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 freshwater 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.
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The Source and Evolutionary History of a Microbial Contaminant Identified Through Soil Metagenomic Analysis
It is often important to determine the source of a microbial strain. Examples include tracking a bacterium linked to a disease epidemic, contaminating the food supply, or used in bioterrorism. Strain identification and tracking are generally approached by using cultivation-based or relatively nonspecific gene fingerprinting methods. Genomic methods have the ability to distinguish strains, but this approach typically has been restricted to isolates or relatively low-complexity communities. We demonstrate that strain-resolved metagenomics can be applied to extremely complex soil samples. We genotypically defined a soil-associated bacterium and identified it as a contaminant. By linking together snapshots of the bacterial genome over time, it was possible to estimate how long the contaminant had been diverging from a likely source population. The results are congruent with the derivation of the bacterium from a strain isolated in Germany and sequenced a decade ago and highlight the utility of metagenomics in strain tracking.
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- Award ID(s):
- 1331940
- NSF-PAR ID:
- 10401599
- Editor(s):
- Brown, C. Titus; Newman, Dianne K.
- Date Published:
- Journal Name:
- mBio
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2161-2129
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Background In modern sequencing experiments, quickly and accurately identifying the sources of the reads is a crucial need. In metagenomics, where each read comes from one of potentially many members of a community, it can be important to identify the exact species the read is from. In other settings, it is important to distinguish which reads are from the targeted sample and which are from potential contaminants. In both cases, identification of the correct source of a read enables further investigation of relevant reads, while minimizing wasted work. This task is particularly challenging for long reads, which can have a substantial error rate that obscures the origins of each read. Results Existing tools for the read classification problem are often alignment or index-based, but such methods can have large time and/or space overheads. In this work, we investigate the effectiveness of several sampling and sketching-based approaches for read classification. In these approaches, a chosen sampling or sketching algorithm is used to generate a reduced representation (a “screen”) of potential source genomes for a query readset before reads are streamed in and compared against this screen. Using a query read’s similarity to the elements of the screen, the methods predict the source of the read. Such an approach requires limited pre-processing, stores and works with only a subset of the input data, and is able to perform classification with a high degree of accuracy. Conclusions The sampling and sketching approaches investigated include uniform sampling, methods based on MinHash and its weighted and order variants, a minimizer-based technique, and a novel clustering-based sketching approach. We demonstrate the effectiveness of these techniques both in identifying the source microbial genomes for reads from a metagenomic long read sequencing experiment, and in distinguishing between long reads from organisms of interest and potential contaminant reads. We then compare these approaches to existing alignment, index and sketching-based tools for read classification, and demonstrate how such a method is a viable alternative for determining the source of query reads. Finally, we present a reference implementation of these approaches at https://github.com/arun96/sketching .more » « less
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ABSTRACT The soil bacterium
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Myxococcus xanthus forms biofilms in response to starvation, marked by cells aggregating into mounds. Some aggregates persist as spore-filled fruiting bodies, while others disperse after initial formation for unknown reasons. Here, we use a combination of cell tracking analysis and computational simulations to identify behaviors at the cellular level that contribute to aggregate dispersal. Our results suggest that cells in aggregates actively determine whether to disperse or persist and undergo a transition to sporulation based on a self-produced cue related to the aggregate size. Identifying these cues is an important step in understanding and potentially manipulating bacterial cell-fate decisions. -
Rotaru, Amelia-Elena (Ed.)ABSTRACT Novel bacterial isolates with the capabilities of lignin depolymerization, catabolism, or both, could be pertinent to lignocellulosic biofuel applications. In this study, we aimed to identify anaerobic bacteria that could address the economic challenges faced with microbial-mediated biotechnologies, such as the need for aeration and mixing. Using a consortium seeded from temperate forest soil and enriched under anoxic conditions with organosolv lignin as the sole carbon source, we successfully isolated a novel bacterium, designated 159R. Based on the 16S rRNA gene, the isolate belongs to the genus Sodalis in the family Bruguierivoracaceae . Whole-genome sequencing revealed a genome size of 6.38 Mbp and a GC content of 55 mol%. To resolve the phylogenetic position of 159R, its phylogeny was reconstructed using (i) 16S rRNA genes of its closest relatives, (ii) multilocus sequence analysis (MLSA) of 100 genes, (iii) 49 clusters of orthologous groups (COG) domains, and (iv) 400 conserved proteins. Isolate 159R was closely related to the deadwood associated Sodalis guild rather than the tsetse fly and other insect endosymbiont guilds. Estimated genome-sequence-based digital DNA-DNA hybridization (dDDH), genome percentage of conserved proteins (POCP), and an alignment analysis between 159R and the Sodalis clade species further supported that isolate 159R was part of the Sodalis genus and a strain of Sodalis ligni . We proposed the name Sodalis ligni str. 159R (=DSM 110549 = ATCC TSD-177). IMPORTANCE Currently, in the paper industry, paper mill pulping relies on unsustainable and costly processes to remove lignin from lignocellulosic material. A greener approach is biopulping, which uses microbes and their enzymes to break down lignin. However, there are limitations to biopulping that prevent it from outcompeting other pulping processes, such as requiring constant aeration and mixing. Anaerobic bacteria are a promising alternative source for consolidated depolymerization of lignin and its conversion to valuable by-products. We presented Sodalis ligni str. 159R and its characteristics as another example of potential mechanisms that can be developed for lignocellulosic applications.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1128/mBio.01969-16
