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1. Cast iron drinking water pipe biofilms support diverse microbial communities containing antibiotic resistance genes, metal resistance genes, and class 1 integrons

   https://doi.org/10.1039/D0EW01059F  

   Kimbell, Lee K. ; LaMartina, Emily Lou ; Kappell, Anthony D. ; Huo, Jingwan ; Wang, Yin ; Newton, Ryan J. ; McNamara, Patrick J. ( March 2021 , Environmental Science: Water Research & Technology)

   Antimicrobial resistance is a well-documented public health concern. The role that drinking water distribution pipes have as sources of antibiotic resistance genes (ARGs) is not well known. Metals are a known stressor for antibiotic resistance development, implying that aging metal-pipe infrastructure could be a source of ARGs. The objective of this study was to determine if ARGs, metal resistance genes (MRGs), and intI 1 were pervasive across various pipe biofilm sample types (biomass surfaces, pipe surfaces, corrosion tubercles, and under corrosion tubercles) and if the resistance genes associated with particular microbial taxa. Eight sample types in triplicate ( n = 24) were taken from inside a >100 year-old, six ft. section of a full-scale chloraminated cast iron drinking water main. Droplet digital PCR (ddPCR) was employed as a novel approach to quantify ARGs in pipes from full-scale drinking water distribution systems (DWDS) because it yielded higher detection frequencies than quantitative PCR (qPCR). Illumina sequencing was employed to characterize the microbial community based on 16S rRNA genes. ARGs and MRGs were detected in all 24 pipe samples. Every sample contained targeted genes. Interestingly, the mean absolute abundances of ARGs and MRGs only varied by approximately one log value across sample types,more »but the mean relative abundances (copy numbers normalized to 16S rRNA genes) varied by over two log values. The ARG and MRGs concentrations were not significantly different between sample types, despite significant changes in dominant microbial taxa. The most abundant genera observed in the biofilm communities were Mycobacterium (0.2–70%), and β-lactam resistance genes bla TEM , bla SHV , and the integrase gene of class 1 integrons ( intI 1) were positively correlated with Mycobacterium . The detection of ARGs, MRGs, and class 1 integrons across all sample types within the pipe indicates that pipes themselves can serve as sources for ARGs in DWDS. Consequently, future work should investigate the role of pipe materials as well as corrosion inhibitors to determine how engineering decisions can mitigate ARGs in drinking water that stem from pipe materials.« less
2. Metagenomics as a Public Health Risk Assessment Tool in a Study of Natural Creek Sediments Influenced by Agricultural and Livestock Runoff: Potential and Limitations

   https://doi.org/10.1128/AEM.02525-19  

   Suttner, Brittany ; Johnston, Eric R. ; Orellana, Luis H. ; Rodriguez-R, Luis M. ; Hatt, Janet K. ; Carychao, Diana ; Carter, Michelle Q. ; Cooley, Michael B. ; Konstantinidis, Konstantinos T. ; Ercolini, Danilo ( March 2020 , Applied and Environmental Microbiology)

   ABSTRACT Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (∼4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was significantly higher than ARG reads in other available freshwatermore »and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments. IMPORTANCE Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli . However, the accuracy of these traditional methods (e.g., low accuracy in quantification, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.« less
3. Critical review of antibiotic resistance genes in the atmosphere

   https://doi.org/10.1039/d2em00091a  

   Kormos, David ; Lin, Kaisen ; Pruden, Amy ; Marr, Linsey C. ( June 2022 , Environmental Science: Processes & Impacts)

   We conducted a critical review to establish what is known about the sources, characteristics, and dissemination of ARGs in the atmosphere. We identified 52 papers that reported direct measurements of bacterial ARGs in air samples and met other inclusion criteria. The settings of the studies fell into the following categories: urban, rural, hospital, industrial, wastewater treatment plants (WWTPs), composting and landfill sites, and indoor environments. Certain genes were commonly studied and generally abundant: sul1 , intI1 , β-lactam ARGs, and tetracycline ARGs. Abundances of total ARGs varied by season and setting, with air in urban areas having higher ARG abundance than rural areas during the summer and vice versa during the winter. There was greater consistency in the types and abundances of ARGs throughout the seasons in urban areas. Human activity within indoor environments was also linked to increased ARG content (abundance, diversity, and concentration) in the air. Several studies found that human exposure to ARGs through inhalation was comparable to exposure through drinking water or ingesting soil. Detection of ARGs in air is a developing field, and differences in sampling and analysis methods reflect the many possible approaches to studying ARGs in air and make direct comparisons between studiesmore »difficult. Methodologies need to be standardized to facilitate identification of the dominant ARGs in the air, determine their major sources, and quantify the role of atmospheric transport in dissemination of ARGs in the environment. With such knowledge we can develop better policies and guidelines to limit the spread of antimicrobial resistance.« less
4. Differential Overlap in Human and Animal Fecal Microbiomes and Resistomes in Rural versus Urban Bangladesh

   https://doi.org/10.1128/aem.00759-22  

   Swarthout, Jenna M. ; Fuhrmeister, Erica R. ; Hamzah, Latifah ; Harris, Angela R. ; Ahmed, Mir A. ; Gurley, Emily S. ; Satter, Syed M. ; Boehm, Alexandria B. ; Pickering, Amy J. ( July 2022 , Applied and Environmental Microbiology)

   Elkins, Christopher A. (Ed.)

