Microbes in the 21st century are understood as symbionts ‘completing’ the human ‘superorganism’ (... more Microbes in the 21st century are understood as symbionts ‘completing’ the human ‘superorganism’ (Homo sapiens plus microbial partners-in-health). This paper addresses a significant paradox: despite the vast majority of our genes being microbial, the lack of routine safety testing for the microbiome has led to unintended collateral side effects from pharmaceuticals that can damage the microbiome and inhibit innate ‘colonization resistance’ against pathobionts. Examples are discussed in which a Microbiome First Medicine approach provides opportunities to ‘manage our microbes’ holistically, repair dysbiotic superorganisms, and restore health and resilience in the gut and throughout the body: namely, managing nosocomial infections for Clostridioides difficile and Staphylococcus aureus and managing the gut and neural systems (gut–brain axis) in autism spectrum disorder. We then introduce a risk analysis tool: the evidence map. This ‘mapping’ tool was recently applied by us to evaluate ev...
An evidence map is visualized as a starting point for deliberations by trans-disciplinary stakeho... more An evidence map is visualized as a starting point for deliberations by trans-disciplinary stakeholders, including microbiologists with interests in the evidence and its influence on health and safety. Available evidence for microbial benefits and risks of the breastmilk ecosystem was structured as an evidence map using established risk analysis methodology. The evidence map based on the published literature and reports included the evidence basis, pro- and contra-arguments with supporting and attenuating evidence, supplemental studies on mechanisms, overall conclusions, and remaining uncertainties. The evidence basis for raw breastmilk included one benefit–risk assessment, systematic review, and systematic review/meta-analysis, and two cohort studies. The evidence basis for benefits was clear, convincing, and conclusive, with supplemental studies on plausible mechanisms attributable to biologically active raw breastmilk. Limited evidence was available to assess microbial risks assoc...
Many investigations of the interactions of microbial competitors in the gastrointestinal tract us... more Many investigations of the interactions of microbial competitors in the gastrointestinal tract used continuous-flow anaerobic cultures. The simulation reported here was a deterministic 11-compartment model coded by using the C programming language and based on parameters from published in vitro studies and assumptions were data were unavailable. The resource compartments were glucose, lactose and sucrose, starch, sorbose, and serine. Six microbial competitors included indigenous nonpathogenic colonizers of the human gastrointestinal tract (Escherichia coli, Enterobacter aerogenes, Bacteroids ovatus, Fusobacterium varium, and Enterococcus faecalis) and the potential human enteropathogen Salmonella typhimurium. Flows of carbon from the resources to the microbes were modified by resource and space controls. Partitioning of resources to the competitors that could utilize them was calculated at each iteration on the basis of availability of all resources by feeding preference functions. ...
Until now, there have been no measurements of the in vivo stability of red-blood-cell-bound C3d a... more Until now, there have been no measurements of the in vivo stability of red-blood-cell-bound C3d and C4d subfragments of the third and fourth components of human complement. We have recently described a radiolabeled antiantiglobulin method for measuring RBC-bound C3d and have demonstrated that small amounts of C3d are present on RBC of all normal subjects tested. In the present study, the method was applied to follow the increments above baseline of RBC-bound C3d and C4d produced by autotransfusing 3 normal volunteers with 160–200 ml of RBC strongly coated in vitro by C3d and C4d. Posttransfusion measurements were carried out over 21–34 days. Immediate and long-term in vivo survival of the transfused RBC was unimpaired by C3d and C4d coating. Of the bound C3d antigen, 85%–95% disappeared from circulating RBC in 5–8 days; the remainder disappeared more slowly, with half-times in the range of 8–29 days. C4d antigen disappeared substantially more slowly, describable by a single exponent...
