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      Compositional and Functional Analysis of the Microbiome in Tissue and Saliva of Oral Squamous Cell Carcinoma

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          Abstract

          Oral squamous cell carcinoma (OSCC) is affected by the interaction between oral pathogen and holobionts, or the combination of the host and its microbial communities. Studies have indicated the structure and feature of the microbiome in OSCC tissue and saliva, the relationships between microbiota and OSCC sites, stages remain unclear. In the present study, OSCC tissue (T), saliva (S) and mouthwash (W) samples were collected from the same subjects and carried out the microbiome study by 16S sequencing. The results showed the T group was significantly different from the S and W groups with the character of lower richness and diversity. Proteobacteria were most enriched in the T group at the phylum level, while Firmicutes were predominant in groups S and W. At the genus level, the predominant taxa of group T were Acinetobacter and Fusobacterium, and for group S and W, the predominant taxa were Streptococcus and Prevotella. The genera related to late stage tumors were Acinetobacter and Fusobacterium, suggesting microbiota may be implicated in OSCC developing. Both compositional and functional analyses indicated that microbes in tumor tissue were potential indicator for the initiation and development of OSCC.

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          FLASH: fast length adjustment of short reads to improve genome assemblies.

          Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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            Defining the healthy "core microbiome" of oral microbial communities

            Background Most studies examining the commensal human oral microbiome are focused on disease or are limited in methodology. In order to diagnose and treat diseases at an early and reversible stage an in-depth definition of health is indispensible. The aim of this study therefore was to define the healthy oral microbiome using recent advances in sequencing technology (454 pyrosequencing). Results We sampled and sequenced microbiomes from several intraoral niches (dental surfaces, cheek, hard palate, tongue and saliva) in three healthy individuals. Within an individual oral cavity, we found over 3600 unique sequences, over 500 different OTUs or "species-level" phylotypes (sequences that clustered at 3% genetic difference) and 88 - 104 higher taxa (genus or more inclusive taxon). The predominant taxa belonged to Firmicutes (genus Streptococcus, family Veillonellaceae, genus Granulicatella), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Corynebacterium, Rothia, Actinomyces), Bacteroidetes (genus Prevotella, Capnocytophaga, Porphyromonas) and Fusobacteria (genus Fusobacterium). Each individual sample harboured on average 266 "species-level" phylotypes (SD 67; range 123 - 326) with cheek samples being the least diverse and the dental samples from approximal surfaces showing the highest diversity. Principal component analysis discriminated the profiles of the samples originating from shedding surfaces (mucosa of tongue, cheek and palate) from the samples that were obtained from solid surfaces (teeth). There was a large overlap in the higher taxa, "species-level" phylotypes and unique sequences among the three microbiomes: 84% of the higher taxa, 75% of the OTUs and 65% of the unique sequences were present in at least two of the three microbiomes. The three individuals shared 1660 of 6315 unique sequences. These 1660 sequences (the "core microbiome") contributed 66% of the reads. The overlapping OTUs contributed to 94% of the reads, while nearly all reads (99.8%) belonged to the shared higher taxa. Conclusions We obtained the first insight into the diversity and uniqueness of individual oral microbiomes at a resolution of next-generation sequencing. We showed that a major proportion of bacterial sequences of unrelated healthy individuals is identical, supporting the concept of a core microbiome at health.
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              Human papillomavirus and oral cancer: the International Agency for Research on Cancer multicenter study.

