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55岁的李先生近来老感觉腿痒,就自己到药店买了些药膏每天涂抹,可一个月过去了,情况非但没有好转,反而严重了。家人带她去医院皮肤科做了检查,医生详细问诊后建议她去血管外科就诊,经血管外科会诊确诊为静脉曲张。
[摘要] 目的:分析造口底盘在造口旁切口治疗中的应用效果。 方法:纳入 2018 年 11 月至 2019 年 11 月我院外 科造口门诊 60 例造口与切口距离<底盘覆盖范围(10 cm×10 cm)的病人,随机分为研究组和对照组各 30 例。 研究组 使用造口底盘,对照组采用片状水胶体敷料治疗保护。 评价两组病人治疗效果、舒适度、换药时间和成本效益的差 异。 结果:研究组和对照组回肠造口分别为 23 例、21 例,结肠造口分别为 7 例、9 例。 研究组和对照组造口周围皮肤 变色、侵蚀和组织增生的评分分别为(5.67±1.21)和(5.80±1.24),切口面积分别为(18.76±16.14) cm2 和(20.91±15.39) cm2 。 两组病人 7 d 后治疗效果和舒适度比较,差异无统计学意义。 但研究组的治疗成本低于对照组[(244.67±58.47)元比 (341.43±106.13)元,P<0.001],换药时间亦少于对照组[(10.90±1.58) min 比(14.77±3.42) min,P<0.001),差 异 均 有 显著统计学意义。 结论:造口底盘可替代水胶体对造口旁切口进行治疗和保护,为造口旁切口治疗的方法之一。
关键词:造口底盘; 切口愈合; 应用效果
摘要:综述了纤维素水凝胶用于电子皮肤器件近期取得的研究进展。指出水凝胶可穿戴电子未来 的发展和应用方向:一是在智能医疗领域实现健康管理和动态治疗;二是实现人类感知支配的物 联网。先从拉伸性、抗冻性和自愈合三方面分析了电子皮肤用纤维素水凝胶所需的基本特性。然 后举例阐述了纤维素水凝胶在药物负载和释放两方面的独特优势,揭示了其在智能医疗领域的价 值,同时总结了水凝胶可穿戴电子的信号传感功能所蕴含的巨大应用潜力。最后探讨了目前纤维 素水凝胶研究面临的挑战,并对纤维素水凝胶及对应的电子皮肤器件的发展趋势进行了展望。
关键词:纤维素水凝胶;抗冻性;柔性传感器;电子皮肤;智能医疗
0 引 言
电子皮肤作为国际前沿课题,是颠覆性促进社 会发展的变革性科技[1]。随着移动通信及相关网络 产品的发展,相信未来可穿戴电子产品会趋于网络 定制化和服务智能化,最终会实现人类感知支配的 物联网等[2]。为了实现智能化服务,电子皮肤器件 需长期贴合体表,实时监测人体信号,并及时作出 响应[3]。寻找并合成与人体软组织具有类似性质和 功能的软材料是摆在科学家面前的首要挑战。毫无 疑问,水凝胶是最佳选择之一[4]。
水凝胶由三维聚合物网络和大量的水组成,以 其类固体的机械性能和类液体的输运性能在电子皮 肤研究中受到各国学者的青睐[5]。但是水凝胶中含 有大量水,低温易冻结,外界环境变化难以控制, 尤其是温度变化将严重损害电子皮肤水凝胶的功 能,甚至误导物联网[6]。为了避免外界环境对电子 皮肤水凝胶的干扰,有必要提高水凝胶的抗冻能 力[7]。另一方面,作为电子皮肤材料,需长期贴合 皮肤,面对电子皮肤越来越高的性能要求,水凝胶 在超拉伸[8]和自愈合[9]等皮肤样特性上需得到进一 步发展。
未来电子的发展将基于非石油路线,更加注 重可再生资源的开发与利用,纤维素由于其天然 的链式结构和生物特性,如无毒、可再生、生物 相容性和生物可降解性,已成为电子皮肤的优秀 候选材料[10],而纤维素水凝胶的研究也随之取得 长足进展。
1 纤维素水凝胶的特性
纤维素由β-(1→4)糖苷键连接两个 D-吡喃型 葡萄糖单元组成,每个葡萄糖单元中含有3个活性 羟基 (—OH)[11],这为通过衍生化和接枝共聚制 备纤维素基功能材料提供了多种途径。电子皮肤材 料需要长期贴合体表,保证设备与人体之间良好的 机械兼容性,避免器件因形变而失效,更要保证人 体的舒适度,减少因电子皮肤带来的刺激与信号误 导[12]。为了更好地应用于电子皮肤,水凝胶材料 除了要克服本身固有的冻结问题,还需要具有良好 的拉伸性和自愈合性等皮肤样特性。
1.1 拉伸性
为了提高水凝胶拉伸性能就需要引入能量耗散 机制,传统方法有设计网络结构、构建复合材料和 引入微凝胶增强效应 (可视为两相复合凝胶)[13]。 但是在不引入其他合成高分子的情况下,要提升纤 维素水凝胶的拉伸性能主要需从交联策略着手,设 计出能量耗散能力强的超拉伸网络结构[14]。目前 对于水凝胶的交联策略主要有三种:物理交联、化 学交联和双交联。
常用的物理相互作用除了氢键外,还有疏水相 互作用、离子相互作用和主-客体相互作用等[11]。 纤维素链上丰富的羟基与纤维素的三维立体构象促 使纤维 素 水 凝 胶 自 带 氢 键 交 联 和 链 间 交 错 缠 结。 2019年,D.Liu等人[15] 诱导大肠杆菌产生大量的细 菌纤维素,通过氢键直接交联制备水凝胶。改性后 的细菌纤维素水凝胶网络致密但仍清晰,最大拉伸 率可达28.67%。另一方面,纤维素具有大量的氢键 结构,这在很大程度上限制了室温下它在水和有机 介质中的溶解度。随着 NaOH/尿素水体系、N-甲基 吗啉-N-氧化物水合物、离子液体等溶剂体系的开 发,通过重建再生纤维素分子间和分子内的氢键, 可 以 制 备 再 生 纤 维 素 水 凝 胶[16]。2019 年, X.F.Zhang等人[17]用高浓度的 ZnCl2 离子溶液溶解 棉纤维素,并将离子化合物 (ZnCl2/CaCl2)整合到 纤维素水凝胶网络中,得到Zn2+/Ca2+/纤维素配位 键组成的物理交联水凝胶,如图1所示。这种新型 纤维素基水凝胶拉伸率达到120.0%。
纤维素在ZnCl2/CaCl2 无机盐体系中溶解和结合[17] Fig.1 DissolutionandbindingofcelluloseinZnCl2/CaCl2 inorganicsaltsystem[17] 为了保证纤维素的稳定结构和有效溶胀,凝胶 过程中,一般会加入化学交联剂促进三维网络的共 价结合[11]。目前报道最多的化学交联剂有环氧化 物、烷基卤化物和含环氧卤化基团的化合物等。卤 代烷与纤维素反应需要较强的碱性环境,因此实际 操作中常用含环氧卤化基团的化合物 (如环氧氯丙 烷)进行化学交联[18]。2019年,X.Cui等人[19]以 豆渣中提取的纤维素为原料,通过向其中加入环氧 氯丙烷 (ECH)与无水葡萄糖单元 (AGU),制备 了具有良好机械性能的纤维素水凝胶。通过改变水 凝胶的含水量,可调节机械性能,其最大拉伸率可 达107%。化学交联水凝胶也可以在交联剂的存在 下,通过单体自由基聚合得到,自由基聚合具有高 反应活性和对水环境的要求相对温和等优势。2019 年,R.P.Tong等人[20]通过醚化改性在 NaOH/尿 素水溶液中制备烯丙基纤维素,再由热引发自由基 聚合得到纤维素水凝胶 (CIH),其具有高可拉伸 性 (拉伸率126%)。通过合理调整化学交联密度, 还可以控制水凝胶的各项性能。此外,该 CIH 可 以作为可靠和稳定的应变传感器,并已成功用于监 测人类活动。
