Conventional tobacco products harbor unique and heterogenous microbiomes.

While an increasing number of studies have evaluated tobacco microbiomes, comparative microbiome analyses across diverse tobacco products are non-existent. Moreover, to our knowledge, no previous studies have characterized the metabolically-active (live) fraction of tobacco bacterial communities and compared them across products. To address these knowledge gaps, we compared bacterial communities across four commercial products (cigarettes, little cigars, cigarillos and hookah) and one research cigarette product. After total DNA extraction (n = 414) from all samples, the V3V4 region of the 16S rRNA gene was sequenced on the Illumina HiSeq platform. To identify metabolically-active bacterial communities within these products, we applied a coupled 5-bromo-2'-deoxyuridine labeling and sequencing approach to a subset of samples (n = 56). Each tobacco product was characterized by its signature microbiome, along with a shared microbiome across all tobacco products consisting of Pseudomonas aeruginosa, P. putida, P. alcaligenes, Bacillus subtilis, and Klebsiella pneumoniae. Comparing across products (using Linear discriminant analysis Effect Size (LEfSe)), a significantly higher (p < 0.05) relative abundance of Klebsiella and Acinetobacter was observed in commercial cigarettes, while a higher relative abundance of Pseudomonas and Pantoea was observed in research cigarettes. Methylorubrum and Paenibacillus were higher in hookah, and Brevibacillus, Lactobacillus, Bacillus, Lysinibacillus, and Staphylococcus were higher in little cigars and cigarillos. Across all products, the majority of the metabolically-active bacterial communities belonged to the genus Pseudomonas, followed by several genera within the Firmicutes phylum (Bacillus, Terribacillus, and Oceanobacillus). Identification of some metabolically-active pathogens such as Bacillus cereus and Haemophilus parainfluenzae in commercial products is of concern because of the potential for these microorganisms to be transferred to users' respiratory tracts via mainstream smoke. Future work is warranted to evaluate the potential impact of these tobacco bacterial communities on users' oral and lung microbiomes, which play such an important role on the spectrum from health to disease.

Variations in Bacterial Communities and Antibiotic Resistance Genes Across Diverse Recycled and Surface Water Irrigation Sources in the Mid-Atlantic and Southwest United States: A CONSERVE Two-Year Field Study.

Reduced availability of agricultural water has spurred increased interest in using recycled irrigation water for U.S. food crop production. However, there are significant knowledge gaps concerning the microbiological quality of these water sources. To address these gaps, we used 16S rRNA gene and metagenomic sequencing to characterize taxonomic and functional variations (e.g., antimicrobial resistance) in bacterial communities across diverse recycled and surface water irrigation sources. We collected 1 L water samples (n = 410) between 2016 and 2018 from the Mid-Atlantic (12 sites) and Southwest (10 sites) U.S. Samples were filtered, and DNA was extracted. The V3-V4 regions of the 16S rRNA gene were then PCR amplified and sequenced. Metagenomic sequencing was also performed to characterize antibiotic, metal, and biocide resistance genes. Bacterial alpha and beta diversities were significantly different (p < 0.001) across water types and seasons. Pathogenic bacteria, such as Salmonella enterica, Staphylococcus aureus, and Aeromonas hydrophilia were observed across sample types. The most common antibiotic resistance genes identified coded against macrolides/lincosamides/streptogramins, aminoglycosides, rifampin and elfamycins, and their read counts fluctuated across seasons. We also observed multi-metal and multi-biocide resistance across all water types. To our knowledge, this is the most comprehensive longitudinal study to date of U.S. recycled water and surface water used for irrigation. Our findings improve understanding of the potential differences in the risk of exposure to bacterial pathogens and antibiotic resistance genes originating from diverse irrigation water sources across seasons and U.S. regions.

Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads.

BACKGROUND: Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. RESULTS: We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. CONCLUSION: The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

Taxonomic and Functional Shifts in the Sprout Spent Irrigation Water Microbiome in Response to Salmonella Contamination of Alfalfa Seeds.