Procedures of sampling and measurement contribute variability and uncertainty to exposure models ... more Procedures of sampling and measurement contribute variability and uncertainty to exposure models that predict incidence and levels of organisms in food products. This paper focuses on methods that account for sampling and measurement error in fitting distributions of organisms in food products for use in exposure models for microbial risk assessment. Define y to be a measured density on a sample selected with stipulated probability from a population, and define x to be the “true” density for that sample. Designate the conditional distribution of y given the sample with “true” value x as g(y|x), and let F(x) be the unknown cumulative density of x. The distribution of the observed values y, h(y), can be expressed through the integral equation h(y) = Sg(y|x) dF{x). Knowledge of g(y|x) and h(y) enables an estimate of the unknown distribution of the organism's F(x). In applications to risk assessment, use of continuous distributions described by a few parameters is desirable. Also de...
Great uncertainty exists in conducting dose-response assessment for microbial pathogens. The data... more Great uncertainty exists in conducting dose-response assessment for microbial pathogens. The data to support quantitative modeling of dose-response relationships are meager. Our philosophy in developing methodology to conduct microbial risk assessments has been to rely on data analysis and formal inferencing from the available data in constructing dose-response and exposure models. The probability of illness is a complex function of factors associated with the disease triangle: the host, the pathogen, and the environment including the food vehicle and indigenous microbial competitors. The epidemiological triangle and interactions between the components of the triangle are used to illustrate key issues in dose-response modeling that impact the estimation of risk and attendant uncertainty. Distinguishing between uncertainty (what is unknown) and variability (heterogeneity) is crucial in risk assessment. Uncertainty includes components that are associated with (i) parameter estimation ...
Human and Ecological Risk Assessment: An International Journal, 2017
ABSTRACT Microbial risk assessors often make simplifying assumptions that lead to the selection o... more ABSTRACT Microbial risk assessors often make simplifying assumptions that lead to the selection of simple concave functions with low-dose linearity, consistent with no-threshold and single-hit hypotheses, as default dose–response model forms. However, evidence is accumulating as the “microbiome revolution” progresses that challenge these assumptions that influence the estimates of the nature and magnitude of uncertainties associated with microbial risks. Scientific advances in the knowledge of the human “superorganism” (hybrid consortium of human plus microbial communities that cooperatively regulates health and disease) enable the design of definitive studies to estimate the pathogen doses overcome by the innate defenses, including the protective microbiota. The systematic investigation of the events of non-typhoid salmonellosis in humans undertaken nearly 2 decades ago was updated to incorporate recent scientific advances in the understanding of impact of the healthy superorganism that strengthens and extends the biological motivations for sublinear or convex dose–response curves in microbial risk assessment. The knowledge of colonization resistance (innate protection of the human superorganism from low doses of ingested pathogens) and microbiota-mediated clearance is advancing mechanistically for many pathosystems. However, until more detailed mechanistic data become available for salmonellosis, the consideration of a variety of empirical model forms is essential for depicting the uncertainty of the “true” dose–response model.
An assessment of the risk of illness associated with Escherichia coli O157:H7 in ground beef was ... more An assessment of the risk of illness associated with Escherichia coli O157:H7 in ground beef was drafted in 2001. The exposure assessment considers farm, slaughter, and preparation factors that influence the likelihood of humans consuming ground beef servings containing E. coli O157:H7 and the number of cells in a contaminated serving. Apparent seasonal differences in prevalence of cattle infected with E. coli O157:H7 corresponded to seasonal differences in human exposure. The model predicts that on average 0.018% of servings consumed during June through September and 0.007% of servings consumed during the remainder of the year are contaminated with one or more E. coli O157:H7 cells. This exposure risk is combined with the probability of illness given exposure (i.e., dose response) to estimate a U.S. population risk of illness of nearly one illness in each 1 million (9.6 × 10−7) servings of ground beef consumed. Uncertainty about this risk ranges from about 0.33 illness in every 1 m...
Risk analysis : an official publication of the Society for Risk Analysis, Jan 25, 2017
Survival models are developed to predict response and time-to-response for mortality in rabbits f... more Survival models are developed to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple-dose data set to predict the probability of death through specifying functions of dose response and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) is an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed use different underlying dose-response functions and use the assumption that, in a multiple-dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this article. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approac...