双交联水凝胶具有突出的性能优势,2016年, D.Zhao等人[21]利用环氧氯丙烷加氢键交联方法制 备了双交 联 (DC)纤 维 素 水 凝 胶,如 图 2 所 示。 研究了 DC纤维素水凝胶中化学交联域和物理交联 域的形成和空间分布,发现环氧氯丙烷与葡萄糖单 元的物质的量的比和乙醇水溶液的浓度是调控 DC 纤维素水凝胶力学性能的两个关键参数。2019年, D.D.Ye等人[22]设计了一种绿色路线来制备超坚 韧的再生纤维素薄膜,在碱/尿素水溶液体系中溶 解纤维素,向其中直接引入氢键,风干后进行结构 致密化处理,水凝胶的强度得到了提高,但拉伸率 仅达到12.4%。为了得到超拉伸率的纯纤维素水 凝胶,再引入化学交联 (环氧氯丙烷)加氢键的组 合形式,使棉纤维素的拉伸率由仅有氢键交联时的 12.4%提升到了44.1%。通过长短链和内外层结构 设计,制备出双网络结构的水凝胶,外层短链增加 损耗模量的同时,内层长链交错缠绕,大幅度提高 了水 凝 胶 的 最 大 拉 伸 率[23]。2019 年,D.D.Ye等 人[24]通过纤维素与低分子量和高分子量交联剂的序 贯反应,构建了化学双交联纤维素水凝胶 (DCH), 得到了相对短链和长链的交联网络。他们提出了 DCH 的加固机理,短链交联的断裂有效地分散了机 械能量,而 长 链 交 联 维 持 了 DCH 的 弹 性,因 此, DCH 的最大拉伸率达到94.5%,此短链和长链交联 的双网络对纤维素水凝胶力学性能的提高起到了重 要作用。2019年,R.P.Tong 等人[25]在自由基聚合 得到纤维素水凝胶的基础上,将水凝胶浸入饱和 NaCl溶液中进行物理交联,制备物化双交联纤维素 水凝胶,其最大拉伸率达到了236%。值得一提的 是,该水凝胶应变传感器在测量手臂和手腕的弯曲 等常规动作时信号稳定、效果良好,并在-20 ℃时 仍具有良好的拉伸性能,为柔性电子器件在大范围 温度下的应用提供了参考。截至目前,已有很多关 于物理或化学策略用来构建有效能量耗散机制的纤 维素基水凝胶的研究。已报道的水凝胶的各种交联 策略及其拉伸率的对应关系如表1所示。
在交联方法已经确定的情况下,还可以通过设 计几何结构来满足在实际应用时的超拉伸要求。常 见的 可 拉 伸 结 构 有:岛 桥[29]、波 浪/皱 纹[30]、纺 织[31]和剪纸[32]。对于水凝胶,常采用波浪结构来 提升其在应用时的拉伸率。以纤维素水凝胶为例, 在制备器件之前,先把水凝胶进行预拉伸,然后将 已被拉伸的水凝胶与其他器件进行组合,随后水凝 胶收缩为波浪结构。在施加应变的情况下,水凝胶 可以产生及时充分的形变且不被破坏,从而使整个 衬底具备更强的拉伸能力。
1.2 抗冻性
最近,未来电子过冷服役受到关注。水凝胶的 网络结构中有大量的亲水基团,并且有较高的含水 量,而当温度低于水的冰点 (0 ℃)时,水凝胶不 可避免地会冻结、变得脆弱、失去了原来的弹性。 因此,迫切需要研发能够在较低温度下使用的抗冻 水凝胶。
电子皮肤涉及元件形态多样性造成冰冻危害形 式多样性,且传统抗冻抑冰策略不适于电子皮肤: 机械除冰 (破坏元件)、低模量材料变形抑冰 (损 害原件可靠性)、构建超润滑层、降低黏附力 (改 变元件表面结构、损害其传感和输运汗液等功能)、 加热抑冰 (扰乱集成热敏元件功能,不能根据元件 需求 “智能”给热)[33-34]。对于水凝胶元件,目前 最行之有效的方法是将盐和醇等防冻剂加入其中, 并 不 影 响 其 正 常 功 能。2019 年,R.P.Tong 等 人[25]报 道 了 超 缓 凝 抗 冻 纤 维 素 离 子 水 凝 胶 (DCIH)。饱和氯化钠溶液浸泡策略赋予 DCIH 优 良的防冻性能,除了在-24 ℃的低温下保持良好 的拉伸性 (拉伸率为100%),还能在大范围的低 温 (-30~-16 ℃)下转变成高视觉透明状态。此 外,通过对输出电信号的研究,证明 DCIH 具有 可靠性高、响应速度快以及宽量程应变传感器的特 性,显示出在广泛温度范围下的柔性电子领域的应 用潜力。纤维素在溶解时常常会引入盐溶液,使其 具有一定的抗冻性,而醇类可以进一步提高纤维素 水凝胶的抗冻性。2019年,X.F.Zhang等人[17]用 高浓度ZnCl2 离子溶液溶解棉纤维素得到的纤维素 水凝胶,在低至-70 ℃时仍保持其柔韧性和导电 性。值得注意的是,在水凝胶中分别加入水和甘 油,其 中 加 入 甘 油 的 水 凝 胶 冰 点 甚 至 达 到 了 -108 ℃。一般来说,甘油是一种非离子的共体, 它能与水分子形成强氢键,同水分子之间的氢键相 互竞争。这种相互作用破坏了水凝胶网络中冰晶的 形成。低温下良好的力学性能和导电性能是纤维素 水凝 胶 面 向 应 用 要 解 决 的 首 要 难 题,2019 年, Y.Wang等人[35]将纤维素溶解于苄基三甲基氢氧 化铵 (BzMe3NOH)水溶液中,通过化学交联直 接制备出具有防冻性能的离子导电纤维素水凝胶 (CCH)。为了对照,通过洗涤导电纤维素水凝胶 制备了纯水纤维素水凝胶 (CH)。如图3[35]所示, CCH 基质中的浓缩 BzMe3NOH 溶液使水凝胶具有透明性和抗冻性。CCH 在-27.8~62.1 ℃内保 持了90%以上的透明度和稳定的力学性能。即使 在-40.0 ℃下其依然保持了弹性和透明度,可以 随意弯折不断裂。基于 CCH 的传感器对应变和温 度具有良好的灵敏度,在包括零下温度在内的较宽 温度范围内,响应速度快,没有明显的滞后现象。
1.3 自愈合性
电子皮肤的成本一直制约着其实际应用。电子 皮肤需时刻贴敷在身体上,对于其水凝胶元件,一 方面要求其发生弹性形变后能恢复到原来的形态, 另一方面面对随时可能的刮伤、划破甚至断裂,需 要其 具 有 良 好 的 的 自 愈 合 性 能[36]。可 逆 共 价 键 (亚胺键和酰腙键)、可逆非共价键 (金属离子配位 键和氢键),以及三维网状结构独特的微裂纹愈合 能力,共同增强了水凝胶的自愈性能[37]。
2020年,J.T.Tang 等 人[38]利 用 纤 维 素 纳 米 晶 (CNC)和海藻酸钠 (SA)作为连接剂,保证 水凝胶结构完整性和机械稳定性的同时在其表面引 入动态席夫碱键合,加上自身氢键的共同作用,水 凝胶在切开后3h即可完全融合。同年,Q.C.Fan 等人[39]从葡萄渣中提取了 CNC,制得水凝胶。向 其中引入 Fe3+ 和 硼 砂,通 过 可 逆 非 共 价 键 作 用, 水凝 胶 获 得 了 良 好 的 自 愈 合 性 能,自 愈 效 率 为 90.0% (自愈效率=切开后自愈合的水凝胶的拉应 力/原始水凝胶的拉应力×100%[40])。连续10次 自愈后,其自愈效率仍可达到75.1%,且储能模 量和损耗模量无明显下降。2020 年,W.Y.Li等 人[41]以双醛细菌纤维素 (DABC)与壳聚糖相结 合,制备了具有良好自愈性 (切开后3h内愈合) 和可注射性的新型抗菌水凝胶。克服了醋酸在医药 领域应用的弊端,摒弃了其他有毒交联剂,为制备 具有注射和抗菌性能的自愈合水凝胶提供了新的 策略。
修复性能与高强度之间往往是矛盾的,材料强 度越大,其流动性能越差,从而愈合性能越差。但 良好的力学强度是水凝胶使用的基础,因此在保证 自愈合性能的同时提升水凝胶的强度具有重要意 义。综合运用金属离子-配体作用和 Diels-Alder 反应成键作用,构建双网络水凝胶,可使其强度大 大提高。此外,将金属离子-配体作用的可逆非共 价键和亚胺键/席夫碱的动态共价键作用相结合, 可赋予水凝胶除了自愈合性能之外良好的延展性。 2015 年, W.J.Zheng 等 人[42] 将 羧 甲 基 纤 维 素 (CMC) 膏 体 在 柠 檬 酸 溶 液 中 酸 化, 得 到 自 愈 CMC水凝胶。该水凝胶在环境温度下可以不受任 何外界刺激自行愈合,自愈效率达到80%。2017 年, 同 一 课 题 组 的 Y.M.Chen 等 人[43] 利 用 N,N’-羰基二 咪 唑 将 其 自 愈 效 率 提 高 到 95%, 愈合后的水凝胶可拉伸至原长度的2.5倍左右,此 外还赋予了水凝胶光致发光性能,在生物医学和工 程领域具有广阔的应用前景。
2 纤维素水凝胶在电子皮肤方面的应用
水凝胶由于其良好的柔韧性、导电性、出色的 输运 能 力、 自 愈 能 力, 在 传 感 器[44]、 软 式 机 器 人[45]和药物传递[46]等方面已有广泛应用。未来先 进的可穿戴电子将替代传统医疗、遥控设备,与通 信技术和网络软件共同构成一套兼具智能医疗和感 知支配物联网的控制系统。纤维素水凝胶的生物相 容性和生物可降解性促使其在电子皮肤的发展中扮 演着不可或缺的角色。
2.1 智能药物载体
以电子皮肤为载体的智能医疗将会提供特有的 药物输送方式:透皮给药,即药物以一定的速率渗 入皮肤,进入循环系统,产生治疗效果。长期贴合 皮肤使用的智能药物载体,除了需要超出正常皮肤 的透气性要求外,还需要具有药物负载、刺激响应 和控制释放的智能医疗体系,充分发挥可穿戴电子 设备早发现、早治疗和方便快捷等优势[47]。 良好的透气性可以有效规避长期穿戴引起的闷 热和发炎等,相比于纤维素气凝胶或木膜材料的多 孔结构,水凝胶的透湿透氧能力明显更差,更需要 对其透气 性 进 行 专 门 的 研 究。2016 年,D.Prabu 等人[48]利用羟丙基甲基纤维素 (HPMC)与海藻 酸钠聚合制得水凝胶膜,水蒸气透过率 (WVTR) 为5.84g/m2/h, 与 健 康 人 体 的 表 皮 水 分 损 失 (TEWL,为 5~10g/m2/h) 值 接 近。2019 年, S.Jiji等人[49]开发了负载百里酚的细菌纤维素水凝 胶 (BCT), 利 用 细 菌 纤 维 素 的 高 亲 水 性, 将 WVTR值提 升 至 400g/m2/d 以 上 (正 常 人 皮 肤 WVTR>204g/m2/d)。分析表明,水蒸气和氧气 等气体是通过水进行输运的,水凝胶的透氧透湿能力与其中的含水量密切相关[50],而另一方面,随 着含水量的增加,水凝胶的力学性能会受到极大 影响。
对于正常皮肤,在透湿透氧的基础上,要实现 水凝胶药物载体智能化,需要对水凝胶从药物负载 到刺激响应、再到控制释放三方面进行深入研究。 首先,水凝胶含大量水,具有优异的溶剂运载能 力,意味着其具备较好的负载药物能力。2016年, Z.Zare-Akbari等人[51]研发了 CMC/ZnO 纳米粒子 复合抗菌水凝胶,通过改变 ZnO 纳米粒子的浓度 得到最高载药量为14.05%的水凝胶药物载体,此 外,基于 CNC和纤维素纳米纤维 (CNF)的水凝 胶本身具有开放的孔隙结构和高比表面积,可以提 供更强的生物利用率和更好的载药能力。2016年, S.Y.Ooi等人[52]利用 CNC的高比表面积制备了对 pH 值具有显著敏感性的复合水凝胶,药物负载量 大幅度提高,接近70%。为了提高载药能力也可 以通过添加其他高比表面积结构或通过静电相互作 用来实现。2017 年,R.Rakhshaei等人[53]利用氧 化锌纳米颗粒浸渍的介孔二氧化硅与 CMC 水凝胶 结合,制得复合水凝胶,在 pH 值 达 到 7.4 以 上 时,对四环素分子的负载量接近130%。
水凝胶药物载体对刺激的响应是其实现智能化 的基础,基于人体皮肤传达的生理信号 (pH 值和 酶等),水凝胶自身需要产生一定的物理化学变化, 进而控制药物的释放。2016年,N.Lin等人[54]开 发了一种基于阳离子 CNC (CCNC)和阴离子海藻 酸盐的双膜水凝胶的复合药物共同递送系统,外层 水凝胶中的阴离子海藻酸盐可以在前3天内实现头 孢他啶水合物的快速药物释放,而内膜水凝胶中的 CCNC可以从第4~12天提供表皮生长因子的持续 释放。通过特殊的凝胶结构达到双膜水凝胶协同释 放的效果,为解决生物医学领域的耐药性问题提供 智能解决方案。2019年,F.C.Lin等人[55]合成了 磁性β-环糊精(β-CD)/纤维素水凝胶,在外部磁场 (EMF)下具有快速溶胀-消胀特性,可远程控制 药物从被动释放到主动控制释放。接枝的β-CD 使 水凝胶具有高载药量,并且同时掺入了 Fe3O4 纳 米粒子,可以控制水凝胶逐步释放的剂量和速率。 该研究将传统水凝胶从被动的接受刺激扩展到主动 刺激并控制释放,进一步扩展了其应用场景。对于 控制 释 放 系 统,还 可 以 通 过 不 同 的 凝 胶 结 构 来 实现。
2.2 实时信号监测
体表作为人体感知交互界面,集成了温度、应 变、体液和视听嗅等感知功能。人体信号包括物理 信号 (运动信号和心率呼吸体温等)和化学信号 (如血糖和激素等)[56]。要实现感知支配物联网技 术,除了计算机视觉和语音捕捉外,另一种重要途 径就是通过肤载水凝胶传感器的实时信号监测。
以应变传感为例,当前可穿戴电子常面向运动 监测,如步数测量等,而基于水凝胶传感器的电子 皮肤不仅能实时监测运动步数,更能够具体地反映 出运动幅度,例如手腕弯曲和喉结伸缩的幅度,如 图4[57]所示。这样实时且具体的信号解决了传统医 疗测量方式的不便性和偶然性,可以实现更加复杂 的人机交互功能,为未来电子皮肤的智能控制奠定 基础。对于电信号的研究,常常需要从引入的导电 粒子来考虑,不同的导电粒子对其电导率和电信号 可靠性 (灵敏度、响应速度和循环次数等)两方面 有着决定性影响。2019 年,R.P.Tong等人[20]利 用 自 由 基 聚 合 制 得 纤 维 素 水 凝 胶 应 变 传 感 器 (CIH),其中 NaOH 为水凝胶提供了丰富的 Na+ 和 OH- ,水 凝 胶 具 有 良 好 的 离 子 导 电 率 (约 为 0.16mS·cm-1),制得的应变传感器可靠 (90% 应变下 的 线 性 拟 合 系 数 R2 0-90% =0.963) 且 稳 定 (循环使用次数>1100次)。同年,R.P.Tong等 人[25]采用物化双交联对水凝胶制备方法进行改进, 得到更宽量程 (R2 0-220% =0.996)的应变传感器, 然而更高的交联密度阻止了离子的自由移动,导致 其电导率只有 1.8×10-5 S·cm-1。相 比 交 联 策 略,不同离子对其电性能的影响更为明显。