Despite recent advances in Salmonella-sprout research, little is known about the relationship between Salmonella and the sprout microbiome during sprouting. Sprout spent irrigation water (SSIW) provides an informative representation of the total microbiome of this primarily aquaponic crop. This study was designed to characterize the function and taxonomy of the most actively transcribed genes in SSIW from Salmonella enterica serovar Cubana-contaminated alfalfa seeds throughout the sprouting process. Genomic DNA and total RNA from SSIW was collected at regular intervals and sequenced using Illumina MiSeq and NextSeq platforms. Nucleic acid data were annotated using four different pipelines. Both metagenomic and metatranscriptomic analyses revealed a diverse and highly dynamic SSIW microbiome. A "core" SSIW microbiome comprised Klebsiella, Enterobacter, Pantoea, and Cronobacter The impact, however, of Salmonella contamination on alfalfa seeds influenced SSIW microbial community dynamics not only structurally but also functionally. Changes in genes associated with metabolism, genetic information processing, environmental information processing, and cellular processes were abundant and time dependent. At time points of 24 h, 48 h, and 96 h, totals of 541, 723, and 424 S Cubana genes, respectively, were transcribed at either higher or lower levels than at 0 h in SSIW during sprouting. An array of S Cubana genes (107) were induced at all three time points, including genes involved in biofilm formation and modulation, stress responses, and virulence and tolerance to antimicrobials. Taken together, these findings expand our understanding of the effect of Salmonella seed contamination on the sprout crop microbiome and metabolome.IMPORTANCE Interactions of human enteric pathogens like Salmonella with plants and plant microbiomes remain to be elucidated. The rapid development of next-generation sequencing technologies provides powerful tools enabling investigation of such interactions from broader and deeper perspectives. Using metagenomic and metatranscriptomic approaches, this study identified not only changes in microbiome structure of SSIW associated with sprouting but also changes in the gene expression patterns related to the sprouting process in response to Salmonella contamination of alfalfa seeds. This study advances our knowledge on Salmonella-plant (i.e., sprout) interaction.

HPLC-UV, Metabarcoding and Genome Skims of Botanical Dietary Supplements: A Case Study in Echinacea.

The use of DNA-based methods to authenticate botanical dietary supplements has been vigorously debated for a variety of reasons. More comparisons of DNA-based and chemical methods are needed, and concordant evaluation of orthogonal approaches on the same products will provide data to better understand the strengths and weaknesses of both approaches. The overall application of DNA-based methods is already firmly integrated into a wide array of continually modernizing stand alone and complementary authentication protocols. Recently, the use of full-length chloroplast genome sequences provided enhanced discriminatory capacity for closely related species of Echinacea compared to traditional DNA barcoding approaches (matK and rbcL). Here, two next-generation sequencing approaches were used: (1) genome skimming and (2) PCR amplicon (metabarcoding). The two genetic approaches were then combined with HPLC-UV to evaluate 20 commercially available dietary supplements of Echinacea representing "finished" products. The trade-offs involved in different DNA approaches were discussed, with a focus on how DNA methods support existing, accepted chemical methods. In most of the products (19/20), HPLC-UV suggested the presence of Echinacea spp. While metabarcoding was not useful with this genus and instead only resolved 7 products to the family level, genome skimming was able to resolve to species (9) or genus (1) with the 10/20 products where it was successful. Additional ingredients that HPLC-UV was unable to identify were also found in four products along with the relative sequence proportion of the constituents. Additionally, genome skimming was able to identify one product that was a different Echinacea species entirely.

Investigating the Distribution of Strains of Erwinia amylovora and Streptomycin Resistance in Apple Orchards in New York Using Clustered Regularly Interspaced Short Palindromic Repeat Profiles: A 6-Year Follow-Up.

