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Evaluating the Information Content of Shallow Shotgun Metagenomics
Open accessAbstract
A common refrain in recent microbiome-related academic meetings is that the field needs to move away from broad taxonomic surveys using 16S sequencing and toward more powerful longitudinal studies using shotgun sequencing. However, performing deep shotgun sequencing in large longitudinal studies remains prohibitively expensive for all but the most well-funded research labs and consortia, which leads many researchers to choose 16S sequencing for large studies, followed by deep shotgun sequencing on a subset of targeted samples. Here, we show that shallow- or moderate-depth shotgun sequencing may be used by researchers to obtain species-level taxonomic and functional data at approximately the same cost as amplicon sequencing. While shallow shotgun sequencing is not intended to replace deep shotgun sequencing for strain-level characterization, we recommend that microbiome scientists consider using shallow shotgun sequencing instead of 16S sequencing for large-scale human microbiome studies.
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“we repeated all bioinformatic, normalization, and ML steps using bacterial assignments from SHOGUN31 and its separate database48, which showed highly concordant performances”
From RETRACTED ARTICLE: Microbiome analyses of blood and tissues suggest cancer diagnostic approach (2020) · cites this paper as [31]
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InfluentialSARS-CoV-2 infectivity can be modulated through bacterial grooming of the glycocalyx
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A Genomic Census of the Chicken Gut Microbiome using Metagenomics and CulturePreprint
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“Page 4/39 sequences), which fail to provide species-level resolution, are unable to detect viruses and reveal nothing about the genome sequences, population structures or functional repertoires of microbial species [11].”
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Kim, N., Kim, C. Y., Yang, S., Park, D.-J., Ha, S., & Lee, I. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.24.465599 · Cited by 2
Millet, Y. A., Meisner, J. S., Tan, J., Jose, A., Humphries, E., Miller, K. J., Bayne, C. F., McComb, M., Giuggio, M., Konopnicki, C. M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.04.487010 · Cited by 2
A Genomic Census of the Chicken Gut Microbiome using Metagenomics and CulturePreprint
Gilroy, R., Ravi, A., Getino, M., Pursley, I., Horton, D. L., Alikhan, N.-F., Baker, D., Gharbi, K., Hall, N., Watson, M., et al. (2020) · Research Square · doi:10.21203/rs.3.rs-56027/v3 · Cited by 2
Yue, Y., Read, T. D., Fedirko, V., Satten, G. A., & Hu, Y. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.27.546795 · Cited by 2
Vaginal microbial profiling in a preterm birth high-risk cohort using shallow shotgun metagenomics
Alishum, A., Christophersen, C. T., & Keelan, J. A. (2021) · Microbiology Australia · doi:10.1071/ma21023 · Cited by 1
DNA extraction protocols for animal fecal material on blood spot cards
Llarena, A., Haverkamp, T. H. A., Gulliksen, W. S., Herstad, K. M. V., Holst‐Jensen, A., Skjerve, E., Rannem, L., Rodríguez, S., & Øines, Ø. (2025) · PLoS ONE · doi:10.1371/journal.pone.0313808 · Cited by 1
Ansari, S., Sarmah, D. T., Verma, R., Chandrasekar, K., Shalimar, S., Nayak, B., Chatterjee, S., & Surjit, M. (2025) · mSystems · doi:10.1128/msystems.00438-25 · Cited by 2
Advantages and disadvantages of various methods for diagnosing intestinal microbiota disorders
Ogay, M., Fominykh, Y. A., & Наджафова, К. Н. (2025) · Экспериментальная и клиническая гастроэнтерология · doi:10.31146/1682-8658-ecg-234-2-179-186 · Cited by 1
Towards Key Principles of Host‐Associated Microbiome Assembly
Araujo, G., Thomas, T., Montoya, J. M., Webster, N. S., & Lurgi, M. (2026) · Ecology Letters · doi:10.1111/ele.70433 · Cited by 1
Microbiome study of Murrah buffalo mastitis milk with emphasis on Acinetobacter species
Sharma, D., Valmiki, H., Chayal, P., Kumar, S., & Chhotaray, S. (2025) · BMC Microbiology · doi:10.1186/s12866-025-04458-7 · Cited by 1
“In a study, Hillmann et al. [55] demonstrated that shallow sequencing provides nearly the same accuracy at both the species and functional levels as deep whole metagenome sequencing for known species and genus in five key aspects of microbiome analysis: beta and alpha diversity, species…”
Chapagain, C., Khezri, A., Ali, J., Smistad, M., Sølverød, L. S., & Ahmad, R. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2025.1680165 · Cited by 1
“Previous studies have shown that fragmentation during extraction adversely aects contiguity, aecting genome completeness and accuracy (Hillmann et al., 2018; Nicholls et al., 2019).”
Alishum, A., Keelan, J. A., Penova‐Veselinovic, B., Christophersen, C. T., Bunce, M., & Allentoft, M. E. (2026) · Microorganisms · doi:10.3390/microorganisms14010128 · Cited by 1
“This approach, even in shallow sequencing depth, allows for a more accurate identification of vaginal bacteria for better understanding of the functional potential of the microbiota [48].”
