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...
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Nature Portfolio
2021
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oai:doaj.org-article:2c00c0d566954b1792fdf043d8b9114f2021-12-02T14:11:00ZMonitoring the microbiome for food safety and quality using deep shotgun sequencing10.1038/s41538-020-00083-y2396-8370https://doaj.org/article/2c00c0d566954b1792fdf043d8b9114f2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41538-020-00083-yhttps://doaj.org/toc/2396-8370Abstract 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.Kristen L. BeckNiina HaiminenDavid ChamblissStefan EdlundMark KunitomiB. Carol HuangNguyet KongBalasubramanian GanesanRobert BakerPeter MarkwellBan KawasMatthew DavisRobert J. PrillHarsha KrishnareddyEd SeaboltCarl H. MarloweSophie PierreAndré QuintanarLaxmi ParidaGeraud DuboisJames KaufmanBart C. WeimerNature PortfolioarticleNutrition. Foods and food supplyTX341-641Food processing and manufactureTP368-456ENnpj Science of Food, Vol 5, Iss 1, Pp 1-12 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Nutrition. Foods and food supply TX341-641 Food processing and manufacture TP368-456 |
| spellingShingle |
Nutrition. Foods and food supply TX341-641 Food processing and manufacture TP368-456 Kristen L. Beck Niina Haiminen David Chambliss Stefan Edlund Mark Kunitomi B. Carol Huang Nguyet Kong Balasubramanian Ganesan Robert Baker Peter Markwell Ban Kawas Matthew Davis Robert J. Prill Harsha Krishnareddy Ed Seabolt Carl H. Marlowe Sophie Pierre André Quintanar Laxmi Parida Geraud Dubois James Kaufman Bart C. Weimer Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| description |
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. |
| format |
article |
| author |
Kristen L. Beck Niina Haiminen David Chambliss Stefan Edlund Mark Kunitomi B. Carol Huang Nguyet Kong Balasubramanian Ganesan Robert Baker Peter Markwell Ban Kawas Matthew Davis Robert J. Prill Harsha Krishnareddy Ed Seabolt Carl H. Marlowe Sophie Pierre André Quintanar Laxmi Parida Geraud Dubois James Kaufman Bart C. Weimer |
| author_facet |
Kristen L. Beck Niina Haiminen David Chambliss Stefan Edlund Mark Kunitomi B. Carol Huang Nguyet Kong Balasubramanian Ganesan Robert Baker Peter Markwell Ban Kawas Matthew Davis Robert J. Prill Harsha Krishnareddy Ed Seabolt Carl H. Marlowe Sophie Pierre André Quintanar Laxmi Parida Geraud Dubois James Kaufman Bart C. Weimer |
| author_sort |
Kristen L. Beck |
| title |
Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| title_short |
Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| title_full |
Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| title_fullStr |
Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| title_full_unstemmed |
Monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| title_sort |
monitoring the microbiome for food safety and quality using deep shotgun sequencing |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/2c00c0d566954b1792fdf043d8b9114f |
| work_keys_str_mv |
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