Fire blight, caused by the bacterium Erwinia amylovora, is one of the most important diseases of apple. The antibiotic streptomycin is routinely used in the commercial apple industries of New York (NY) and New England to manage the disease. In 2002 and again, from 2011 to 2014, outbreaks of streptomycin resistance (SmR) were reported and investigated in NY. Motivated by new grower reports of control failures, we conducted a follow-up investigation of the distribution of SmR and E. amylovora strains for major apple production regions of NY over the last 6 years (2015 to 2020). Characterization of clustered regularly interspaced short palindromic repeat (CRISPR) profiles revealed that a few "cosmopolitan" strains were widely prevalent across regions, whereas many other "resident" strains were confined to one location. In addition, we uncovered novel CRISPR profile diversity in all investigated regions. SmR E. amylovora was detected only in a small area spanning two counties from 2017 to 2020 and was always associated with one CRISPR profile (41:23:38), which matched the profile of SmR E. amylovora, discovered in 2002. This suggests the original SmR E. amylovora was never fully eradicated and went undetected because of several seasons of low disease pressure in this region. Investigation of several representative isolates under controlled greenhouse conditions indicated significant differences in aggressiveness on 'Gala' apples. Potential implications of strain differences include the propensity of strains to become distributed across wide geographic regions and associated resistance management practices. Results from this work will directly influence sustainable fire blight management recommendations for commercial apple industries in NY state and other regions.

Using full chloroplast genomes of 'red' and 'yellow' Bixa orellana (achiote) for kmer based identification and phylogenetic inference.

BACKGROUND: Full chloroplast genomes provide high resolution taxonomic discrimination between closely related plant species and are quickly replacing single and multi-locus barcoding regions as reference materials of choice for DNA based taxonomic annotation of plants. Bixa orellana, commonly known as "achiote" and "annatto" is a plant used for both human and animal foods and was thus identified for full chloroplast sequencing for the Center for Veterinary Medicine (CVM) Complete Chloroplast Animal Feed database. This work was conducted in collaboration with the Instituto de Medicina Tradicional (IMET) in Iquitos, Peru. There is a wide range of color variation in pods of Bixa orellana for which genetic loci that distinguish phenotypes have not yet been identified. Here we apply whole chloroplast genome sequencing of "red" and "yellow" individuals of Bixa orellana to provide high quality reference genomes to support kmer database development for use identifying this plant from complex mixtures using shotgun data. Additionally, we describe chloroplast gene content, synteny and phylogeny, and identify an indel and snp that may be associated with seed pod color. RESULTS: Fully assembled chloroplast genomes were produced for both red and yellow Bixa orellana accessions (158,918 and 158,823 bp respectively). Synteny and gene content was identical to the only other previously reported full chloroplast genome of Bixa orellana (NC_041550). We observed a 17 base pair deletion at position 58,399-58,415 in both accessions, relative to NC_041550 and a 6 bp deletion at position 75,531-75,526 and a snp at position 86,493 in red Bixa orellana. CONCLUSIONS: Our data provide high quality reference genomes of individuals of red and yellow Bixa orellana to support kmer based identity markers for use with shotgun sequencing approaches for rapid, precise identification of Bixa orellana from complex mixtures. Kmer based phylogeny of full chloroplast genomes supports monophylly of Bixaceae consistent with alignment based approaches. A potentially discriminatory indel and snp were identified that may be correlated with the red phenotype.

Quasimetagenomic source tracking of Listeria monocytogenes from naturally contaminated ice cream.