2019 年,Y.Wang等 人[35]采 用 苄 基 三 甲 基 氢 氧 化 铵 (BzMe3NOH) 溶 解 纤 维 素 制 得 水 凝 胶 传 感 器 (CCH),由于溶剂离子可在水凝胶网络中自由扩 散或定向移动,此 CCH 的电导率可达 2.37S· m-1。值得一提的是,该 CCH 在-40 ℃下保持了 稳定的电导率,为柔性电子器件在大范围温度下的 应用提供了参考。总体而言,离子水凝胶传感器接 入电 路 中 可 以 看 作 一 个 电 解 池,对 于 常 规 的 含 Na+ 的离子水凝胶,由于阴极上 H+ 的还原速率缓 慢以及水凝胶中化学成分的变化,相应的传感器的灵敏度、可靠性和功能性还有很大的提升空间。为 了实现高性能的水凝胶传感器,关键是引入合适的 阳离子 (具有比 H+ 更高的氧化还原电势)或者特 殊性能的导体,例如 Cu2+ 的高还原率可以使传感 器具有较高的信噪比和灵敏度,同时在电流传输过 程中保持恒定的离子组成和浓度[58],添加 MXene 的复合水凝胶在压缩应变下表现出比在拉伸应变下 高得多的灵敏度,这种不对称应变敏感性水凝胶的 传感能力增加了新的维度,可以方便地检测到水凝 胶表面的运动方向和速度[8],这些都为水凝胶传感 器的导电粒子引入提供了新思路。
不仅如此,对于pH 值和葡萄糖等化学信号的 实时检测,则可结合上文中的智能药物载体达到控 制药物释放的智能医疗。2011年,C.Y.Chang等 人[59]通过季铵盐纤维素 (QC)和CMC与ECH 交 联,合成了一种具有pH 值和盐响应性能的新型两 性水凝胶。该水凝胶在pH 值为1~13内都表现出 良好的pH 值敏感性。2017年,H.C.Liu等人[60] 在室温下简单混合改性纤维素和盐溶液获得纤维素 水凝胶,得到 pH 值和氧化还原双重响应的水凝 胶,该方案操作简便,可用于制备其他多反应性多 糖水凝胶,有益于pH 值响应水凝胶传感器的实际 生产。糖尿病是近年来全球最具挑战性的健康问题 之一,糖尿病的典型特征是体内血糖水平高,在血 糖正常范围内及时检测和控制血糖是糖尿病治疗的 主要手段,因此,葡萄糖感测至关重要。2019年, M.X.Wu等人[61]通过分别组装可光交联的水凝胶 和pH 值响应纳米凝胶,开发了基于智能水凝胶系 统的葡萄糖感测视觉检测方法。在正常血糖状态 下,水凝胶显示较大的溶胀,导致其形成较大的形 状,但水凝胶的颜色或荧光强度较弱。在高血糖状 态下,水凝胶显示较小的溶胀,导致其形成较小的 形状,但具有较强的颜色或荧光强度。基于对水凝 胶大小变化和强度变化的观察,可以通过比色法或 荧光成像直接观察葡萄糖水平。水凝胶系统为视觉 检测葡萄糖提供了一种新颖的手段,扩大了其在糖 尿病临床诊断或葡萄糖相关分析中的应用前景。
3 结 语
目前纤维素水凝胶的性能主要受限于纤维素来 源的选择及溶解、交联策略的调整。未来随着研究 的深入,功能各异和性能优越的纤维素水凝胶将被 越来越多地应用于绿色电子皮肤领域。相比于合成 高分子水凝胶,功能化纤维素基水凝胶仍有很大的 提高空间。首先,纳米纤维素难以单独作为水凝胶 骨架,然而常规纤维素溶解时通常引入Na+ 和 Mg2+ 等金属离子使其具有一定的导电性,限制了其在封 装材料和保温基底材料中的应用,而作为应变传感 器,其导电性能又具有很大的提升空间。为满足电 子皮肤苛刻的功能需求,改性纤维素结合其他功能 化粒子的复合水凝胶将是未来纤维素水凝胶的主要 选择方向。其次,对于纤维素水凝胶的性能研究, 主要需解决交联密度引起的拉伸性与流动性 (自愈 合和透气)的矛盾,以及电子元件高度集成引起的 设备能耗、兼容性和生产成本等方面的问题。最后, 电子皮肤在智能医疗和人物交互领域将会以用户体 验为原则,向着绿色、智能和舒适的方向不断前进, 将进一步促进纤维素水凝胶等绿色材料的发展。
纤维素水凝胶作为新兴的绿色材料的代表,优 异的性能决定了其巨大的发展潜力。随着研究不断 深入,纤维素水凝胶在柔性电极、电子皮肤和药物 载体等方面的技术将趋于成熟,进而促进智能医疗 和人物互联的发展。纤维素水凝胶作为未来电子皮 肤的重要元件,将推动人类走向健康和便捷的智能 生活。
Amanda W. Ernlund PhD1| Lauren T. Moffatt PhD2,3| Collin M. Timm PhD1|Kristina K. Zudock BS1| Craig W. Howser MS1| Kianna M. Blount BS1|Abdulnaser Alkhalil PhD2| Jeffrey W. Shupp MD, FACS2,3| David K. Karig PhD1,4
Abstract
Common treatment for venous leg wounds includes topical wound dressings with compression. At each dressing change, wounds are debrided and washed; however, the effect of the washing procedure on the wound microbiome has not been studied.We hypothesized that wound washing may alter the wound microbiome. To characterize microbiome changes with respect to wound washing, swabs from 11 patients with chronic wounds were sampled before and after washing, and patient microbiomes were characterized using 16S rRNA sequencing and culturing.Microbiomes across patient samples prior to washing were typically polymicrobial but varied in the number and type of bacterial genera present. Proteus and Pseudomonas were the dominant genera in the study. We found that washing does not consistently change microbiome diversity but does cause consistent changes in microbiome composition. Specifically, washing caused a decrease in the relative abundance of the most highly represented genera in each patient cluster. The finding that venous leg ulcer wound washing, a standard of care therapy, can induce changes in the wound microbiome is novel and could be potentially informative for future guided therapy
