Dataset Information

Monitoring the microbiome for food safety and quality using deep shotgun sequencing.

ABSTRACT: In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species' viability from total RNA sequencing.

SUBMITTER: Beck KL

PROVIDER: S-EPMC7870667 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Monitoring the microbiome for food safety and quality using deep shotgun sequencing.

Beck Kristen L KL Haiminen Niina N Chambliss David D Edlund Stefan S Kunitomi Mark M Huang B Carol BC Kong Nguyet N Ganesan Balasubramanian B Baker Robert R Markwell Peter P Kawas Ban B Davis Matthew M Prill Robert J RJ Krishnareddy Harsha H Seabolt Ed E Marlowe Carl H CH Pierre Sophie S Quintanar André A Parida Laxmi L Dubois Geraud G Kaufman James J Weimer Bart C BC

NPJ science of food 20210208 1

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera pe ...[more]

PMID: 33558514

Similar Datasets

Project description:BackgroundThe goal of this study was to assess the microbial ecology and diversity present in the uterus of post-partum dairy cows with and without metritis from 24 commercial California dairy farms using shotgun metagenomics. A set subset of 95 intrauterine swab samples, taken from a larger selection of 307 individual cow samples previously collected, were examined for α and β diversity and differential abundance associated with metritis. Cows within 21 days post-partum were categorized into one of three clinical groups during sample collection: control (CT, n = 32), defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge; metritis (MET, n = 33), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; and purulent discharge cows (PUS, n = 31), defined as a non-fetid purulent or mucopurulent vaginal discharge.ResultsAll three clinical groups (CT, MET, and PUS) were highly diverse, with the top 12 most abundant genera accounting for 10.3%, 8.8%, and 10.1% of mean relative abundance, respectively. The α diversity indices revealed a lower diversity from samples collected from MET and PUS when compared to CT cows. PERMANOVA statistical testing revealed a significant difference (P adjusted < 0.01) in the diversity of genera between CT and MET samples (R2 = 0.112, P = 0.003) and a non-significant difference between MET and PUS samples (R2 = 0.036, P = 0.046). ANCOM-BC analysis revealed that from the top 12 most abundant genera, seven genera were increased in the natural log fold change (LFC) of abundance in MET when compared to CT samples: Bacteroides, Clostridium, Fusobacterium, Phocaeicola, Porphyromonas, Prevotella, and Streptococcus. Two genera, Dietzia and Microbacterium, were decreased in natural LFC of abundance when comparing MET (regardless of treatment) and CT, while no changes in natural LFC of abundance were observed for Escherichia, Histophilus, and Trueperella.ConclusionsThe results presented here, are the current deepest shotgun metagenomic analyses conducted on the bovine uterine microbiome to date (mean of 256,425 genus-level reads per sample). Our findings support that uterine samples from cows without metritis (CT) had increased α-diversity but decreased β-diversity when compared to metritis or PUS cows, characteristic of dysbiosis. In summary, our findings highlight that MET cows have an increased abundance of Bacteroides, Porphyromonas, and Fusobacterium when compared to CT and PUS, and support the need for further studies to better understand their potential causal role in metritis pathogenesis.

Project description:BackgroundHealth surveillance of murine colonies employed for scientific purposes aim at detecting unwanted infection that can affect the well-being of animals and personnel, and potentially undermine scientific results. In this study, we investigated the use of a next-generation sequencing (NGS) metagenomic approach for monitoring the microbiota composition and uncovering the possible presence of pathogens in mice housed in specific pathogen-free (SPF) or conventional (non-SPF) facilities.ResultsAnalysis of metagenomic NGS assay through public and free algorithms and databases allowed to precisely assess the composition of mouse gut microbiome and quantify the contribution of the different microorganisms at the species level. Sequence analysis allowed the uncovering of pathogens or the presence of imbalances in the microbiota composition. In several cases, fecal pellets taken from conventional facilities were found to carry gene sequences from bacterial pathogens (Helicobacter hepaticus, Helicobacter typhlonius, Chlamydia muridarum, Streptococcus pyogenes, Rodentibacter pneumotropicus, Citrobacter rodentium, Staphylococcus aureus), intestinal protozoa (Entamoeba muris, Tritrichomonas muris, Spironucleus muris) nematoda (Aspiculuris tetraptera, Syphacia obvelata), eukaryotic parasites (Myocoptes musculinus) and RNA virus (Norwalk virus). Thus, the use of NGS metagenomics can reduce the number of tests required for the detection of pathogens and avoid the use of sentinel mice.ConclusionsIn summary, in comparison with standard approaches, which require multiple types of test, NGS assay can detect bacteria, fungi, DNA and RNA viruses, and eukaryotic parasites from fecal pellets in a single test. Considering the need to protect animal well-being and to improve the success and reproducibility of preclinical studies, this work provides the proof-of-concept that the use of NGS metagenomics for health monitoring of laboratory mice is a feasible and dependable approach, that is able to broaden the current concept of health monitoring of laboratory mice from "pathogen surveillance" to a more inclusive "microbiota surveillance".

Project description:Few previous studies have assessed stability and "gold-standard" concordance of fecal sample collection methods for whole-genome shotgun metagenomic sequencing (WGSS), an increasingly popular method for studying the gut microbiome. We used WGSS data to investigate ambient temperature stability and putative gold-standard concordance of microbial profiles in fecal samples collected and stored using fecal occult blood test (FOBT) cards, fecal immunochemical test (FIT) tubes, 95% ethanol, or RNAlater. Among 15 Mayo Clinic employees, for each collection method, we calculated intraclass correlation coefficients (ICCs) to estimate stability of fecal microbial profiles after storage for 4?days at ambient temperature and concordance with immediately frozen, no-solution samples (i.e., the putative gold standard). ICCs were estimated for multiple metrics, including relative abundances of select phyla, species, KEGG k-genes (representing any coding sequence that had >70% identity and >70% query coverage with respect to a known KEGG ortholog), KEGG modules, and KEGG pathways; species and k-gene alpha diversity; and Bray-Curtis and Jaccard species beta diversity. ICCs for microbial profile stability were excellent (?90%) for fecal samples collected via most of the collection methods, except those preserved in 95% ethanol. Concordance with the immediately frozen, no-solution samples varied for all collection methods, but the number of observed species and the beta diversity metrics tended to have higher concordance than other metrics. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT cards, FIT tubes, and RNAlater are acceptable choices for fecal sample collection methods in future WGSS studies.IMPORTANCE A major direction for future microbiome research is implementation of fecal sample collections in large-scale, prospective epidemiologic studies. Studying microbiome-disease associations likely requires microbial data to be pooled from multiple studies. Our findings suggest collection methods that are most optimal to be used standardly across future WGSS microbiome studies.

Dataset Information

Monitoring the microbiome for food safety and quality using deep shotgun sequencing.

Publications

Monitoring the microbiome for food safety and quality using deep shotgun sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets