Single cell transcriptomic analysis of human mesenchymal stem cells reveals limited heterogeneity

人臍帶間充質(zhì)干細(xì)胞單細(xì)胞轉(zhuǎn)錄組文章掌腰，探索人臍帶間充質(zhì)干細(xì)胞的異質(zhì)性老客，文章鏈接：Cell Death and Disease

Abstract

間充質(zhì)干細(xì)胞（MSC）是一群多能細(xì)胞棕诵，具有通過調(diào)節(jié)再生和炎癥優(yōu)異的促進(jìn)組織修復(fù)能力。MSCs在疾病治療中的療效依賴于產(chǎn)生的同源性細(xì)胞群體的相對數(shù)量棍丐。但是，體外擴(kuò)增培養(yǎng)的MSCs的細(xì)胞異質(zhì)性和分化的軌跡（方向）尚未闡明壶唤。文章分析了來源于兩個臍帶（UC-MSCs）的361個MSCs單細(xì)胞轉(zhuǎn)錄組杨拐。對這些收獲于不同時期的UC-MSCs采用炎癥因子刺激或者不刺激。通過加權(quán)基因相關(guān)網(wǎng)絡(luò)分析意外發(fā)現(xiàn)UC-MSCs僅僅擁有有限的異質(zhì)性且與供體和細(xì)胞代際無關(guān)瀑踢。同時扳还，還發(fā)現(xiàn)用炎性細(xì)胞因子（IFNγ和TNFα）預(yù)處理后，這種經(jīng)典的策略可以提高M(jìn)SCs的治療效果橱夭，并且處理后MSCs的基因表達(dá)出現(xiàn)一致性的變化普办。基于細(xì)胞周期依賴的主成分分析顯示徘钥，鑒定出具有有限異質(zhì)性的這些UC-MSC與它們進(jìn)入G2 / M期密切相關(guān)。并觀察到特異性基因CD168以細(xì)胞周期依賴性方式表達(dá)肢娘。CD168陽性的細(xì)胞體外分選和培養(yǎng)時呈础，CD168的表達(dá)依然顯示出對周期的依賴舆驶。研究結(jié)果表明，體外擴(kuò)增的UC-MSCs是一群具有以細(xì)胞周期為主的有限異質(zhì)性的細(xì)胞而钞。因此沙廉，本研究為基于MSCs的疾病治療提供了標(biāo)準(zhǔn)化的信息。

Introduction

間充質(zhì)干細(xì)胞（MSCs）是由俄羅斯科學(xué)家Alexander Friedenstein在20世紀(jì)60年代后期從骨髓（BM）中發(fā)現(xiàn)的多能細(xì)胞臼节，他觀察到骨髓是生物體出生后間充質(zhì)組織的干細(xì)胞庫¹撬陵。如今，MSCs的鑒定基于它們的成纖維細(xì)胞樣形態(tài)网缝，一系列的表面標(biāo)志物表達(dá)狀態(tài)及其三系分化潛能²巨税。由于MSCs的自我更新特性和多重分化潛能，體外擴(kuò)增MSCs在再生醫(yī)療中具有廣闊的前景粉臊。
(人們)已經(jīng)可以從各種組織和器官中分離出來MSCs草添，盡管骨髓來源的MSCs最廣泛地用于潛在的治療探索，臍帶來源的UC-MSCs似乎更適合于臨床應(yīng)用扼仲。與BM-MSCs相比远寸，UC-MSCs更易于大量獲取，省去了骨髓穿刺的麻煩屠凶。重要的是,UC-MSCs源于生命的早期階段驰后，并且在體內(nèi)移植中，具有較低的免疫原性矗愧。盡管UC-MSCs主要用于異體移植治療灶芝，但是它們的治療效果已經(jīng)在一些臨床前和臨床研究中得到了證實(shí)^3,4。
在過去十幾年中贱枣，由于MSCs的棉衣調(diào)節(jié)能力监署，顯示出MSCs在組織再生的臨床應(yīng)用與管控炎癥性疾病中取得了令人矚目的成就。MSCs在治療炎癥性疾病具有驚人的效果纽哥，首先發(fā)現(xiàn)于一名患有類固醇和環(huán)孢菌素抗性GvHD5的9歲患者⁵钠乏；然而，這一治療效果并不使總能復(fù)現(xiàn)⁶春塌∠埽考慮到炎癥在調(diào)動MSCs免疫抑制能力關(guān)鍵作用，一系列的臨床治療采用聯(lián)合IFNγ and TNFα炎性細(xì)胞因子來體外預(yù)處理MSCs只壳，從而改善了MSCs在自身免疫性疾病的治療效果^7,8俏拱。MSCs精確表達(dá)的諸如CCL5，CXCL9吼句，吲哚胺2,3-雙加氧酶（IDO）锅必，前列腺素內(nèi)過氧化物合酶2（PTGS2）趨化因子和免疫抑制因子。TSG6能被炎癥細(xì)胞因子誘導(dǎo)并通過協(xié)同作用導(dǎo)致免疫抑制⁹。

在限制MSCs在臨床應(yīng)用中的療效的突出因素中搞隐，MSCs群體的標(biāo)準(zhǔn)化被歸于首位驹愚。依據(jù)文獻(xiàn)報道，MSCs在體外擴(kuò)增中存在形態(tài)和增殖速率方面存在差異¹⁰ 劣纲。此外逢捺，來自不同克隆的MSCs展現(xiàn)出不同的克隆集落形成和分化能力¹¹。這些證據(jù)表明癞季，來自不同供體劫瞳，組織，克隆甚至來自同一克隆集落的不同細(xì)胞的MSCs可能存在異質(zhì)性¹²绷柒。

在對遲發(fā)型超敏反應(yīng)（DTH）的小鼠模型先前的研究中志于，發(fā)現(xiàn)從不同供體分離的MSC對治療DTH13顯示出明顯的療效差異¹³。因此辉巡，克隆間異質(zhì)性可能是臨床試驗(yàn)結(jié)果不一致解釋恨憎。單細(xì)胞測序的進(jìn)步為探索單細(xì)胞水平的細(xì)胞異質(zhì)性提供了一種獨(dú)特的方法。迄今為止郊楣，關(guān)于人類MSCs的大多數(shù)研究都是基于混合群體憔恳，迫切需要對MSC的單細(xì)胞分析進(jìn)行詳細(xì)研究，以闡明各種特性的變化净蚤。

本研究中钥组，我們采用了最新的微流體單細(xì)胞捕獲系統(tǒng)和高通量測序技術(shù)研究人UC-MSCs的轉(zhuǎn)錄組學(xué)的異質(zhì)性。我們分析了361個UC-MSCs今瀑。其中的159個暴露與炎性細(xì)胞因子中程梦。研究發(fā)現(xiàn)，培養(yǎng)的UC-MSCs存在細(xì)胞亞群橘荠∮旄剑基于加權(quán)基因相關(guān)網(wǎng)絡(luò)分析（WGCNA）^14,15，發(fā)現(xiàn)UC-MSCs的異質(zhì)性由某些關(guān)鍵基因模塊所決定哥童。通過對這些基因的進(jìn)一步分析發(fā)現(xiàn)挺份，細(xì)胞周期分布是UC-MSC中異質(zhì)性來源的重要原因。結(jié)合其他一些研究的信息贮懈，我們的結(jié)果表明UC-MSCs是一群相對同源的細(xì)胞群匀泊，并且分離和擴(kuò)增方案中的標(biāo)準(zhǔn)化具有較高的可能獲得更好的臨床療效。

Results

Heterogeneity in human umbilical cord derived MSCs（臍帶來源的MSCs的異質(zhì)性）

單細(xì)胞轉(zhuǎn)錄組分析已經(jīng)被廣泛用于識別細(xì)胞信號和揭示細(xì)胞發(fā)育軌跡朵你。為了檢測MSCs的異質(zhì)性增加它們在臨床上的應(yīng)用各聘。我們從臍帶中分離MSCs，體外擴(kuò)增培養(yǎng)抡医，采用單細(xì)胞轉(zhuǎn)錄組測序 (Fig. 1a）躲因。這些體外擴(kuò)增培養(yǎng)的UC-MSCs滿足MSCs的定義要求，CD73, CD90, CD105的細(xì)胞表面標(biāo)記呈陽性，CD31毛仪，CD34搁嗓，CD45和HLA-DR的呈陰性。(Fig. S1).

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我們基于Fluidigm C1自動制備系統(tǒng)和96×96集成流體回路箱靴，分離得到單個的UC-MSCs（52個來自供體1的第5代細(xì)胞，50個細(xì)胞來自供體2的第0代細(xì)胞荷愕，50個細(xì)胞來自供體2的第2代細(xì)胞衡怀，50個細(xì)胞來自供體2的第5代細(xì)胞）(Fig. 1b) 。經(jīng)過RNA提取安疗，cDNA預(yù)擴(kuò)增和測序質(zhì)量控制后抛杨，我們制備了所有的361個細(xì)的cDNA文庫（159個細(xì)胞和202個沒有刺激的細(xì)胞），利用Illumina HiSeq 2500系統(tǒng)對這些細(xì)胞進(jìn)行轉(zhuǎn)錄組測序荐类。并在高靈敏度DNA測定中證明了其高度均一性(Fig. S2)怖现。

通過對單細(xì)胞轉(zhuǎn)錄組數(shù)據(jù)分析，202個未處理細(xì)胞使用外加標(biāo)1,4,7的RNA或ERCC作為內(nèi)參玉罐，識別 出高度可變的基因屈嗤，并通過主成分分析，在所有的四個數(shù)據(jù)集中發(fā)現(xiàn)了（huc2_p0吊输， huc2_p2饶号，huc2_p5，huc1_p5）幾個亞群(Fig. 1c)季蚂。
在被檢測的基因中茫船，經(jīng)過低表達(dá)基因過濾(在至少1/10細(xì)胞中檢測到，每個細(xì)胞平均1個讀數(shù)）54??98個基因中的4753個被保留扭屁，這些基因所在的數(shù)據(jù)集被用于WGCNA分析算谈。結(jié)果顯示，對于原代UC-MSCs,the blue module (藍(lán)色模塊)（0.79料滥，huc2_p0中p = 1×10-11）和 the turquoise module(綠松石模塊)（0.95然眼，huc2_p0中p = 2×10-26）與huc2_p0亞群中的第3組和第2組顯著相關(guān)(Fig. 1d)。在第四個數(shù)據(jù)集中發(fā)現(xiàn)了類似的結(jié)果(Fig. S3). 幔欧。Venn圖顯示四個數(shù)據(jù)集中的藍(lán)色模塊和綠松石模塊共享基因Fig. S4)罪治。 Z得分（Z-summary score）表明（藍(lán)色：huc1_p5：15.43，huc2_p2：15.67礁蔗，huc2_p5：9.47;綠松石：huc1：43.73觉义，huc2_p2：46.63，huc2_p5：32.19）的基因是高度保守的 (Fig. 1e)浴井。這些結(jié)果表明晒骇，人類UC-MSC中存在亞群，并且這些亞群保守而不依賴于供體和傳代。
為了找到不同MSCs亞群的特征標(biāo)記洪囤，我們掃描了藍(lán)色模塊和綠松石模塊中的徒坡，那些在一個特定組中高表達(dá)的基因，并存在至少一個數(shù)據(jù)集中 (Fig. S5, group 3 in dataset huc1, group 2 in dataset huc2_P0, group 3 in dataset huc2_P2, and group 4 in dataset huc2_P5). 隨后識別出七個特征基因：brca1瘤缩，cdca5喇完，hmgb1，hmmr / cd168剥啤，melk锦溪，prc1和racgap1。它們在四個子集中的表達(dá)模式相似府怯，選取huc2_p0作為代表 (Fig. 1f 和
Fig. S5). 與其他組相比刻诊，這7個基因在第2組中的表達(dá)顯著升高∥總之则涯，我們發(fā)現(xiàn)UC-MSCs在某些基因的表達(dá)時具有異質(zhì)性。

Inflammatory cytokines stimulated MSCs subpopulations also exhibit heterogeneity in the featured genes 炎性細(xì)胞因子刺激的MSCs亞群也在特征基因中表現(xiàn)出異質(zhì)性

MSCs最獨(dú)特的特征之一冲簿，是它們的免疫抑制功能和治療各種炎性疾病的有效性粟判。如今關(guān)注的問題是在MSCs細(xì)胞中炎癥誘導(dǎo)的基因表達(dá)是否存在異質(zhì)性。在用IFNγ和TNFα刺激后民假，分析了159個UC-MSCs細(xì)胞huc1_sti_p5浮入，huc2_sti_p2和huc2_sti_p5）(Figs 1a and 2a)。通過無偏的層次聚類羊异，在所有的數(shù)據(jù)集中識別出了一個明顯的亞群(Fig. 2b and Fig. S6)阀参。WGCNA分析顯示桥胞，綠松石和藍(lán)色模塊在不同的數(shù)據(jù)集中具有顯著的相關(guān)性和保守性峡钓。另外巾遭，這兩個模塊中大量的基因與未處理組中的基因相似(Fig. 2c, d and Fig. S7)。有趣的是平道，在用炎性細(xì)胞因子處理后睹欲，MSCs的主要模塊仍顯示出與未刺激狀態(tài)下相似的模式。
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為了確定最初的UC-MSCs的特征基因是否也能顯示出炎性細(xì)胞因子引發(fā)的MSCs中的亞群一屋，我們采用了PCA分析窘疮。 我們發(fā)現(xiàn)先前發(fā)現(xiàn)的7個特征基因的表達(dá)水平在3個組中的第1組中最高(Fig. 2e)。有趣的是冀墨，與第2組和第3組相比闸衫，與第2組和第3組相比，第1組由MSCs介導(dǎo)的免疫調(diào)節(jié)關(guān)鍵細(xì)胞因子和趨化因子包括CCL5诽嘉，IDO1蔚出，CXCL9弟翘，CCL2，PTGS2 / COX2骄酗，TNFAIP6 / TSG6和IL6）的表達(dá)最低(Fig. 2f)稀余，而其他基因在所有3組中表現(xiàn)出相似的表達(dá)模式∏鞣可以在所有數(shù)據(jù)集中找到特征基因和免疫調(diào)節(jié)基因的這些反負(fù)相關(guān)(Figs. S8 and S9)睛琳。 這些結(jié)果表明，我們在UC-MSCs中發(fā)現(xiàn)的亞群七種特征基因表達(dá)水平高踏烙，同時具有較低的免疫調(diào)節(jié)基因表達(dá)水平掸掏。

The limited heterogeneity in expanded MSCs is linked to cell cycle stages

擴(kuò)增的MSC中有限的異質(zhì)性與細(xì)胞周期階段有關(guān)

鑒于特征基因是細(xì)胞個體間基因表達(dá)變異性的代表，我們探討這些特征基因是否可以用于MSCs亞群的鑒定標(biāo)記宙帝。我們評估了七個特征基因在體外擴(kuò)增的UC-MSCs群中的表達(dá)情況。觀察到只有很小的一群細(xì)胞表達(dá)高水平的七個特征基因(Fig. S10)募闲。七個特征基因中的CD168基因具有相對高的表達(dá)水平步脓。隨后，我們通過流式細(xì)胞儀分選分離出CD168陽性和陰性的MSCs(Fig. 3c)浩螺，分選的CD168高表達(dá)的MSCs與未分選的MSCs一起靴患，分別比較了它們的形態(tài)，細(xì)胞表面標(biāo)志物和增殖潛能(Fig. 3c)要出。在顯微鏡下鸳君，這些細(xì)胞表現(xiàn)出類似的紡錘形形態(tài)(Fig. 3c)。MTS實(shí)驗(yàn)顯示患蹂，CD168陽性或颊，陰性的MSCs和未分選的MSC的生長速率相似，與接種的細(xì)胞數(shù)量無關(guān) (Fig. 3d)传于。此外囱挑，我們還評估了MSCs鑒定的一組標(biāo)記基因，包括CD73沼溜，CD90平挑，CD105，CD34系草，CD11b通熄，CD19，CD45和HLA-DR找都。對于CD73唇辨，CD90，CD105的陽性和CD34檐嚣，CD11b助泽，CD19啰扛，CD45和HLA-DR的陰性沒有顯著差異(Fig. 3e)。有趣的是嗡贺，當(dāng)我們分析CD168在擴(kuò)增的CD168 陽性MSC隐解，CD168陰性MSC和未分選的MSC中的表達(dá)時，發(fā)現(xiàn)這些組中的CD168表達(dá)水平是可比較的（分別為0.99％诫睬，1.07％和1.80％）煞茫。(Fig. 3b)）。這些結(jié)果表明CD168陰性MSC可以恢復(fù)基因表達(dá)模式摄凡，因?yàn)镃D168 陽性伴隨擴(kuò)增時發(fā)生续徽，表明MSC之間的異質(zhì)性具有局限性。
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為了研究MSCs中有限異質(zhì)性的特征和形成亲澡，我們分析了每個數(shù)據(jù)集中各個模塊之間的關(guān)系钦扭，如圖Fig. 3f所示。值得注意的是床绪，在藍(lán)色和綠松石基因模塊中客情，有或沒有炎癥刺激的UC-MSCs中基因表達(dá)存在顯著差異（分別在huc1_ctrl和huc1_sti中為-0.69和-0.88）(Fig. 3f)）。GO富集分析進(jìn)一步表明癞己，與細(xì)胞遷移和細(xì)胞因子信號傳導(dǎo)相關(guān)的通路在藍(lán)色模塊中富集膀斋，在綠松石模塊與細(xì)胞周期活性相關(guān)的通路高度富集(Fig. 3g)。

我們基GO富集“細(xì)胞周期”和“免疫調(diào)節(jié)”中的注釋得到了57個細(xì)胞周期相關(guān)基因和20個免疫調(diào)節(jié)相關(guān)基因的列表痹雅，并進(jìn)行單細(xì)胞qPCR以確定它們在擴(kuò)增的UC-MSCs中的表達(dá)情況仰担。我們發(fā)現(xiàn)兩個大的模塊之間的細(xì)胞周期相關(guān)基因和免疫調(diào)節(jié)相關(guān)基因之間存在高度負(fù)相關(guān)(Fig. 3h)
。在UC-MSC的單細(xì)胞RNA測序中也可以觀察到這種負(fù)相關(guān)性 (Fig. 2b, c and Figs. S8 and 9)绩社。因此摔蓝，我們的結(jié)果表明，UC-MSC中有限的異質(zhì)性與細(xì)胞周期進(jìn)展有關(guān)铃将。