BACKGROUND: The more quickly bacterial pathogens responsible for foodborne illness outbreaks can be linked to a vehicle of transmission or a source, the more illnesses can be prevented. Whole genome sequencing (WGS) based approaches to source tracking have greatly increased the speed and resolution with which public health response can pinpoint the vehicle and source of outbreaks. Traditionally, WGS approaches have focused on the culture of an individual isolate before proceeding to DNA extraction and sequencing. For Listeria monocytogenes (Lm), generation of an individual isolate for sequencing typically takes about 6 days. Here we demonstrate that a hybrid, "quasimetagenomic" approach ie; direct sequencing of microbiological enrichments (first step in pathogen detection and recovery) can provide high resolution source tracking sequence data, 5 days earlier than response that focuses on culture and sequencing of an individual isolate. This expedited approach could save lives, prevent illnesses and potentially minimize unnecessary destruction of food. METHODS: Naturally contaminated ice cream (from a 2015 outbreak) was enriched to recover Listeria monocytogenes following protocols outlined in the Bacteriological Analytic Manual (BAM). DNA from enriching microbiota was extracted and sequenced at incremental time-points during the first 48 h of pre-enrichment using the Illumina MiSeq platform (2 by 250), to evaluate genomic coverage of target pathogen, Listeria monocytogenes. RESULTS: Quasimetagenomic sequence data acquired from hour 20 were sufficient to discern whether or not Lm strain/s were part of the ongoing outbreak or not. Genomic data from hours 24, 28, 32, 36, 40, 44, and 48 of pre-enrichments all provided identical phylogenetic source tracking utility to the WGS of individual isolates (which require an additional 5 days to culture). CONCLUSIONS: The speed of this approach (more than twice as fast as current methods) has the potential to reduce the number of illnesses associated with any given outbreak by as many as 75% percent of total cases and potentially with continued optimization of the entire chain of response, contribute to minimized food waste.

Global transcriptomic analyses of Salmonella enterica in Iron-depleted and Iron-rich growth conditions.

BACKGROUND: Salmonella enterica possess several iron acquisition systems, encoded on the chromosome and plasmids. Recently, we demonstrated that incompatibility group (Inc) FIB plasmid-encoded iron acquisition systems (Sit and aerobactin) likely play an important role in persistence of Salmonella in human intestinal epithelial cells (Caco-2). In this study, we sought to determine global transcriptome analyses of S. enterica in iron-rich (IR) and iron-depleted (ID) growth conditions. RESULTS: The number of differentially-expressed genes were substantially higher for recipient (SE819) (n = 966) and transconjugant (TC) (n = 945) compared to the wild type (WT) (SE163A) (n = 110) strain in ID as compared to IR growth conditions. Several virulence-associated factors including T3SS, flagellin, cold-shock protein (cspE), and regulatory genes were upregulated in TC in ID compared to IR conditions. Whereas, IS1 and acrR/tetR transposases located on the IncFIB plasmid, ferritin and several regulatory genes were downregulated in TC in ID conditions. Enterobactin transporter (entS), iron ABC transporter (fepCD), colicin transporter, IncFIB-encoded enolase, cyclic di-GMP regulator (cdgR) and other regulatory genes of the WT strain were upregulated in ID compared to IR conditions. Conversely, ferritin, ferrous iron transport protein A (feoA), IncFIB-encoded IS1 and acrR/tetR transposases and ArtA toxin of WT were downregulated in ID conditions. SDS-PAGE coupled with LC-MS/MS analyses revealed that siderophore receptor proteins such as chromosomally-encoded IroN and, IncFIB-encoded IutA were upregulated in WT and TC in ID growth conditions. Both chromosome and IncFIB plasmid-encoded SitA was overexpressed in WT, but not in TC or recipient in ID conditions. Increased expression of flagellin was detected in recipient and TC, but not in WT in ID conditions. CONCLUSION: Iron concentrations in growth media influenced differential gene expressions both at transcriptional and translational levels, including genes encoded on the IncFIB plasmid. Limited iron availability within the host may promote pathogenic Salmonella to differentially express subsets of genes encoded by chromosome and/or plasmids, facilitating establishment of successful infection.

Metagenome tracking biogeographic agroecology: Phytobiota of tomatoes from Virginia, Maryland, North Carolina and California.

