Human Populations ◽

E Coli ◽

Animal Populations ◽

Routine Surveillance ◽

Animal Isolates

Abstract Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however, a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics - ampicillin, cefotaxime, ciprofloxacin and gentamicin – for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together and likewise separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might promote a better one-health approach for AR in Germany.

Download Full-text

A Bayesian latent class mixture model with censoring for correlation analysis in antimicrobial resistance across populations

BMC Medical Research Methodology ◽

10.1186/s12874-021-01384-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Min Zhang ◽

Chong Wang ◽

Annette M. O’Connor

Keyword(s):

Antimicrobial Resistance ◽

Mixture Model ◽

Latent Class ◽

National Level ◽

Resistant Bacteria ◽

Human Populations ◽

Concentration Data ◽

Animal Populations ◽

Surveillance Programs ◽

And Control

Abstract Background The emergence of antimicrobial resistance across populations is a global threat to public health. Surveillance programs often monitor human and animal populations to evaluate trends of emergence in these populations. Many national level antibiotic resistance surveillance programs quantify the proportion of resistant bacteria as a means of monitoring emergence and control measures. The reason for monitoring these different populations are many, including interest in similar changes in resistance which might provide insight into emergence and control options. Methods In this research, we developed a method to quantify the correlation in antimicrobial resistance across populations, for the conventionally unnoticed mean shift of the susceptible bacteria. With the proposed Bayesian latent class mixture model with censoring and multivariate normal hierarchy, we address several challenges associated with analyzing the minimum inhibitory concentration data. Results Application of this approach to the surveillance data from National Antimicrobial Resistance Monitoring System led to a detection of positive correlation in the central tendency of azithromycin resistance of the susceptible populations from Salmonella serotype Typhimurium across food animal and human populations. Conclusions Our proposed approach has been shown to be accurate and superior to the commonly used naïve estimation by simulation studies. Further implementation of this Bayesian model could serve as a useful tool to indicate the co-existence of antimicrobial resistance, and potentially a need of clinical intervention.

Download Full-text

Transcriptome and chromatin landscape of iNKT cells are shaped by subset differentiation and antigen exposure

Nature Communications ◽

10.1038/s41467-021-21574-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Mallory Paynich Murray ◽

Isaac Engel ◽

Grégory Seumois ◽

Sara Herrera-De la Mata ◽

Sandy Lucette Rosales ◽

...

Keyword(s):

T Cells ◽

Inkt Cells ◽

Phenotypic Analysis ◽

Follicular Helper ◽

Transcriptional Changes ◽

Innate Lymphocytes ◽

Killer T Cells ◽

Invariant Natural Killer ◽

Two Populations

AbstractInvariant natural killer T cells (iNKT cells) differentiate into thymic and peripheral NKT1, NKT2 and NKT17 subsets. Here we use RNA-seq and ATAC-seq analyses and show iNKT subsets are similar, regardless of tissue location. Lung iNKT cell subsets possess the most distinct location-specific features, shared with other innate lymphocytes in the lung, possibly consistent with increased activation. Following antigenic stimulation, iNKT cells undergo chromatin and transcriptional changes delineating two populations: one similar to follicular helper T cells and the other NK or effector like. Phenotypic analysis indicates these changes are observed long-term, suggesting that iNKT cells gene programs are not fixed, but they are capable of chromatin remodeling after antigen to give rise to additional subsets.

Download Full-text

Resistance and Adaptation of Bacteria to Non-Antibiotic Antibacterial Agents: Physical Stressors, Nanoparticles, and Bacteriophages

Antibiotics ◽

10.3390/antibiotics10040435 ◽

2021 ◽

Vol 10 (4) ◽

pp. 435

Author(s):

Sada Raza ◽

Kinga Matuła ◽

Sylwia Karoń ◽

Jan Paczesny

Keyword(s):

Antimicrobial Resistance ◽

Antibacterial Agents ◽

Uv Light ◽

Resistance Mechanisms ◽

Resistant Bacteria ◽

Physical Factors ◽

Defense Systems ◽

Drug Resistant Bacteria

Antimicrobial resistance is a significant threat to human health worldwide, forcing scientists to explore non-traditional antibacterial agents to support rapid interventions and combat the emergence and spread of drug resistant bacteria. Many new antibiotic-free approaches are being developed while the old ones are being revised, resulting in creating unique solutions that arise at the interface of physics, nanotechnology, and microbiology. Specifically, physical factors (e.g., pressure, temperature, UV light) are increasingly used for industrial sterilization. Nanoparticles (unmodified or in combination with toxic compounds) are also applied to circumvent in vivo drug resistance mechanisms in bacteria. Recently, bacteriophage-based treatments are also gaining momentum due to their high bactericidal activity and specificity. Although the number of novel approaches for tackling the antimicrobial resistance crisis is snowballing, it is still unclear if any proposed solutions would provide a long-term remedy. This review aims to provide a detailed overview of how bacteria acquire resistance against these non-antibiotic factors. We also discuss innate bacterial defense systems and how bacteriophages have evolved to tackle them.

Download Full-text

α-Oxoaldehyde metabolism and diabetic complications

Biochemical Society Transactions ◽

10.1042/bst0311358 ◽

2003 ◽

Vol 31 (6) ◽

pp. 1358-1363 ◽

Cited By ~ 80

Author(s):

P.J. Beisswenger ◽

S.K. Howell ◽

R.G. Nelson ◽

M. Mauer ◽

B.S. Szwergold

Keyword(s):

Diabetic Complications ◽

Complex Mixture ◽

Therapeutic Interventions ◽

Diabetic Patients ◽

Human Populations ◽

Control Mechanisms ◽

Protective Mechanisms ◽

Glycation End Products ◽

End Products

The factors responsible for variable susceptibility to diabetic nephropathy are not clear. According to the non-enzymatic glycation hypothesis, diabetes-related tissue damage occurs due to a complex mixture of toxic products, including α-oxoaldehydes, which are inherently toxic as well as serving as presursors for advanced glycation end-products. Protective mechanisms exist to control this unavoidable glycation, and these are determined by genetic or environmental factors that can regulate the concentrations of the reactive sugars or end-products. In diabetes these protective mechanisms become more important, since glycation stress increases, and less efficient defence systems against this stress could lead to diabetic complications. Some of these enzymatic control mechanisms, including those that regulate α-oxoaldehydes, have been identified. We have observed significant increases in production of the α-oxoaldehydes methylglyoxal and 3-deoxyglucosone in three human populations with biopsy-proven progression of nephropathy. The increase in methylglyoxal could be secondary to defects in downstream glycolytic enzymes (such as glyceraldehyde-3-phosphate dehydrogenase) that regulate its production, or in detoxification mechanisms such as glyoxalase. Other mechanisms, however, appear to be responsible for the observed increase in 3-deoxyglucosone levels. We present results of our studies on the mechanisms responsible for variable production of α-oxoaldehydes by measuring the activity and characteristics of these enzymes in cells from complication-prone and -resistant diabetic patients. New therapeutic interventions designed to control these endogenous mechanisms could potentially enhance protection against excessive glycation and prevent or reverse complications of long-term diabetes.

Download Full-text