Cell cycle stage determines the heterogeneity of MSCs

細(xì)胞周期階段決定了MSC的異質(zhì)性

我們接下來檢查了細(xì)胞周期軌跡對UC-MSCs中異質(zhì)性的影響项鬼。我們采用基于評分細(xì)胞周期相關(guān)基因的分類方法，并描述每個細(xì)胞在G1/S和G2/M期中表達(dá)細(xì)胞的特征基因劲阎。
通過顯示紅色的CD168/HMMR陽性細(xì)胞绘盟，我們發(fā)現(xiàn)大多數(shù)細(xì)胞位于右上方，表明它們處于G2/M期 (Fig. 4a)
悯仙。為了進(jìn)一步證實(shí)與細(xì)胞周期相關(guān)的其他特征基因（brca1龄毡，cdca5，melk锡垄，racgap1沦零，prc1和hmgb1）的相關(guān)性，我們檢查了它們的表達(dá)模式货岭，發(fā)現(xiàn)它們的表達(dá)與CD168/HMMR 陽性的MSCs類似路操，富集在圖的右上角(Fig. 4b)
疾渴。為了檢查細(xì)胞周期階段是否與這些特征基因在UC-MSCs中的高表達(dá)相關(guān)，我們使用了四種小分子抑制劑來阻止G1/S期（Abemaciclib和GGTI298）和G2/M期（Nocodazole）的MSCs屯仗。和伊沙匹赂惆印）(Fig. 4c and Fig. S11)。用碘化丙啶（PI）染色顯示MSCs中的DNA含量并確定細(xì)胞周期的階段魁袜，我們分析了二倍體和四倍體細(xì)胞中CD168 +細(xì)胞的百分比桩撮。我們發(fā)現(xiàn)在G2/M期停滯的大多數(shù)MSC在CD168中呈陽性(Fig. 4c, d and Fig. S11)
。然而峰弹，在G1/S期停滯的UC-MSC表現(xiàn)出相反的模式(Fig. 4c, d and Fig. S11)店量。
[圖片上傳失敗...(image-e44f5e-1559183711238)]
由于體外培養(yǎng)很大程度上降低了UC-MSCs中CD168/HMMR的表達(dá)，我們直接分析了分離出的CD168/HMMR陽性的MSCs與細(xì)胞周期相關(guān)基因的表達(dá)鞠呈。 如所預(yù)測的融师，新分離的CD168/HMMR陽性MSC表達(dá)較低水平的G1/S基因，mcm2蚁吝，而表達(dá)高水平的G2/M基因诬滩，aurkb和cdk1 (Fig. 4e)
。 表明細(xì)胞周期的G2/M期與這些指示的特征基因的關(guān)系灭将，包括brca1，cdca5后控，hmmr庙曙，melk，prc1和racgap1浩淘。 我們將UC-MSCs分為G0/G1期和G2/M期捌朴，并使用實(shí)時PCR分析前述提到的基因的表達(dá)情況。 我們發(fā)現(xiàn)這些特征基因在G2/M細(xì)胞中的表達(dá)高于G0/G1細(xì)胞中的表達(dá)(Fig. 4f)张抄。 總之砂蔽，細(xì)胞周期階段控制UC-MSCs的異質(zhì)性。

Discussion

自第一例MSCs用于治療患有類固醇和環(huán)孢菌素耐藥GvHD的9男孩以來署惯，各種隨訪研究都集中在MSCs在組織修復(fù)和再生方面的潛力研究[16,25]左驾。MSCs治療成功依賴于MSCs的質(zhì)量，注射途徑极谊，患者狀態(tài)和臨床干預(yù)這個關(guān)鍵參數(shù)诡右。MSCs的行業(yè)標(biāo)準(zhǔn)對于控制MSCs的質(zhì)量至關(guān)重要。本研究轻猖，我們對來自兩個不同供體和三個傳代的UC-MSC進(jìn)行單細(xì)胞RNA測序帆吻，我們對來自兩個不同供體的三個代際的UC-MSCs進(jìn)行單細(xì)胞RNA測序,并設(shè)置有無炎性細(xì)胞因子刺激兩組。
我們發(fā)現(xiàn)咙边，無論供體和代級如何猜煮，UC-MSCs中基因表達(dá)的異質(zhì)性是有限的次员。此外，經(jīng)炎性細(xì)胞因子（IFNγ和TNFα）刺激的UC-MSCs在基因表達(dá)中顯示相似的多樣性模式王带，表明有無炎性細(xì)胞因子刺激UC-MSCs均具有有限異質(zhì)性淑蔚。我們發(fā)現(xiàn)了包括brca1，cdca5辫秧，melk束倍，hmmr，racgap1盟戏，prc1和hmgb1在內(nèi)的七個特征基因绪妹。更深一步地分析顯示，異質(zhì)性在很大程度上與UC-MSCs的細(xì)胞周期階段有關(guān)柿究。