Describing baseline microbiota associated with agricultural commodities in the field is an important step towards improving our understanding of a wide range of important objectives from plant pathology and horticultural sustainability, to food safety. Environmental pressures on plants (wind, dust, drought, water, temperature) vary by geography and characterizing the impact of these variable pressures on phyllosphere microbiota will contribute to improved stewardship of fresh produce for both plant and human health. A higher resolution understanding of the incidence of human pathogens on food plants and co-occurring phytobiota using metagenomic approaches (metagenome tracking) may contribute to improved source attribution and risk assessment in cases where human pathogens become introduced to agro-ecologies. Between 1990 and 2007, as many as 1990 culture-confirmed Salmonella illnesses were linked to tomatoes from as many as 12 multistate outbreaks (Bell et al., 2012; Bell et al., 2015; Bennett et al., 2014; CDC, 2004; CDC, 2007; Greene et al., 2005a; Gruszynski et al., 2014). When possible, source attribution for these incidents revealed a biogeographic trend, most events were associated with eastern growing regions. To improve our understanding of potential biogeographically linked trends in contamination of tomatoes by Salmonella, we profiled microbiota from the surfaces of tomatoes from Virginia, Maryland, North Carolina and California. Bacterial profiles from California tomatoes were completely different than those of Maryland, Virginia and North Carolina (which were highly similar to each other). A statistically significant enrichment of Firmicutes taxa was observed in California phytobiota compared to the three eastern states. Rhizobiaceae, Sphingobacteriaceae and Xanthobacteraceae were the most abundant bacterial families associated with tomatoes grown in eastern states. These baseline metagenomic profiles of phyllosphere microbiota may contribute to improved understanding of how certain ecologies provide supportive resources for human pathogens on plants and how components of certain agro-ecologies may play a role in the introduction of human pathogens to plants.

Metagenomics of pasteurized and unpasteurized gouda cheese using targeted 16S rDNA sequencing.

BACKGROUND: The microbiome of cheese is diverse, even within a variety. The metagenomics of cheese is dependent on a vast array of biotic and abiotic factors. Biotic factors include the population of microbiota and their resulting cellular metabolism. Abiotic factors, including the pH, water activity, fat, salt, and moisture content of the cheese matrix, as well as environmental conditions (temperature, humidity, and location of aging), influence the biotic factors. This study assessed the metagenomics of commercial Gouda cheese prepared using pasteurized or unpasteurized cow milk or pasteurized goat milk via 16S rDNA sequencing. RESULTS: Results were analyzed and compared based on milk pasteurization and source, spatial variability (core, outer, and under the rind), and length of aging (2-4 up to 12-18 months). The dominant organisms in the Gouda cheeses, based on percentage of sequence reads identified at the family or genus levels, were Bacillaceae, Lactococcus, Lactobacillus, Streptococcus, and Staphylococcus. More genus- or family-level (e.g. Bacillaceae) identifications were observed in the Gouda cheeses prepared with unpasteurized cow milk (120) compared with those prepared with pasteurized cow milk (92). When assessing influence of spatial variability on the metagenomics of the cheese, more pronounced differences in bacterial genera were observed in the samples taken under the rind; Brachybacterium, Pseudoalteromonas, Yersinia, Klebsiella, and Weissella were only detected in these samples. Lastly, the aging length of the cheese greatly influenced the number of organisms observed. Twenty-seven additional genus-level identifications were observed in Gouda cheese aged for 12-18 months compared with cheese only aged 2-4 months. CONCLUSIONS: Collectively, the results of this study are important in determining the typical microbiota associated with Gouda cheese and how the microbiome plays a role in safety and quality.

Shifts in spinach microbial communities after chlorine washing and storage at compliant and abusive temperatures.

Fresh produce, like spinach, harbors diverse bacterial populations, including spoilage and potentially pathogenic bacteria. This study examined the effects of produce washing in chlorinated water and subsequent storage on the microbiota of spinach. Baby spinach leaves from a commercial fresh-cut produce processor were assessed before and after washing in chlorinated water, and then after one week's storage at 4, 10, and 15 °C. Microbial communities on spinach were analyzed by non-selective plating, qPCR, and 16S rDNA amplicon sequencing. Bacterial populations on spinach, averaging 6.12 ±â€¯0.61 log CFU/g, were reduced by 1.33 ±â€¯0.57 log after washing. However, populations increased by 1.77-3.24 log after storage, with larger increases occurring at higher temperature (15 > 10 > 4 °C). The predominant phylum identified on unwashed spinach leaves was Proteobacteria; dominant genera were Pseudomonas and Sphingomonas. Bacterial communities shifted significantly after chlorine washing and storage. Several Proteobacteria species, such as Stenotrophomonas sp. and Erwinia sp., were relatively tolerant of chlorine treatment, while species of Flavobacterium and Pedobacter (phylum Bacteroidetes) grew rapidly during storage, especially at abusive temperatures. Cupriavidus sp. and Ralstonia sp. showed significant increases after washing. After storage, microbial communities on spinach appeared to shift back toward the pre-washing distributions.

