Whole genome analysis and in vivo safety assessment of probiotic candidate Lactobacillus acidophilus L177
Open accessAbstract
Probiotics, particularly strains of lactic acid bacteria (LAB), are recognized for their beneficial effects on gut health. Lactobacillus acidophilus L177, a promising probiotic strain isolated from canine feces, was evaluated for safety and probiotic properties through whole genome sequencing and a 28-day subacute oral toxicity study in C57BL/6 mice. The toxicity study involved daily administration of L177 at doses of 108, 109, and 1010 CFU/mL, with continuous monitoring of general health, behavioral changes, and physiological parameters. Body weight, food and water intake, hematological and biochemical indices, organ weights, and histopathology were assessed. No significant adverse effects were observed, and proinflammatory cytokines (TNF-α, IL-6, IL-1β) remained undetectable in serum, indicating an absence of inflammatory response. Statistical analysis confirmed no significant differences in key health markers between treated and control groups (p > 0.05). Whole genome sequencing revealed a single chromosome of approximately 1,972,211 base pairs (GC content: 35.02%) with 1 CRISPR sequence and 1,955 genes. Functional annotation highlighted genes associated with metabolism, information processing, and cellular functions. Antibiotic Resistance Gene analysis identified one AMR gene (lnu(C)), but phenotypic tests confirmed L177 is sensitive to clindamycin and lincomycin. Sixty-seven virulence-associated genes were detected, mainly related to structure, metabolism, and regulation. These findings support the safety and probiotic potential of L. acidophilus L177 for potential applications in both animal and human health.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Whole-genome sequencing-based genomic screening allows in silico detection of antibiotic resistance genes, virulence-associated factors, and mobile genetic elements, providing a basis for modern probiotic safety evaluation.
“Whole-genome sequencing-based genomic screening allows for the in silico detection of antibiotic resistance genes, virulence-associated factors, and mobile genetic elements, thus providing a basis for modern probiotic safety evaluation [20,133,155,156].”
From Current Concepts in Probiotic Safety and Efficacy (2026) · cites this paper as [155]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232 · see citing works
Prodigal: prokaryotic gene recognition and translation initiation site identification
Hyatt, D., Chen, G.-L., LoCascio, P. F., Land, M., Larimer, F. W., & Hauser, L. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-119 · Cited by 12,426 · see citing works
tRNAscan-SE: A Program for Improved Detection of Transfer RNA Genes in Genomic Sequence
Lowe, T. M., & Eddy, S. R. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.5.955 · Cited by 11,120 · see citing works
Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads
Wick, R. R., Judd, L. M., Gorrie, C. L., & Holt, K. E. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005595 · Cited by 8,728 · see citing works
Huerta‐Cepas, J., Szklarczyk, D., Heller, D., Hernández-Plaza, A., Forslund, S. K., Cook, H., Mende, D. R., Letunić, I., Rattei, T., Jensen, L. J., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1085 · Cited by 4,943 · see citing works
The Gene Ontology (GO) database and informatics resource
Gene Ontology Consortium (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh036 · Cited by 4,533 · see citing works
Bland, C., Ramsey, T. L., Sabree, F., Lowe, M., Brown, K., Kyrpides, N. C., & Hugenholtz, P. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-209 · Cited by 1,038 · see citing works
Bennett, P. M. (2008) · British Journal of Pharmacology · doi:10.1038/sj.bjp.0707607 · Cited by 895 · see citing works
Horizontal transfer of antibiotic resistance genes in clinical environments
Lerminiaux, N. A., & Cameron, A. D. S. (2018) · Canadian Journal of Microbiology · doi:10.1139/cjm-2018-0275 · Cited by 807 · see citing works
Probiotics: mechanism of action, health benefits and their application in food industries
Latif, A., Shehzad, A., Niazi, S., Zahid, A., Ashraf, W., Iqbal, M. W., Rehman, A., Riaz, T., Aadil, R. M., Khan, I. M., et al. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1216674 · Cited by 633 · see citing works
Current status of probiotic and related health benefits
Das, T. K., Pradhan, S., Chakrabarti, S., Mondal, K. C., & Ghosh, K. (2022) · Applied Food Research · doi:10.1016/j.afres.2022.100185 · Cited by 294 · see citing works
Dong, P., Wang, H., Fang, T., Wang, Y., & Ye, Q. (2019) · Environment International · doi:10.1016/j.envint.2019.01.050 · Cited by 267 · see citing works
Gao, H., Li, X., Chen, X., Deng, H., Wei, C., Zhang, L., & Li, P. (2022) · Journal of Microbiology and Biotechnology · doi:10.4014/jmb.2205.05041 · Cited by 174 · see citing works
Whole genome sequencing for the risk assessment of probiotic lactic acid bacteria
Peng, X., Ed‐Dra, A., & Yue, M. (2022) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2022.2087174 · Cited by 148 · see citing works
Zhou, J. S., Shu, Q., Rutherfurd, K. J., Prasad, J., Gopal, P. K., & Gill, H. S. (2000) · Food and Chemical Toxicology · doi:10.1016/s0278-6915(99)00154-4 · Cited by 131 · see citing works
Khalid, A., Jaffar, M. A., Khan, T., Lail, R. A., Ali, S., Aktaş, G., Waris, A., Javaid, A., Ijaz, N., & Muhammad, N. (2021) · Hematology · doi:10.1080/16078454.2021.1950898 · Cited by 121 · see citing works
Probiotic mechanisms of action
Halloran, K., & Underwood, M. A. (2019) · Early Human Development · doi:10.1016/j.earlhumdev.2019.05.010 · Cited by 116 · see citing works
Evolutionary history and pan-genome dynamics of strawberry ( Fragaria spp.)