自從骨髓中首次鑒定獲得MSCs后邮旷，如今幾乎可以從所有的組織中獲得MSCs。骨髓來源的BM-MSCs在臨床應(yīng)用中最為常見蝇摸，與來自它組織中的MSCs相比婶肩，UC-MSCs具有大規(guī)模擴(kuò)增和標(biāo)準(zhǔn)化的巨大潛力。UC-MSCs單細(xì)胞基因譜分析顯示個體細(xì)胞存在異質(zhì)性貌夕，不同細(xì)胞分別表現(xiàn)出明顯的增殖和分化潛能律歼。基于UC-MSCs大小的分類顯示啡专，形態(tài)較小的細(xì)胞生長更快险毁，更為年輕。此外们童，利用多色慢病毒條形碼標(biāo)記作為UC-MSC克隆發(fā)育的分析工具畔况，發(fā)現(xiàn)在體外擴(kuò)增期間可以減少M(fèi)SCs的異質(zhì)性。
因此慧库，體外擴(kuò)增的MSCs間的異質(zhì)性的鑒別和應(yīng)用反應(yīng)了它們在疾病治療中應(yīng)用的治療機(jī)會跷跪。考慮到不同供體來源和擴(kuò)增過程中可供選擇的MSCs的克隆齐板。

可以代表它們在疾病治療中應(yīng)用的新的治療機(jī)會吵瞻。考慮到不同供體??來源和擴(kuò)增過程中MSCs克隆選擇的可能性甘磨，我們對來自不同供體和傳代的UC-MSC的單細(xì)胞RNA測序分析描述了數(shù)據(jù)集之間的可變性非常保守听皿，表明UC-的異質(zhì)性有限。間充質(zhì)干宽档。以前的研究已經(jīng)指出尉姨，培養(yǎng)條件也可以影響MSCs32的轉(zhuǎn)錄和蛋白質(zhì)組譜。在存在炎癥的情況下吗冤，來自不同供體的MSC可以提供解決DTH炎癥的一致結(jié)果又厉，這歸因于由炎性刺激引發(fā)的不同供體MSC中免疫抑制分子的可比較和豐富的表達(dá)九府。這些結(jié)果提出了將異質(zhì)MSC發(fā)展成同質(zhì)群體的潛在方法。雖然炎癥可以使MSC具有最重要的免疫抑制作用覆致，并使得不同的供體來源的MSC具有類似的組織再生改善侄旬，但這些炎性細(xì)胞因子刺激的UC-MSC不是同質(zhì)的。令人驚訝的是煌妈，它們的基因譜可變性的表達(dá)模式與未處理的UC-MSC相似儡羔。

為了揭示UC-MSCs有限異質(zhì)性的本質(zhì)，我們分析了特征基因璧诵，發(fā)現(xiàn)綠松石模塊與細(xì)胞周期調(diào)控有非常密切的關(guān)系汰蜘。令人意想不到的是觀察到了細(xì)胞周期基因聚類的模塊和免疫相關(guān)分子聚類的模塊之間負(fù)相關(guān)性。我們發(fā)現(xiàn)UC-MSCs亞群大多處于G2/M期之宿，UC-MSCs的異質(zhì)性（有無炎性細(xì)胞因子刺激）均受細(xì)胞周期進(jìn)程的控制族操。