Nichols, S., Estandía, A., Young, C., Knowles, L. S., Palinauskas, V., Okamura, B., & Clegg, S. M. (2026) · International Journal for Parasitology · doi:10.1016/j.ijpara.2025.104768 · Cited by 1
Gonçalves, A. R., Ranganathan, H., Valdes, C., Zhu, H., Zhang, B., Kok, C. R., Martí, J. M., Mulakken, N., Thissen, J. B., Jaing, C. J., et al. (2026) · Frontiers in Microbiology · doi:10.3389/fmicb.2025.1695501 · Cited by 3
Akram, H. M., & Saliem, S. S. (2026) · Bacteria · doi:10.3390/bacteria5010011 · Cited by 1
“Recent cost-effectiveness analyses have shown that shallow shotgun metagenomics (1–5 million microbial reads) can still outperform 16S for detecting virulence genes and antibiotic resistance markers but may lack sufficient depth for comprehensive functional profiling or strain-level analysis [69].”
Toward reproducible pig gut microbiome profiling through standardized methodologies
Yergaliyev, T., Enokela, S. O., Eberhardt, G., Flisikowski, K., Hornburg, S. C., Reyer, H., Tetens, J., Wimmers, K., Zentek, J., & Camarinha‐Silva, A. (2026) · ISME Communications · doi:10.1093/ismeco/ycag097 · Cited by 1
“Moreover, MG sequencing can be problematic in samples with high host or feed DNA content and a relatively low microbial DNA fraction [25].”
Zielińska, K., Pantiukh, K., Org, E., Łabaj, P. P., & Kościółek, T. (2026) · mSystems · doi:10.1128/msystems.00144-26 · Cited by 2
“…in metagenomic contexts: Hillmann et al. demon strated that shallow shotgun sequencing imposes a fundamental ceiling on functional analysis that does not apply equally to taxonomic profiling, as low sequencing depth precludes de novo assembly of novel genes and genomic regions entirely (30).”
Mthembu, T. P., Hlongwane, N. L., Salawu-Rotimi, A., Hadebe, K., & Pierneef, R. (2026) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2026.1828785 · Cited by 1
Empirical evidence for gut microbial influence on human brain neurochemistry via the gut–brain axis
Johnstone, N., & Kadosh, K. C. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03813-y · Cited by 1
Thergarajan, G., & Bhassu, S. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.105866 · Cited by 1
Current Progress of Bioinformatics for Human Health
Zhao, J., Zhang, S., Wu, S., Zhang, W., & Su, X. (2023) · Translational bioinformatics · doi:10.1007/978-981-19-8210-1_8 · Cited by 2
Role and diversity of microbes in agriculture
Raja, N., Sajitha, T. P., Khan, M. L., & Ravikanth, G. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-90500-8.00022-1 · Cited by 1
How to navigate the many direct-to-consumer microbiota analyses and why to use them
Pierro, F. D., Bertuccioli, A., Cazzaniga, M., Matera, M., Cavecchia, I., Gerardi, V., Piccirelli, S., Salvi, D., Pugliano, C. L., Cesaro, P., et al. (2024) · Minerva Gastroenterology · doi:10.23736/s2724-5985.24.03799-9 · Cited by 1
Fleshner, M. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14587 · Cited by 1
“Shotgun metagenomics sequencing (both shallow and deep) allows species‐level bacteria identification and potential functional profiling of putative microbial signals/ function (Hillmann et al., 2018; Knight et al., 2018; Surana & Kasper, 2017).”
BackgroundThe Role of Genomics in Food Quality and Safety Management: Possibilities and Limitations
Gray, J. A., Hu, Y., Wilson, A., Chandry, P. S., Benlloch‐Tinoco, M., JORDAN, K. N., Fanning, S., & Fox, E. M. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-816395-5.00011-3 · Cited by 1
OBSOLETE: The Role of Genomics in Food Quality and Safety Management: Possibilities and Limitations
Gray, J. (2015) · Elsevier eBooks · doi:10.1016/b978-0-08-100596-5.00011-1 · Cited by 1
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Microbiomic Profiling of Food Processing Environments and Foods for Food Safety and Quality
Brehm‐Stecher, B. F., & Siragusa, G. R. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-822521-9.00237-9 · Cited by 1
Palacios, N., Gordon, S., Wang, T., Burk, R. D., Qi, Q., Huttenhower, C., González, H. M., Knight, R. D., DeCarli, C. S., Daviglus, M., et al. (2024) · medRxiv · doi:10.1101/2024.05.17.24307533 · Cited by 1
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Self-citationMetaFunPrimer: primer design for targeting genes observed in metagenomesPreprint
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Development of an oral swab based microbiome test for the detection of feline dental diseasePreprint
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インゲボルク・バッハマンの『30歳』(1961年)--主観性の闇を抜けて (宗教と文学研究)
山中, 博. (1999) · 福岡大学総合研究所報
Metadata
- Authors
- Hillmann, B., Al-Ghalith, G. A., Shields-Cutler, R. R., Zhu, Q., Gohl, D. M., Beckman, K. B., Knight, R., & Knights, D.
- Affiliations
- University of Minnesota (US)
- Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota, USA
- Biotechnology Institute, University of Minnesota, Minneapolis, Minnesota, USA
- University of California San Diego (US)
- Corresponding author
- Knights, Dan
- ORCID
- Venue
- mSystems
- Publisher
- American Society for Microbiology
- Published
- 2018-10-30
- Volume
- 3
- Issue
- 6
- ISSN
- 2379-5077 (ISSN-L)
- PMC
- PMC6234283
- OpenAlex
- W2951076599
- Cited by
- 474
- References
- 26
- Citations by year
- 2026: 52 · 2025: 66 · 2024: 57 · 2023: 61 · 2022: 60 · 2021: 82 · 2020: 68 · 2019: 24 · 2018: 2
- FWCI
- 15.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- mSystems (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- HHS | National Institutes of Health (R01AI121383, P01DK078669)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- 16S rRNA gene sequencing, functional metagenomics, amplicon sequencing
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