Development of a Reference Standard Library of Chloroplast Genome Sequences, GenomeTrakrCP.

Precise, species-level identification of plants in foods and dietary supplements is difficult. While the use of DNA barcoding regions (short regions of DNA with diagnostic utility) has been effective for many inquiries, it is not always a robust approach for closely related species, especially in highly processed products. The use of fully sequenced chloroplast genomes, as an alternative to short diagnostic barcoding regions, has demonstrated utility for closely related species. The U. S. Food and Drug Administration (FDA) has also developed species-specific DNA-based assays targeting plant species of interest by utilizing chloroplast genome sequences. Here, we introduce a repository of complete chloroplast genome sequences called GenomeTrakrCP, which will be publicly available at the National Center for Biotechnology Information (NCBI). Target species for inclusion are plants found in foods and dietary supplements, toxin producers, common contaminants and adulterants, and their close relatives. Publicly available data will include annotated assemblies, raw sequencing data, and voucher information with each NCBI accession associated with an authenticated reference herbarium specimen. To date, 40 complete chloroplast genomes have been deposited in GenomeTrakrCP (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA325670/), and this will be expanded in the future.

Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak.

BACKGROUND: Microbiota that co-enrich during efforts to recover pathogens from foodborne outbreaks interfere with efficient detection and recovery. Here, dynamics of co-enriching microbiota during recovery of Listeria monocytogenes from naturally contaminated ice cream samples linked to an outbreak are described for three different initial enrichment formulations used by the Food and Drug Administration (FDA), the International Organization of Standardization (ISO), and the United States Department of Agriculture (USDA). Enrichment cultures were analyzed using DNA extraction and sequencing from samples taken every 4 h throughout 48 h of enrichment. Resphera Insight and CosmosID analysis tools were employed for high-resolution profiling of 16S rRNA amplicons and whole genome shotgun data, respectively. RESULTS: During enrichment, other bacterial taxa were identified, including Anoxybacillus, Geobacillus, Serratia, Pseudomonas, Erwinia, and Streptococcus spp. Surprisingly, incidence of L. monocytogenes was proportionally greater at hour 0 than when tested 4, 8, and 12 h later with all three enrichment schemes. The corresponding increase in Anoxybacillus and Geobacillus spp.indicated these taxa co-enriched in competition with L. monocytogenes during early enrichment hours. L. monocytogenes became dominant after 24 h in all three enrichments. DNA sequences obtained from shotgun metagenomic data of Listeria monocytogenes at 48 h were assembled to produce a consensus draft genome which appeared to have a similar tracking utility to pure culture isolates of L. monocytogenes. CONCLUSIONS: All three methods performed equally well for enrichment of Listeria monocytogenes. The observation of potential competitive exclusion of L. mono by Anoxybacillus and Geobacillus in early enrichment hours provided novel information that may be used to further optimize enrichment formulations. Application of Resphera Insight for high-resolution analysis of 16S amplicon sequences accurately identified L. monocytogenes. Both shotgun and 16S rRNA data supported the presence of three slightly variable genomes of L. monocytogenes. Moreover, the draft assembly of a consensus genome of L. monocytogenes from shotgun metagenomic data demonstrated the potential utility of this approach to expedite trace-back of outbreak-associated strains, although further validation will be needed to confirm this utility.

Advancing metagenome-assembled genome-based pathogen identification: unraveling the power of long-read assembly algorithms in Oxford Nanopore sequencing.