KEYWORDS
16S sequencing, microbiome, venous stasis ulcers, wound treatment
1 INTRODUCTION
Venous leg ulcers are chronic wounds affecting approximately 1% of Americans, and are more prevalent in the elderly population (aged 65 years and older).1 They are difficult to treat and can cause significant morbidity in patients who are not able to modify the causative factors for the lesions or who are not surgical candidates. VLUs are recurrent in 72% of patients diagnosed and have the worst healing prognosis of all leg ulcers.2 Typically, VLU wounds remain open for more than a year highlighting the need for prolonged management and more effective treatment strategies.3 VLUs are a late response of venous hypertension in the lower extremity. This hypertension can be caused by inadequate muscle pump function, incompetent valves or venous thrombosis. When venous pressure is elevated, it is difficult to achieve arterial perfusion and thus oxygen delivery, which can both cause the ulcer and retard wound healing. Due to the resultant poor arterial circulation in the area of these ulcers, many of the cellular and proteinaceous elements needed for wound healing are not able to access the wound bed.4 Interestingly, even when venous hypertension is mitigated, either surgically or by modifications in comorbidities, VLUs may persist or recur. This suggests that more research is needed to fully understand the pathophysiology of these ulcers.
Recently, the interplay between the microbiome and the wound environment has been shown to play a role in both chronic wound development5,6 and wound healing.7,8 The precise impact of the microbiome on wounds can be tied to microbial diversity of the host skin, where microbial composition varies depending on moisture content of the skin as well as dermal versus epidermal coloniza9-11 Highly represented epidermal skin bacterial phyla include Actinobacteria, Firmicutes, Proteobacteria, and Bacteroidetes, whereas subepidermal compartments typically contain higher proportions of Proteobacteria and Actinobacteria,9-11 Interestingly, unlike the gut and other microbiome systems in which increased diversity of host commensal organisms correlates with improved outcomes in dysbiotic conditions, the role of bacterial diversity in chronic wounds is less straight-forward. Studies examining diabetic ulcers, VLUs, and other chronic wounds show increases or decreases in the diversity of skin bacteria in wounds accompanying positive healing outcomes.12-14 In fact, treatments that disrupt the wound microbiome and cause either increases or decreases in diversity may result in faster7,8 The variability of the wound microbiome suggests that successful treatment is in part dependent on the individual's microbial ecology and treatment regimen.8
