Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease.
Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease.
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DOI：
10.3389/fcimb.2020.588155
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发表时间：
2020
影响因子：
5.7
通讯作者：
Belibasakis GN
中科院分区：
文献类型：
--
作者：
Bao K;Li X;Poveda L;Qi W;Selevsek N;Gumus P;Emingil G;Grossmann J;Diaz PI;Hajishengallis G;Bostanci N;Belibasakis GN
由于缺乏足够的组织提取方法，绘制牙龈组织蛋白质组和微生物组的努力受到阻碍。压力循环技术（PCT）是一种新兴的平台，用于可重现的组织均质化和改善的序列检索覆盖率。因此，我们采用PCT来表征健康和患病牙龈组织中的蛋白质组和微生物组特征。健康和患病的对侧牙龈组织样本（共n = 10），从5个全身健康的个人（51.6 ± 4.3岁）与广泛的慢性牙周炎。然后使用Barocycler裂解并消化组织，制备蛋白质并提交用于质谱分析，并提交微生物组DNA用于16 S rRNA谱分析。总的来说，定量了1，366种人类蛋白质（错误发现率0.22%），其中69种蛋白质在牙周病部位与健康部位相比差异表达（≥2种肽且p < 0.05，62种上升，7种下降）。这些主要是细胞外或囊泡相关蛋白，具有分子转运功能。在微生物组水平上，确定了362个物种水平的操作分类单位。其中，14种优势种占总相对丰度的80%以上，而11种在健康和患病地点之间存在显著差异。其中，密螺旋体HMT 253和船形梭杆菌HMT 253与疾病部位相关，分别与30个和6个上调蛋白强烈相互作用（r > 0.7）。健康位点相关菌株前庭链球菌、韦荣氏球菌、月单胞菌属HMT 478和Leptotrichia sp. HMT 417分别与31、21、9和18个上调蛋白质表现出强烈的负相互作用（r <-0.7）。相反，下调的蛋白质没有显示出与受调控的细菌的强相互作用。本研究通过采用PCT辅助工作流程鉴定了人类牙龈的蛋白质组和组织内微生物组谱。这是第一份证明分析健康和疾病部位牙龈组织完整蛋白质组谱的可行性的报告，同时破译组织部位特异性微生物组特征。
Efforts to map gingival tissue proteomes and microbiomes have been hampered by lack of sufficient tissue extraction methods. The pressure cycling technology (PCT) is an emerging platform for reproducible tissue homogenisation and improved sequence retrieval coverage. Therefore, we employed PCT to characterise the proteome and microbiome profiles in healthy and diseased gingival tissue. Healthy and diseased contralateral gingival tissue samples (total n = 10) were collected from five systemically healthy individuals (51.6 ± 4.3 years) with generalised chronic periodontitis. The tissues were then lysed and digested using a Barocycler, proteins were prepared and submitted for mass spectrometric analysis and microbiome DNA for 16S rRNA profiling analysis. Overall, 1,366 human proteins were quantified (false discovery rate 0.22%), of which 69 proteins were differentially expressed (≥2 peptides and p < 0.05, 62 up, 7 down) in periodontally diseased sites, compared to healthy sites. These were primarily extracellular or vesicle-associated proteins, with functions in molecular transport. On the microbiome level, 362 species-level operational taxonomic units were identified. Of those, 14 predominant species accounted for >80% of the total relative abundance, whereas 11 proved to be significantly different between healthy and diseased sites. Among them, Treponema sp. HMT253 and Fusobacterium naviforme and were associated with disease sites and strongly interacted (r > 0.7) with 30 and 6 up-regulated proteins, respectively. Healthy-site associated strains Streptococcus vestibularis, Veillonella dispar, Selenomonas sp. HMT478 and Leptotrichia sp. HMT417 showed strong negative interactions (r < −0.7) with 31, 21, 9, and 18 up-regulated proteins, respectively. In contrast the down-regulated proteins did not show strong interactions with the regulated bacteria. The present study identified the proteomic and intra-tissue microbiome profile of human gingiva by employing a PCT-assisted workflow. This is the first report demonstrating the feasibility to analyse full proteome profiles of gingival tissues in both healthy and disease sites, while deciphering the tissue site-specific microbiome signatures.
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影响因子：
4.3
作者：
Demmer RT;Behle JH;Wolf DL;Handfield M;Kebschull M;Celenti R;Pavlidis P;Papapanou PN
通讯作者：
Papapanou PN
影响因子：
4.4
作者：
Bostanci, Nagihan;Ramberg, Per;Papapanou, Panos N.
通讯作者：
Papapanou, Panos N.
影响因子：
4.6
作者：
Bao K;Bostanci N;Thurnheer T;Belibasakis GN
通讯作者：
Belibasakis GN
影响因子：
7.6
作者：
Baek, K.;Ji, S.;Choi, Y.
通讯作者：
Choi, Y.
影响因子：
2.6
作者：
Chi, B;Qi, M;Kuramitsu, HK
通讯作者：
Kuramitsu, HK