Oxford Nanopore sequencing is one of the high-throughput sequencing technologies that facilitates the reconstruction of metagenome-assembled genomes (MAGs). This study aimed to assess the potential of long-read assembly algorithms in Oxford Nanopore sequencing to enhance the MAG-based identification of bacterial pathogens using both simulated and mock communities. Simulated communities were generated to mimic those on fresh spinach and in surface water. Long reads were produced using R9.4.1+SQK-LSK109 and R10.4 + SQK-LSK112, with 0.5, 1, and 2 million reads. The simulated bacterial communities included multidrug-resistant Salmonella enterica serotypes Heidelberg, Montevideo, and Typhimurium in the fresh spinach community individually or in combination, as well as multidrug-resistant Pseudomonas aeruginosa in the surface water community. Real data sets of the ZymoBIOMICS HMW DNA Standard were also studied. A bioinformatic pipeline (MAGenie, freely available at https://github.com/jackchen129/MAGenie) that combines metagenome assembly, taxonomic classification, and sequence extraction was developed to reconstruct draft MAGs from metagenome assemblies. Five assemblers were evaluated based on a series of genomic analyses. Overall, Flye outperformed the other assemblers, followed by Shasta, Raven, and Unicycler, while Canu performed least effectively. In some instances, the extracted sequences resulted in draft MAGs and provided the locations and structures of antimicrobial resistance genes and mobile genetic elements. Our study showcases the viability of utilizing the extracted sequences for precise phylogenetic inference, as demonstrated by the consistent alignment of phylogenetic topology between the reference genome and the extracted sequences. R9.4.1+SQK-LSK109 was more effective in most cases than R10.4+SQK-LSK112, and greater sequencing depths generally led to more accurate results.IMPORTANCEBy examining diverse bacterial communities, particularly those housing multiple Salmonella enterica serotypes, this study holds significance in uncovering the potential of long-read assembly algorithms to improve metagenome-assembled genome (MAG)-based pathogen identification through Oxford Nanopore sequencing. Our research demonstrates that long-read assembly stands out as a promising avenue for boosting precision in MAG-based pathogen identification, thus advancing the development of more robust surveillance measures. The findings also support ongoing endeavors to fine-tune a bioinformatic pipeline for accurate pathogen identification within complex metagenomic samples.

Paired metagenomic and chemical evaluation of aflatoxin-contaminated dog kibble.

Introduction: Identification of chemical toxins from complex or highly processed foods can present 'needle in the haystack' challenges for chemists. Metagenomic data can be used to guide chemical toxicity evaluations by providing DNA-based description of the wholistic composition (eukaryotic, bacterial, protozoal, viral, and antimicrobial resistance) of foods suspected to harbor toxins, allergens, or pathogens. This type of information can focus chemistry-based diagnostics, improve hazard characterization and risk assessment, and address data gaps. Additionally, there is increasing recognition that simultaneously co-occurring mycotoxins, either from single or multiple species, can impact dietary toxicity exposure. Metagenomic data provides a way to address data gaps related to co-occurrence of multiple fungal species. Methods: Paired metagenomic and chemical data were used to evaluate aflatoxin-contaminated kibble with known levels of specific mycotoxins. Kibble was ground to a fine powder for both chemical and molecular analyses. Chemical analyses were performed with Liquid Chromatography Mass Spectrometry (LCMS) and according to the AOAC Official method 2005.08: Aflatoxins in Corn, Raw Peanuts, and Peanut Butter using Liquid Chromatography with Post-Column Photochemical Derivatization. Metagenomes were created from DNA extracted from ground kibble and sequenced on an Illumina NextSeq 2000 with an average sequence depth of 180 million reads per replicate. Results and discussion: Metagenomic data demonstrated that the abundance of DNA from putative aflatoxigenic Aspergillus spp. correlated with the levels of aflatoxin quantified by LCMS. Metagenomic data also identified an expansive range of co-occurring fungal taxa which may produce additional mycotoxins. DNA data paired with chemical data provides a novel modality to address current data gaps surrounding dietary mycotoxin exposure, toxigenic fungal taxonomy, and mycotoxins of emerging concern.

Metagenomic survey of antimicrobial resistance (AMR) in Maryland surface waters differentiated by high and low human impact.