Chronic wounds are colonized by a diverse array of bacterial genera, and one mechanism that is hypothesized to contribute to chronicity is the presence of bacterial biofilms.15 In ulcer environments, commensal skin bacteria may contribute to the formation of biofilms leading to persistent infection, particularly when host immune function is impaired.16 One study found that the most abundant genera in diabetic foot ulcers included Staphylococcus and Corynebacterium. 17 Also, anaerobes are found in high abundance due to low oxygen presence in the wound yet are not generally detectable by traditional clinical culturing methods.18 If a biofilm is detectable in VLUs, usually by biopsy, the presence of Staphylococcus aureus and Pseudomonas accounts for a large percentage of the bacteria in the biofilm, and these bacteria are believed to initiate biofilm formation.19 Biofilms in wounds are mostly polymicrobial; however, monomicrobial biofilms are seen as well in a much smaller percentage. Finally, wound depth can determine the presence or absence of particular bacteria.20 Various wound types sampled in different anatomical locations across patients showed a predominance of Staphylococcus residing in superficial wounds, while Pseudomonas persisted in deeper wound layers.6
Treatment of chronic VLUs consists of topical ointments, creams, foams, hydrogels, and other dressing products developed to promote a positive wound healing environment. Chlorhexidine-based antiseptic regimens of the skin have been shown to promote a decrease in bacterial burden and infection in surgical wounds.21 The effects of antiseptics on resident skin epithelial inhabitants have been characterized as short-term with an increase in predominant genera and loss of less abundant genera; effects are highly personalized to skin site following antiseptic treatment.22 Treatment of VLUs follows a regimen of topical antiseptic to the site of the wound followed by application of a secondary dressing that allows for compression. These dressings are changed at intervals of 7–10 days. At dressing change, the wounds are assessed, debrided, and then cleansed or washed with an antimicrobial solution before new dressings are applied. Systemic antimicrobial treatments may be used in certain circumstances but have little efficacy for promoting chronic wound healing due to antibioticresistant bacteria present in large numbers in biofilms.3
Although modulation of the wound microbiome is becoming a promising modality for therapy in wound treatment, a comprehensive understanding of microbiome dynamics before and after therapy in VLUs is currently lacking. Therefore, in this study, we undertook a survey of 11 patient microbiomes by performing 16S amplicon sequencing and in vitro culture using a selection of bacteria-specific media on skin swabs isolated from VLUs before and after wound washing. Bacterial composition of wound samples before and after wash were quantified and compared to determine effects of washing on bacterial communities. Results from this study may have implications for the success of therapeutic strategies in treating this disease.