Human individuals and societies have been identifying risks and managing them since ancient times... more Human individuals and societies have been identifying risks and managing them since ancient times (When you build a new house, you shall make a parapet for your roof, so that you shall not put blood in your house if [when] one falls from it. Deut. 22: 8) by various ...
Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approa... more Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approach to microbial risk assessment is presented that employs data analysis for developing parsimonious models and accounts formally for the variability and uncertainty of model inputs using analysis of variance and Monte Carlo simulation. The purpose of the paper is to raise and examine issues in conducting microbial risk assessments. The enteric pathogen Escherichia coli O157:H7 was selected as an example for this study due to its significance to public health. The framework for our work is consistent with the risk assessment components described by the National Research Council in 1983 (hazard identification; exposure assessment; dose‐response assessment; and risk characterization). Exposure assessment focuses on hamburgers, cooked a range of temperatures from rare to well done, the latter typical for fast food restaurants. Features of the model include predictive microbiology components ...
This guest editorial introduces a special collection of four manuscripts that offer a new perspec... more This guest editorial introduces a special collection of four manuscripts that offer a new perspective in Risk Analysis relating to the evolving interdisciplinary field of microbial risk assessment. The objective of the collection was to focus on the strengths and limitations of ...
Journal of Toxicology and Environmental Health, Part A, 2004
In order to estimate the risk or probability of adverse events in risk assessment, it is necessar... more In order to estimate the risk or probability of adverse events in risk assessment, it is necessary to identify the important variables that contribute to the risk and provide descriptions of distributions of these variables for well-defined populations. One component of modeling dose response that can create uncertainty is the inherent genetic variability among pathogenic bacteria. For many microbial risk assessments, the "default" assumption used for dose response does not account for strain or serotype variability in pathogenicity and virulence, other than perhaps, recognizing the existence of avirulent strains. However, an examination of data sets from human clinical trials in which Salmonella spp. and Campylobacter jejuni strains were administered reveals significant strain differences. This article discusses the evidence for strain variability and concludes that more biologically based alternatives are necessary to replace the default assumptions commonly used in microbial risk assessment, specifically regarding strain variability.
Microbes in the 21st century are understood as symbionts ‘completing’ the human ‘superorganism’ (... more Microbes in the 21st century are understood as symbionts ‘completing’ the human ‘superorganism’ (Homo sapiens plus microbial partners-in-health). This paper addresses a significant paradox: despite the vast majority of our genes being microbial, the lack of routine safety testing for the microbiome has led to unintended collateral side effects from pharmaceuticals that can damage the microbiome and inhibit innate ‘colonization resistance’ against pathobionts. Examples are discussed in which a Microbiome First Medicine approach provides opportunities to ‘manage our microbes’ holistically, repair dysbiotic superorganisms, and restore health and resilience in the gut and throughout the body: namely, managing nosocomial infections for Clostridioides difficile and Staphylococcus aureus and managing the gut and neural systems (gut–brain axis) in autism spectrum disorder. We then introduce a risk analysis tool: the evidence map. This ‘mapping’ tool was recently applied by us to evaluate ev...
An evidence map is visualized as a starting point for deliberations by trans-disciplinary stakeho... more An evidence map is visualized as a starting point for deliberations by trans-disciplinary stakeholders, including microbiologists with interests in the evidence and its influence on health and safety. Available evidence for microbial benefits and risks of the breastmilk ecosystem was structured as an evidence map using established risk analysis methodology. The evidence map based on the published literature and reports included the evidence basis, pro- and contra-arguments with supporting and attenuating evidence, supplemental studies on mechanisms, overall conclusions, and remaining uncertainties. The evidence basis for raw breastmilk included one benefit–risk assessment, systematic review, and systematic review/meta-analysis, and two cohort studies. The evidence basis for benefits was clear, convincing, and conclusive, with supplemental studies on plausible mechanisms attributable to biologically active raw breastmilk. Limited evidence was available to assess microbial risks assoc...