   ABSTRACT Low- and middle-income countries (LMICs) bear the largest mortality burden of antibiotic-resistant infections. Small-scale animal production and free-roaming domestic animals are common in many LMICs, yet data on zoonotic exchange of gut bacteria and antibiotic resistance genes (ARGs) in low-income communities are sparse. Differences between rural and urban communities with regard to population density, antibiotic use, and cohabitation with animals likely influence the frequency of transmission of gut bacterial communities and ARGs between humans and animals. Here, we determined the similarity in gut microbiomes, using 16S rRNA gene amplicon sequencing, and resistomes, using long-read metagenomics, between humans, chickens, and goats in a rural community compared to an urban community in Bangladesh. Gut microbiomes were more similar between humans and chickens in the rural (where cohabitation is more common) than the urban community, but there was no difference for humans and goats in the rural versus the urban community. Human and goat resistomes were more similar in the urban community, and ARG abundance was higher in urban animals than rural animals. We identified substantial overlap of ARG alleles in humans and animals in both settings. Humans and chickens had more overlapping ARG alleles than humans and goats. All fecal hostsmore »from the urban community and rural humans carried ARGs on chromosomal contigs classified as potentially pathogenic bacteria, including Escherichia coli , Campylobacter jejuni , Clostridioides difficile , and Klebsiella pneumoniae . These findings provide insight into the breadth of ARGs circulating within human and animal populations in a rural compared to urban community in Bangladesh. IMPORTANCE While the development of antibiotic resistance in animal gut microbiomes and subsequent transmission to humans has been demonstrated in intensive farming environments and high-income countries, evidence of zoonotic exchange of antibiotic resistance in LMIC communities is lacking. This research provides genomic evidence of overlap of antibiotic resistance genes between humans and animals, especially in urban communities, and highlights chickens as important reservoirs of antibiotic resistance. Chicken and human gut microbiomes were more similar in rural Bangladesh, where cohabitation is more common. Incorporation of long-read metagenomics enabled characterization of bacterial hosts of resistance genes, which has not been possible in previous culture-independent studies using only short-read sequencing. These findings highlight the importance of developing strategies for combatting antibiotic resistance that account for chickens being reservoirs of ARGs in community environments, especially in urban areas.« less
5. Spatiotemporal evolution of COVID-19 infection and detection within night light networks: comparative analysis of USA and China

   https://doi.org/10.1007/s41109‐020‐00345‐4  

   Small, Christopher ; Sousa, Daniel ( December 2021 , Applied Network Science)

   Abstract The spatial distribution of population affects disease transmission, especially when shelter in place orders restrict mobility for a large fraction of the population. The spatial network structure of settlements therefore imposes a fundamental constraint on the spatial distribution of the population through which a communicable disease can spread. In this analysis we use the spatial network structure of lighted development as a proxy for the distribution of ambient population to compare the spatiotemporal evolution of COVID-19 confirmed cases in the USA and China. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band sensor on the NASA/NOAA Suomi satellite has been imaging night light at ~ 700 m resolution globally since 2012. Comparisons with sub-kilometer resolution census observations in different countries across different levels of development indicate that night light luminance scales with population density over ~ 3 orders of magnitude. However, VIIRS’ constant ~ 700 m resolution can provide a more detailed representation of population distribution in peri-urban and rural areas where aggregated census blocks lack comparable spatial detail. By varying the low luminance threshold of VIIRS-derived night light, we depict spatial networks of lighted development of varying degrees of connectivity within which populations are distributed. The resulting size distributions of spatial network componentsmore »(connected clusters of nodes) vary with degree of connectivity, but maintain consistent scaling over a wide range (5 × to 10 × in area & number) of network sizes. At continental scales, spatial network rank-size distributions obtained from VIIRS night light brightness are well-described by power laws with exponents near −2 (slopes near −1) for a wide range of low luminance thresholds. The largest components (10 4 to 10 5 km 2 ) represent spatially contiguous agglomerations of urban, suburban and periurban development, while the smallest components represent isolated rural settlements. Projecting county and city-level numbers of confirmed cases of COVID-19 for the USA and China (respectively) onto the corresponding spatial networks of lighted development allows the spatiotemporal evolution of the epidemic (infection and detection) to be quantified as propagation within networks of varying connectivity. Results for China show rapid nucleation and diffusion in January 2020 followed by rapid decreases in new cases in February. While most of the largest cities in China showed new confirmed cases approaching zero before the end of February, most of these cities also showed distinct second waves of cases in March or April. Whereas new cases in Wuhan did not approach zero until mid-March, as of December 2020 it has not yet experienced a second wave of cases. In contrast, the results for the USA show a wide range of trajectories, with an abrupt transition from slow increases in confirmed cases in a small number of network components in January and February, to rapid geographic dispersion to a larger number of components shortly before mobility reductions occurred in March. Results indicate that while most of the upper tail of the network had been exposed by the end of March, the lower tail of the component size distribution has only shown steep increases since mid-June.« less