Qiao, Q., Edger, P. P., Xue, L., Qiong, L., Lu, J., Zhang, Y., Cao, Q., Yocca, A. E., Platts, A. E., Knapp, S. J., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2105431118 · Cited by 108 · see citing works
Pourjafar, H., Ansari, F., Sadeghi, A., Samakkhah, S. A., & Jafari, S. M. (2022) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2022.2047883 · Cited by 103 · see citing works
Functional Genomics of Host–Microbiome Interactions in Humans
Luca, F., Kupfer, S. S., Knights, D., Khoruts, A., & Blekhman, R. (2017) · Trends in Genetics · doi:10.1016/j.tig.2017.10.001 · Cited by 99 · see citing works
Wang, Y., Liang, Q., Lu, B., Shen, H., Liu, S., Shi, Y., Leptihn, S., Li, H., Wei, J., Liu, C., et al. (2021) · BMC Genomics · doi:10.1186/s12864-021-07539-9 · Cited by 88 · see citing works
Exploring the potential impact of probiotic use on drug metabolism and efficacy
Purdel, C. N., Ungurianu, A., Adam-Dima, I., & Margina, D. M. (2023) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2023.114468 · Cited by 63 · see citing works
Devarajan, A. R., Mudgil, P., Aldhaheri, F., Hamed, F., Dhital, S., & Maqsood, S. (2022) · Journal of Dairy Science · doi:10.3168/jds.2021-20745 · Cited by 60 · see citing works
Safety Assessment of Bacillus subtilis MB40 for Use in Foods and Dietary Supplements
Spears, J. L., Kramer, R., Nikiforov, A. I., Rihner, M. O., & Lambert, E. A. (2021) · Nutrients · doi:10.3390/nu13030733 · Cited by 51 · see citing works
The Role of Carbohydrate Intake on the Gut Microbiome: A Weight of Evidence Systematic Review
Mora-Flores, L. P., Moreno-Terrazas, R., Fuentes-Cabrera, J., Pérez-Vicente, H. A., de Anda‐Jáuregui, G., & Neri-Torres, E. E. (2023) · Microorganisms · doi:10.3390/microorganisms11071728 · Cited by 51 · see citing works
Mahjoory, Y., Mohammadi, R., Hejazi, M. A., & Nami, Y. (2023) · Scientific Reports · doi:10.1038/s41598-023-27721-1 · Cited by 50 · see citing works
Thumu, S. C. R., & Halami, P. M. (2019) · Journal of the Science of Food and Agriculture · doi:10.1002/jsfa.10071 · Cited by 35 · see citing works
Ou, D., Ling, N., Wang, X., Zou, Y., Dong, J., Zhang, D., Shen, Y., & Ye, Y. (2022) · Foods · doi:10.3390/foods11152177 · Cited by 34 · see citing works
Zhao, L., Zhang, Y., Liu, Y., Zhong, J., & Zhang, D. (2023) · Microorganisms · doi:10.3390/microorganisms11010140 · Cited by 33 · see citing works
Self-citationHsu, H., Liao, Y.-C., Lin, S.-H., Lin, J., Lee, C., & Watanabe, K. (2022) · Microorganisms · doi:10.3390/microorganisms10040784 · Cited by 31 · see citing works
Karameşe, M., Aydın, H., Gelen, V., Şengül, E., & Karameşe, S. A. (2020) · Future Microbiology · doi:10.2217/fmb-2020-0005 · Cited by 27 · see citing works
Multi-functional properties of lactic acid bacteria strains derived from canine feces
Liu, Y., Wang, J., Zheng, H., Xin, J., Zhong, Z., Liu, H., Fu, H., Zhou, Z., Qiu, X., & Peng, G. (2024) · Frontiers in Veterinary Science · doi:10.3389/fvets.2024.1404580 · Cited by 19 · see citing works
Self-citationEnhancing Food Sustainability through Probiotics Isolated from Fermented Cauliflower
Rachwał, K., Gustaw, K. M., & Sadok, I. (2024) · Sustainability · doi:10.3390/su16198340 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Current Concepts in Probiotic Safety and Efficacy
Churin, A. A., Sokolyanskaya, L. O., Lukina, A. P., & Karnachuk, O. V. (2026) · Nutrients · doi:10.3390/nu18040696 · Cited by 31 · see citing works
“Whole-genome sequencing-based genomic screening allows for the in silico detection of antibiotic resistance genes, virulence-associated factors, and mobile genetic elements, thus providing a basis for modern probiotic safety evaluation [20,133,155,156].”