Many investigations of the interactions of microbial competitors in the gastrointestinal tract us... more Many investigations of the interactions of microbial competitors in the gastrointestinal tract used continuous-flow anaerobic cultures. The simulation reported here was a deterministic 11-compartment model coded by using the C programming language and based on parameters from published in vitro studies and assumptions were data were unavailable. The resource compartments were glucose, lactose and sucrose, starch, sorbose, and serine. Six microbial competitors included indigenous nonpathogenic colonizers of the human gastrointestinal tract (Escherichia coli, Enterobacter aerogenes, Bacteroids ovatus, Fusobacterium varium, and Enterococcus faecalis) and the potential human enteropathogen Salmonella typhimurium. Flows of carbon from the resources to the microbes were modified by resource and space controls. Partitioning of resources to the competitors that could utilize them was calculated at each iteration on the basis of availability of all resources by feeding preference functions. ...
Until now, there have been no measurements of the in vivo stability of red-blood-cell-bound C3d a... more Until now, there have been no measurements of the in vivo stability of red-blood-cell-bound C3d and C4d subfragments of the third and fourth components of human complement. We have recently described a radiolabeled antiantiglobulin method for measuring RBC-bound C3d and have demonstrated that small amounts of C3d are present on RBC of all normal subjects tested. In the present study, the method was applied to follow the increments above baseline of RBC-bound C3d and C4d produced by autotransfusing 3 normal volunteers with 160–200 ml of RBC strongly coated in vitro by C3d and C4d. Posttransfusion measurements were carried out over 21–34 days. Immediate and long-term in vivo survival of the transfused RBC was unimpaired by C3d and C4d coating. Of the bound C3d antigen, 85%–95% disappeared from circulating RBC in 5–8 days; the remainder disappeared more slowly, with half-times in the range of 8–29 days. C4d antigen disappeared substantially more slowly, describable by a single exponent...
Procedures of sampling and measurement contribute variability and uncertainty to exposure models ... more Procedures of sampling and measurement contribute variability and uncertainty to exposure models that predict incidence and levels of organisms in food products. This paper focuses on methods that account for sampling and measurement error in fitting distributions of organisms in food products for use in exposure models for microbial risk assessment. Define y to be a measured density on a sample selected with stipulated probability from a population, and define x to be the “true” density for that sample. Designate the conditional distribution of y given the sample with “true” value x as g(y|x), and let F(x) be the unknown cumulative density of x. The distribution of the observed values y, h(y), can be expressed through the integral equation h(y) = Sg(y|x) dF{x). Knowledge of g(y|x) and h(y) enables an estimate of the unknown distribution of the organism's F(x). In applications to risk assessment, use of continuous distributions described by a few parameters is desirable. Also de...
Great uncertainty exists in conducting dose-response assessment for microbial pathogens. The data... more Great uncertainty exists in conducting dose-response assessment for microbial pathogens. The data to support quantitative modeling of dose-response relationships are meager. Our philosophy in developing methodology to conduct microbial risk assessments has been to rely on data analysis and formal inferencing from the available data in constructing dose-response and exposure models. The probability of illness is a complex function of factors associated with the disease triangle: the host, the pathogen, and the environment including the food vehicle and indigenous microbial competitors. The epidemiological triangle and interactions between the components of the triangle are used to illustrate key issues in dose-response modeling that impact the estimation of risk and attendant uncertainty. Distinguishing between uncertainty (what is unknown) and variability (heterogeneity) is crucial in risk assessment. Uncertainty includes components that are associated with (i) parameter estimation ...
Human and Ecological Risk Assessment: An International Journal, 2017
ABSTRACT Microbial risk assessors often make simplifying assumptions that lead to the selection o... more ABSTRACT Microbial risk assessors often make simplifying assumptions that lead to the selection of simple concave functions with low-dose linearity, consistent with no-threshold and single-hit hypotheses, as default dose–response model forms. However, evidence is accumulating as the “microbiome revolution” progresses that challenge these assumptions that influence the estimates of the nature and magnitude of uncertainties associated with microbial risks. Scientific advances in the knowledge of the human “superorganism” (hybrid consortium of human plus microbial communities that cooperatively regulates health and disease) enable the design of definitive studies to estimate the pathogen doses overcome by the innate defenses, including the protective microbiota. The systematic investigation of the events of non-typhoid salmonellosis in humans undertaken nearly 2 decades ago was updated to incorporate recent scientific advances in the understanding of impact of the healthy superorganism that strengthens and extends the biological motivations for sublinear or convex dose–response curves in microbial risk assessment. The knowledge of colonization resistance (innate protection of the human superorganism from low doses of ingested pathogens) and microbiota-mediated clearance is advancing mechanistically for many pathosystems. However, until more detailed mechanistic data become available for salmonellosis, the consideration of a variety of empirical model forms is essential for depicting the uncertainty of the “true” dose–response model.
