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Pathogens such as bacteria, fungi and viruses are important components of soil and aquatic communities, where they can benefit from decaying and living organic matter, and may opportunistically infect human and animal hosts. One-third of human infectious diseases is constituted by sapronotic disease agents that are natural inhabitants of soil or aquatic ecosystems. They are capable of existing and reproducing in the environment outside of the host for extended periods of time. However, as ecological research on sapronosis is infrequent and epidemiological models are even rarer, very little information is currently available. Their importance is overlooked in medical and veterinary research, as well as the relationships between free environmental forms and those that are pathogenic. Here, using dynamical models in realistic aquatic metacommunity systems, we analyze sapronosis transmission, using the human pathogen Mycobacterium ulcerans that is responsible for Buruli ulcer. We show that the persistence of bacilli in aquatic ecosystems is driven by a seasonal upstream supply, and that the attachment and development of cells to aquatic living forms is essential for such pathogen persistence and population dynamics. Our work constitutes the first set of metacommunity models of sapronotic disease transmission, and is highly flexible for adaptation to other types of sapronosis. The importance of sapronotic agents on animal and human disease burden needs better understanding and new models of sapronosis disease ecology to guide the management and prevention of this important group of pathogens., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Louse flies (Diptera: Hippoboscidae) are obligate ectoparasites that often cause behavioral, pathogenic, and evolutionary effects on their hosts. Interactions between ectoparasites and avian hosts, especially migrating taxa, may influence avian pathogen spread in tropical and temperate ecosystems and affect long-term survival, fitness and reproductive success. The purpose of this study was to characterize the vector-associated microbiome of ectoparasitic louse flies feeding on migrating raptors over the fall migration period. Surveys for louse flies occurred during fall migration (2015-2016) at a banding station in Pennsylvania, United States; flies were collected from seven species of migrating raptors, and we sequenced their microbial (bacteria and archaea) composition using high-throughput targeted amplicon sequencing of the 16S rRNA gene (V4 region). All louse flies collected belonged to the same species, Icosta americana. Our analysis revealed no difference in bacterial communities of louse flies retrieved from different avian host species. The louse fly microbiome was dominated by a primary endosymbiont, suggesting that louse flies maintain a core microbial structure despite receiving blood meals from different host species. Thus, our findings highlight the importance of characterizing both beneficial and potentially pathogenic endosymbionts when interpreting how vector-associated microbiomes may impact insect vectors and their avian hosts., Competing Interests: The authors have declared that no competing interests exist.

Background: The postmortem microbiome can provide valuable information to a death investigation and to the human health of the once living. Microbiome sequencing produces, in general, large multi-dimensional datasets that can be difficult to analyze and interpret. Machine learning methods can be useful in overcoming this analytical challenge. However, different methods employ distinct strategies to handle complex datasets. It is unclear whether one method is more appropriate than others for modeling postmortem microbiomes and their ability to predict attributes of interest in death investigations, which require understanding of how the microbial communities change after death and may represent those of the once living host., Methods and Findings: Postmortem microbiomes were collected by swabbing five anatomical areas during routine death investigation, sequenced and analyzed from 188 death cases. Three machine learning methods (boosted algorithms, random forests, and neural networks) were compared with respect to their abilities to predict case attributes: postmortem interval (PMI), location of death, and manner of death. Accuracy depended on the method used, the numbers of anatomical areas analyzed, and the predicted attribute of death., Conclusions: All algorithms performed well but with distinct features to their performance. Xgboost often produced the most accurate predictions but may also be more prone to overfitting. Random forest was the most stable across predictions that included more anatomic areas. Analysis of postmortem microbiota from more than three anatomic areas appears to yield limited returns on accuracy, with the eyes and rectum providing the most useful information correlating with circumstances of death in most cases for this dataset., Competing Interests: The authors have declared that no competing interests exist.

Population-based public health data on antibiotic resistance gene carriage is poorly surveyed. Research of the human microbiome as an antibiotic resistance reservoir has primarily focused on gut associated microbial communities, but data have shown more widespread microbial colonization across organs than originally believed, with organs previously considered as sterile being colonized. Our study demonstrates the utility of postmortem microbiome sampling during routine autopsy as a method to survey antibiotic resistance carriage in a general population. Postmortem microbial sampling detected pathogens of public health concern including genes for multidrug efflux pumps, carbapenem, methicillin, vancomycin, and polymixin resistances. Results suggest that postmortem assessments of host-associated microbial communities are useful in acquiring community specific data while reducing selective-participant biases., Competing Interests: The authors have declared that no competing interests exist.

Microorganisms play a critical role in the decomposition of organic matter, which contributes to energy and nutrient transformation in every ecosystem. Yet, little is known about the functional activity of epinecrotic microbial communities associated with carrion. The objective of this study was to provide a description of the carrion associated microbial community functional activity using differential carbon source use throughout decomposition over seasons, between years and when microbial communities were isolated from eukaryotic colonizers (e.g., necrophagous insects). Additionally, microbial communities were identified at the phyletic level using high throughput sequencing during a single study. We hypothesized that carrion microbial community functional profiles would change over the duration of decomposition, and that this change would depend on season, year and presence of necrophagous insect colonization. Biolog EcoPlates™ were used to measure the variation in epinecrotic microbial community function by the differential use of 29 carbon sources throughout vertebrate carrion decomposition. Pyrosequencing was used to describe the bacterial community composition in one experiment to identify key phyla associated with community functional changes. Overall, microbial functional activity increased throughout decomposition in spring, summer and winter while it decreased in autumn. Additionally, microbial functional activity was higher in 2011 when necrophagous arthropod colonizer effects were tested. There were inconsistent trends in the microbial function of communities isolated from remains colonized by necrophagous insects between 2010 and 2011, suggesting a greater need for a mechanistic understanding of the process. These data indicate that functional analyses can be implemented in carrion studies and will be important in understanding the influence of microbial communities on an essential ecosystem process, carrion decomposition.