              Human papillomavirus (HPV), the causal agent of cervical cancer, appears to be involved in the etiology of cancer of the oral cavity and oropharynx. To investigate these associations, we conducted a multicenter case-control study of cancer of the oral cavity and oropharynx in nine countries. We recruited 1670 case patients (1415 with cancer of the oral cavity and 255 with cancer of the oropharynx) and 1732 control subjects and obtained an interview, oral exfoliated cells, and blood from all participants and fresh biopsy specimens from case patients. HPV DNA was detected by polymerase chain reaction (PCR). Antibodies against HPV16 L1, E6, and E7 proteins in plasma were detected with enzyme-linked immunosorbent assays. Multivariable models were used for case-control and case-case comparisons. HPV DNA was detected in biopsy specimens of 3.9% (95% confidence interval [CI] = 2.5% to 5.3%) of 766 cancers of the oral cavity with valid PCR results and 18.3% (95% CI = 12.0% to 24.7%) of 142 cancers of the oropharynx (oropharynx and tonsil combined) with valid PCR results. HPV DNA in cancer biopsy specimens was detected less frequently among tobacco smokers and paan chewers and more frequently among subjects who reported more than one sexual partner or who practiced oral sex. HPV16 DNA was found in 94.7% of HPV DNA-positive case patients. HPV DNA in exfoliated cells was not associated with cancer risk or with HPV DNA detection in biopsy specimens. Antibodies against HPV16 L1 were associated with risk for cancers of the oral cavity (odds ratio [OR] = 1.5, 95% CI = 1.1 to 2.1) and the oropharynx (OR = 3.5, 95% CI = 2.1 to 5.9). Antibodies against HPV16 E6 or E7 were also associated with risk for cancers of the oral cavity (OR = 2.9, 95% CI = 1.7 to 4.8) and the oropharynx (OR = 9.2, 95% CI = 4.8 to 17.7). HPV appears to play an etiologic role in many cancers of the oropharynx and possibly a small subgroup of cancers of the oral cavity. The most common HPV type in genital cancers (HPV16) was also the most common in these tumors. The mechanism of transmission of HPV to the oral cavity warrants further investigation.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 June 2019
                2019
                : 10
                : 1439
                Affiliations
                [1] 1Department of Oral Maxillofacial Head and Neck Oncology, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai, China
                [2] 2Shanghai Key Laboratory of Stomatology, Shanghai Research Institute of Stomatology, National Clinical Research Center of Stomatology , Shanghai, China
                [3] 3Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University , Beijing, China
                [4] 4College of Life Sciences, Qilu Normal University , Jinan, China
                [5] 5Shandong Children’s Microbiome Center, Qilu Children’s Hospital of Shandong University , Jinan, China
                [6] 6Qingdao Human Microbiome Center, The Affiliated Central Hospital of Qingdao University , Qingdao, China
                [7] 7Shandong Provincial Key Laboratory of Oral Tissue Regeneration, School of Stomatology, Shandong University , Jinan, China
                [8] 8Department of Human Microbiome, School of Stomatology, Shandong University , Jinan, China
                [9] 9State Key Laboratory of Microbial Technology, Shandong University , Qingdao, China
                [10] 10School of Information Science and Engineering, Shandong Normal University , Jinan, China
                Author notes

                Edited by: Nezar Al-hebshi, Temple University, United States

                Reviewed by: Renee Maxine Petri, University of Veterinary Medicine Vienna, Austria; Ranju Ralhan, Icahn School of Medicine at Mount Sinai, United States; Waleed Abu Al-Soud, Al Jouf University, Saudi Arabia

                *Correspondence: Lei Zhang, microbiome@ 123456foxmail.com

                These authors have contributed equally to this work

                This article was submitted to Systems Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2019.01439
                6607966
                31297102
                300dcf6b-d3c9-467d-a01c-dcb73cf144cc
                Copyright © 2019 Zhang, Yang, Feng, Chen, Li, Liang, Li, Li, Xu, Zhang and Chen.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 February 2019
                : 07 June 2019
                Page count
                Figures: 7, Tables: 1, Equations: 0, References: 55, Pages: 11, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 2016YFC0902700
                Award ID: 81472572
                Award ID: 91229103
                Award ID: 31471202
                Funded by: Shanghai Science and Technology Development Foundation 10.13039/100012543
                Funded by: Taishan Scholar Foundation of Shandong Province 10.13039/100012620
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                16s rrna gene,microbiota,oscc,cross-sectional study,salivary and oscc bacteriome

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