總之，我們通過對UC-MSC單細(xì)胞RNA測序的分析揭示了UC-MSC的異質(zhì)性主要是由細(xì)胞周期階段的不同分布引起的比被。除了在研究MSC生物學(xué)方面有價值之外色难，該信息還對MSC標(biāo)準(zhǔn)化和采用MSC治療各種疾病的發(fā)展具有重要意義。

Methods and materials

Single cell capture and quality control

MSCs were captured on a large microfluidic chip (designed for cells from 17 to 25?μm) using the Fluidigm C1 Autoprep System. Capturing efficiency was evaluated by microscopic observation; each capture site was manually confirmed with single cell and processed further. RNA degradation and contamination was monitored on 1% agarose gels. RNA purity was checked using the NanoPhotometer spectrophotometer (IMPLEN, CA, USA). RNA concentration was measured using the Qubit RNA Assay Kit in Qubit 2.0 Flurometer (Life Technologies, CA, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Quality control was performed by Novogene Co., Limited.

Library preparation and sequencing

Sequencing libraries were generated using the NEBNext Ultra RNA Library Prep Kit for Illumina (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using the TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq 2500 platform and 50?bp single-end reads were generated. These procedures were achieved by Novogene Co., Limited.

Data analysis

Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, poly-N and low quality reads from raw data. At the same time, the clean data of Q20, Q30 and GC content were calculated. All the downstream analyses were based on the clean data with high quality.

Reference genome (hg19) and gene annotation file (UCSC RefGene) were downloaded from illumina iGenomes. Index of the reference genome was built using Bowtie2 (v2.2.5) and single-end clean reads were aligned to the reference genome using Top Hat (v2.1.0).

Quantification of gene expression level

HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. To normalize sequencing depth, the size factors was calculated by estimate SizeFactorsForMatrix function in R package DESeq2. Normalized counts were calculated by divided raw counts of each genes by size factor of each samples.

Subgroup identification and differential expression analysis

We applied R package SCDE to identify subpopulations of MSCs. Briefly, spike-in RNAs were used to calculate a regression line of gene expression levels and variations, single-cells were grouped into subpopulations by hierarchical clustering with genes that significantly deviation from the fit. Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the SCDE R package. The SCDE package implements routines for fitting individual error models for single-cell RNA-seq measurements by using a mixture of a negative binomial distribution and low-level Poisson distribution to model each gene. Genes with P-value?<?0.05 found by SCDE were assigned as differentially expressed.

GO analysis of differentially expressed genes

GO enrichment analysis of differentially expressed genes was implemented by the topGO R package. GO terms with corrected P value?<?0.05 were considered significantly enriched by differential expressed genes.

Weighted gene correlation network analysis (WGCNA)

A signed network was constructed by using genes that significantly deviated from SCDE fit in each dataset. Soft power 12, which is the default parameter, was used to derive a pair wise distance matrix for selected genes using the topological overlap measure, and the dynamic hybrid cut method was used to detect clusters. The node centrality, defined as the sum of within-cluster connectivity measures, was used to rank genes for “hub-ness” within each cluster. For visual analysis of the constructed networks by hard thresholding of edge distances, the closest 150 edges were represented using Cytoscape 3.0.0.

Based on the gene modules identified by WGCNA analysis, we screened the genes in blue and turquoise modules with three criteria: (1) highly expressed in one specific subcluster compared to the other clusters; (2) the subcluster specific expression existed in more than one dataset; (3) expressed on the cell surface. Finally, we identified seven featured genes: brca1, cdca5, hmgb1, hmmr/cd168, melk, prc1, and racgap1.

表達(dá)矩陣下載：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117837

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