Here, we examine surface waters as a modality to better understand baseline antimicrobial resistance (AMR) across the environment to supplement existing AMR monitoring in pathogens associated with humans, foods, and animals. Data from metagenomic and quasimetagenomic (shotgun sequenced enrichments) are used to describe AMR in Maryland surface waters from high and low human impact classifications.

Evaluation of universal preenrichment broth and comparison of rapid molecular methods for the detection of Salmonella from spent sprout irrigation water (SSIW).

Sprouts and spent sprout irrigation water (SSIW) present unique challenges for the development of a Salmonella detection method in food matrices. This study aimed to compare universal preenrichment broth (UPB) and lactose broth (LB) as preenrichment media for cultural and rapid screening methods and to compare their abilities to recover Salmonella in SSIW samples from different sprout varieties (i.e., alfalfa, broccoli, and mung bean sprouts). The associated co-enriched microbiota with different sprout varieties using different preenrichment media were also examined using a quasi-metagenomic approach. The performance of media and detection methods was compared using the relative level of detection (RLOD) value, as recommended by ISO 16140-2:2016. The level of detection (LOD) for Salmonella culture method with UPB was similar to that with LB in low aerobic plate count (APC) background samples (the relative LOD, i.e., RLOD, was nearly 1 after adjusting for the effects of SSIW variety and serovar), but significantly lower than that with LB in high APC background samples (RLOD = 0.32). The LOD for Salmonella with selected rapid methods was comparable to each other (RLOD from 0.97 to 1.50) and to the culture method (RLOD from 0.69 to 1.03), and no significant difference was detected between preenrichment broths in low APC background samples with RLOD values between 0.76 and 1.04. In samples with a high APC background, however, a drastic difference in LOD was observed between methods and between preenrichment broths for each method. The RLOD ranged from 0.03 to 0.32 when UPB was compared to LB as preenrichment broth. The composition and relative abundance (RA) of co-enriched microbiota was affected by multiple factors including food matrices, preenrichment media and Salmonella contamination. Altogether, this study validated UPB as a better preenrichment broth than LB for the detection of Salmonella enterica from SSIW. This study also suggested UPB may also be an optimal preenrichment medium for rapid screening methods when APC level is high. The observation of potential exclusion of Salmonella in preenrichment through the overgrowth of competitive microflora from the quasi-metagenomic study provided novel information that may be used to further optimize preenrichment formulations.

SARS-CoV-2 wastewater variant surveillance: pandemic response leveraging FDA's GenomeTrakr network.

Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA's genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject, PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA's GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA. IMPORTANCE: This paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA's laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples.

Development of a tiered multilocus sequence typing scheme for members of the Lactobacillus acidophilus complex.

Members of the Lactobacillus acidophilus complex are associated with functional foods and dietary supplements because of purported health benefits they impart to the consumer. Many characteristics of these microorganisms are reported to be strain specific. Therefore, proper strain typing is essential for safety assessment and product labeling, and also for monitoring strain integrity for industrial production purposes. Fifty-two strains of the L. acidophilus complex (L. acidophilus, L. amylovorus, L. crispatus, L. gallinarum, L. gasseri, and L. johnsonii) were genotyped using two established methods and compared to a novel multilocus sequence typing (MLST) scheme. PCR restriction fragment length polymorphism (PCR-RFLP) analysis of the hsp60 gene with AluI and TaqI successfully clustered 51 of the 52 strains into the six species examined, but it lacked strain-level discrimination. Random amplified polymorphic DNA PCR (RAPD-PCR) targeting the M13 sequence resulted in highly discriminatory profiles but lacked reproducibility. In this study, an MLST scheme was developed using the conserved housekeeping genes fusA, gpmA, gyrA, gyrB, lepA, pyrG, and recA, which identified 40 sequence types that successfully clustered all of the strains into the six species. Analysis of the observed alleles suggests that nucleotide substitutions within five of the seven MLST loci have reached saturation, a finding that emphasizes the highly diverse nature of the L. acidophilus complex and our unconventional application of a typically intraspecies molecular typing tool. Our MLST results indicate that this method could be useful for characterization and strain discrimination of a multispecies complex, with the potential for taxonomic expansion to a broader collection of Lactobacillus species.