Presutto, E., Capozzi, V., Chiara, M., Drider, D., Spano, G., & Fragasso, M. (2026) · World Journal of Microbiology and Biotechnology · doi:10.1007/s11274-026-04872-7 · Cited by 10 · see citing works
Sharma, I., Bharti, S., Pandey, S., Gupta, S., Bisen, P. S., Kango, N., & Sharma, K. K. (2026) · Food Nutrition · doi:10.1016/j.fnutr.2026.100067 · Cited by 3 · see citing works
Joseph, A., Salini, S. V., Narsimlu, B., kumar, S., Kumari, M., & Behare, P. V. (2026) · Food and Chemical Toxicology · doi:10.1016/j.fct.2026.116060 · Cited by 2 · see citing works
Chen, M., Lao, J., Tan, L., Zhang, L., Li, J., Wang, B., Lv, S., Yan, S., Wen, Z., Chen, B., et al. (2026) · Journal of Functional Foods · doi:10.1016/j.jff.2026.107245
Using AI to Profile Egyptian Lactobacillus for Next Generation Functional Foods
El-Moez, S. I. A., Seadawy, M. G., El-Hosseny, M. F., Kelany, M. A. E., Ageez, A. M., AbdElwahab, M. G., Ghareeb, A. Z., Zayed, M. A., Ghareeb, D. A., & Soliman, A. M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3121-8.ch007
Probiotic Strain Identification: Current and Future Approaches
Begum, K., Rahman, M. S., & Ema, N. J. (2026) · Asian Journal of Pharmaceutical and Health Sciences · doi:10.5530/ajphs.2026.16.88
Chen, X.-T., Wang, Q.-S., Guo, X.-Y., Li, D., Wu, X., Li, X.-Y., Zheng, X., Li, Y.-Y., Han, S., Feng, L., et al. (2026) · Microorganisms · doi:10.3390/microorganisms14051090
Anadol, E., Kara, A., Tezer, H., Sezer, Ş. C., Yığman, Z., Billur, D., Kara, B. A., Söylemez, S., Aytekin, S. Y., & Arslan, M. (2026) · Research Square · doi:10.21203/rs.3.rs-11113544/v1
Zhang, L., Chen, M., Wen, Z., Li, J., Chen, B., Ju, X., Ma, Y., Yanhong, Y., Ma, X., Yan, S., et al. (2026) · Microorganisms · doi:10.3390/microorganisms14102222
Jun, Q., Chen, Z., Liu, H., Zhang, Y., Xie, H., Cao, Y., & Wang, Q. (2026) · Food Bioscience · doi:10.1016/j.fbio.2026.110216
Self-citation
- Authors
- Liu, Y., Zheng, H., Wang, J., Xin, J., Wu, R., Zhang, J., Zhong, Z., Liu, H., Huang, Y., Fu, H., Zhou, Z., & Peng, G.
- Affiliations
- Sichuan Agricultural University (CN)
- Corresponding author
- Peng, Guangneng
- ORCID
- Venue
- BMC Microbiology
- Published
- 2025-07-02
- Volume
- 25
- Issue
- 1
- Pages
- 398-398
- ISSN
- 1471-2180 (ISSN-L)
- PMC
- PMC12217917
- OpenAlex
- W4411923497
- Cited by
- 9
- References
- 34
- Citations by year
- 2026: 9
- FWCI
- 4.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Microbiology (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Life Sciences › Immunology and Microbiology › Immunology › Aquaculture disease management and microbiota
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Keywords
- probiotic safety, whole genome sequencing, subacute oral toxicity, lactic acid bacteria, inflammatory cytokines, virulence genes, antibiotic resistance genes, gut health
- MeSH terms
- Whole Genome Sequencing, Animals, Feces, Female, Lactobacillus acidophilus, Male, Mice, Inbred C57BL, Cytokines, Genome, Bacterial, Probiotics, Mice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