An assessment of the risk of illness associated with Escherichia coli O157:H7 in ground beef was ... more An assessment of the risk of illness associated with Escherichia coli O157:H7 in ground beef was drafted in 2001. The exposure assessment considers farm, slaughter, and preparation factors that influence the likelihood of humans consuming ground beef servings containing E. coli O157:H7 and the number of cells in a contaminated serving. Apparent seasonal differences in prevalence of cattle infected with E. coli O157:H7 corresponded to seasonal differences in human exposure. The model predicts that on average 0.018% of servings consumed during June through September and 0.007% of servings consumed during the remainder of the year are contaminated with one or more E. coli O157:H7 cells. This exposure risk is combined with the probability of illness given exposure (i.e., dose response) to estimate a U.S. population risk of illness of nearly one illness in each 1 million (9.6 × 10−7) servings of ground beef consumed. Uncertainty about this risk ranges from about 0.33 illness in every 1 m...
Risk analysis : an official publication of the Society for Risk Analysis, Jan 25, 2017
Survival models are developed to predict response and time-to-response for mortality in rabbits f... more Survival models are developed to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple-dose data set to predict the probability of death through specifying functions of dose response and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) is an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed use different underlying dose-response functions and use the assumption that, in a multiple-dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this article. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approac...
Human individuals and societies have been identifying risks and managing them since ancient times... more Human individuals and societies have been identifying risks and managing them since ancient times (When you build a new house, you shall make a parapet for your roof, so that you shall not put blood in your house if [when] one falls from it. Deut. 22: 8) by various ...
Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approa... more Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approach to microbial risk assessment is presented that employs data analysis for developing parsimonious models and accounts formally for the variability and uncertainty of model inputs using analysis of variance and Monte Carlo simulation. The purpose of the paper is to raise and examine issues in conducting microbial risk assessments. The enteric pathogen Escherichia coli O157:H7 was selected as an example for this study due to its significance to public health. The framework for our work is consistent with the risk assessment components described by the National Research Council in 1983 (hazard identification; exposure assessment; dose‐response assessment; and risk characterization). Exposure assessment focuses on hamburgers, cooked a range of temperatures from rare to well done, the latter typical for fast food restaurants. Features of the model include predictive microbiology components ...
This guest editorial introduces a special collection of four manuscripts that offer a new perspec... more This guest editorial introduces a special collection of four manuscripts that offer a new perspective in Risk Analysis relating to the evolving interdisciplinary field of microbial risk assessment. The objective of the collection was to focus on the strengths and limitations of ...
Journal of Toxicology and Environmental Health, Part A, 2004
In order to estimate the risk or probability of adverse events in risk assessment, it is necessar... more In order to estimate the risk or probability of adverse events in risk assessment, it is necessary to identify the important variables that contribute to the risk and provide descriptions of distributions of these variables for well-defined populations. One component of modeling dose response that can create uncertainty is the inherent genetic variability among pathogenic bacteria. For many microbial risk assessments, the "default" assumption used for dose response does not account for strain or serotype variability in pathogenicity and virulence, other than perhaps, recognizing the existence of avirulent strains. However, an examination of data sets from human clinical trials in which Salmonella spp. and Campylobacter jejuni strains were administered reveals significant strain differences. This article discusses the evidence for strain variability and concludes that more biologically based alternatives are necessary to replace the default assumptions commonly used in microbial risk assessment, specifically regarding strain variability.
Uploads
Papers by Peg Coleman