2 METHODS
2.1 Sample collection
Eleven patients with persistent VLUs established for >1 year were included in this study. All patients received the same primary dressing and compression as well as dressing change interval. Wound cleansing was performed with chlorhexidine gluconate and hypochlorous acid solutions for all patients. Information regarding wound debridement was not collected as part of this study and may or may not have been performed as part of standard of care treatment for this patient cohort. Swabs of the wound were collected immediately before and immediately after washing. Swabs were obtained using the Levine technique23 by rotating the swab 360 degrees in a 1 cm square area for 5 s using gentle pressure to release tissue exudate, and samples were placed in cryovials containing 1.5 ml of tryptic soy broth or placed in a cryovial and covered in AllProtect Tissue Preservation Reagent (Qiagen). Tips were broken off into the tubes. The swab tips in broth were processed within approximately 30 min of collection in the laboratory for plating and assessment of bacterial growth on selective media. The swabs in AllProtect Reagent to be used for molecular work were stored at 80C. Wounds were washed and then swabs were collected immediately following wash using the same procedure as pre-wash.
2.2 Wound characterization and treatment
All wounds were located overlying the medial malleolus. Wounds were treated with a primary dressing that contained ACTICOAT (Smith Nephew) followed by Drawtex (Urgo). A secondary dressing for compression was the 3M™ Coban™ 2 Layer Compression System.This dressing regimen remained in place for a week.
2.3 Bacterial growth on selective growth plates
Swabs from before-wash and after-wash were thoroughly vortexed in media. The tip of the swab was then removed from the media. Media was serially diluted, and plated on tryptic soy agar, MacConkey agar, Streptococcus selective agar, and mannitol salt agar growth selective plates and allowed to grow 24 h at 37C. Samples were plated induplicate. Bacterial growth was quantified as present or absent for growth following 24 h.
2.4 DNA extraction and 16S rRNA sequencing
Genomic DNA was extracted from 22 swab samples using the DNeasy PowerWater Kit (Qiagen) and normalized on an Eppendorf epMotion 5075 Liquid Handling Workstation to 0.2 ng/ml. Primers were designed to target the 16S V3 and V4 regions (forward primer: 50 -TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNG GCWGCAG-30 , reverse primer: 5'-GTCTCGTGGGCTCGGAGATGTG TATAAGAGACAGGACTACHVGGGTATCTAATCC-30 ). The targeted regions were amplified via PCR, purified, attached to Illumina sequencing adapters using the Nextera XT Index Kit Set A, and purified again before library pooling. After quality control, final libraries were sequenced on the Illumina MiSeq using v3 reagents with a 600 bp kit (paired 300-bp reads) in a single 65-h run.
2.5 16S amplicon data processing and bacterial
identification Reads underwent quality filtering using Trimmomatic (version 0.35), where adapter sequences were eliminated, and reads were cut at points of low quality using a sliding window of 4 and a minimum PHRED score of 20. After read quality control, paired-end reads were joined using QIIME's join_paired_ends.py script with default settings. Unjoined reads were discarded and assembled reads were assigned to samples from barcodes using QIIME's split_libraries.py.24 OTUs were identified by open reference OTU picking using the GreenGenes25 13_5 97% database and QIIME's pick_open_reference_otus.py script. For downstream analysis, OTUs present >1% in at least one sample were included.
2.6 Diversity analysis
All diversity analyses utilized the percent abundance table where OTUs present >1% in at least one sample were included. The percent abundance table was analysed using the Bray–Curtis dissimilarity metric as a measure of β-diversity between before- and after-wash samples within a patient, before-wash samples across patients, and after-wash samples across patients. Cluster analysis of before-wash samples was performed using hierarchical clustering of the Bray–
Curtis dissimilarity metric. The optimal cluster number of 4 was determined by calculating the consistency of clusters with the silhouette technique, a quantification of how similar an object is to its assigned cluster compared to neighbouring clusters. The maximum average silhouette is considered the appropriate number of clusters. Clustering arrangements 1–10 were tested using the factoextra R package (Figure S1B). Statistical significance of hierarchical clusters was tested using pvclust boostrap analysis of clustering with threshold of au>90% significance.26 To quantify α-diversity, Shannon diversity (H) was calculated for all samples using H = –Σpiln(pi ), where pi represents the normalized population fraction of species i. The number ofunique OTUs represented in a sample was also used as a metric ofα-diversity. To test whether α-diversity changed between beforewash and after-wash samples across all patients, a paired Student's t-test was used on Shannon diversity quantifications and total unique OTUs on before and after samples.
2.7 Data availability
Raw sequencing data are available from the Short Read Archive (SRA) with accession number PRJNA704944.
3 RESULTS
3.1 Characterization of patient venous stasis
ulcer microbiome We investigated the wound bacterial microbiome ecology of 11 patients with established VLUs by collecting skin swabs from wounds following removal of dressings and compression bandages. Swabs were collected prior to and after washing with either a hypochlorous acid- or a chlorohexidine-based soap solution. We performed 16S amplicon sequencing on these before-wash and afterwash swab samples, obtaining libraries with an average sequencing depth of approximately 46,000 reads per sample. From these data, we were able to identify 44 different genera present in any sample at >1% relative abundance, a commonly employed threshold to distinguish low abundance genera from common or high abundance genera clinically27 (Tables 1 and S1).
Previous studies have shown VLU microbiomes comprised a diverse bacterial population that varies depending on patient. To examine diversity of the bacterial populations in VLUs in this patient cohort, we quantified the relative abundance of bacterial genera in each patient before wash. We found the top 10 most ubiquitous genera to contain mostly gram-negative bacteria with some representation of gram-positive bacteria. Organisms included aerobes, anaerobes, and facultative anaerobes (Table 2). The top five genera in order of most to least abundant were Proteus, Pseudomonas, Morganella, Providencia and Finegoldia. Of these, Morganella was unique to this patient population compared to several studies examining microbiome in VLU patients16,28 (Figure 1(A)). Cluster analysis based on the Bray-Curtis index of relative abundance of shared genera across patients revealed that patients formed four unsupervised clusters (Figure 1(B)) as determined by comparison of intra- and inter-cluster distances through silhouette analysis (Figure S1B). Significance of hierarchical clusters was determined using a multi-scale bootstrap resampling technique on all clusters (4clusters = pval >90%, Figure S1C). Principal coordinate analysis of the Bray-Curtis distance indices also displayed four groups when the top three most variable axes were measured (total variance captured 60.8%) (Figure 1(C)). To determine patterns in community composition of each of the four clusters, we examined alpha diversity, a measure of community richness and evenness within clusters (Figure 1(D)). We found that cluster 3 had reduced diversity compared to other clusters. We next examined the number and composition of genera in each patient (Figure 1(E)). We found that each patient varied in the community members present in samples before wash, yet a few taxonomic features were consistent within each cluster (Table 3). Cluster 1 contained a single patient (P-42) predominantly colonized by four genera, the most abundant of these genera being an unidentified genus from the family Oxalobacteraceae. Cluster 2 patients (P-33, P-41, and P-43) were colonized mainly by an unidentified genus from Alcaligenaceae (18%–64%) and had 7–9 genera total. Cluster 3 patients (P-28, P-30, and P-40) were colonized by Proteus as the dominant genera (45%– 90%) and were colonized by fewer genera overall (2–4) than other patients in this cohort, suggesting reduced diversity of the microbiome in this patient subset. All Cluster 4 patients exhibited a large abundance of Morganella. These data suggest that there may be underlying characteristics in the wound environment promoting growth of particular genera in some patients in this cohort.
3.2 Washing venous stasis ulcers does not change diversity of the ulcer microbiome
Previous studies examining VLU microbiomes report contradictory results regarding microbiome diversity in cases of healed or unhealed wounds. In some cases, diversity is either unchanged or higher in wounds that did not heal, and in other cases, no correlation is found regarding length of time of wound healing or treatment with antibi14,28 To understand the effect of washing of VLUs on microbiome diversity, we quantified patient samples for metrics of microbiome diversity within sample before and after washing across this patient cohort (Figure 2(A), (B)). We first examined the number of genera >1% in each patient's set of samples before and after washing and compared whether there was effect of washing on species richness across the patient cohort (Figure 2(A)). We found no difference overall in species richness before and after washing (p-value 0.42, Student's paired t-test). We also examined the relative proportion of each species within a sample as a measure of diversity using the Shannon diversity index and compared samples before and after washing across the dataset. No statistical difference was detected across the dataset in evenness of the distribution of genera (p value 0.43, Student's paired t-test) (Figure 2(B)). Interestingly, when examining genera richness and genera diversity within individual patients, some notable differences in alpha diversity could be detected (Figure 2(C), (D)). However, additional data are required to confirm these observations. When quantifying number of genera in beforeand after-wash samples by patient (present at >1% relative abundance), we found 3/11 patients lost detected genera, 5/11 patients gained detected genera, and 3 patients experienced no change in detected genera (Figure 2(C)). Also, comparison of Shannon indices before and after washing for each patient revealed an approximately even split between patients with increased diversity and patients with decreased diversity following washing (Figure 2(D)). The lack of significant difference in alpha diversity metrics including richness and diversity suggests that washing does not affect diversity of patient microbiome samples in this cohort.
3.3 Modulation of community structure of venous stasis ulcers following washing
Though overall species richness and evenness were unchanged by washing in our patient population, specific community composition of wounds may be affected by the washing procedure itself, particularly if washing affects the ability of certain bacteria to adhere to the wound. Specific community structure of VLUs across samples in this patient cohort before wash revealed some similarities within clusters of patients' VLU microbiomes (Figure 1(B)–(D)). Therefore, we next examined changes in community structure associated with washing within each patient and each patient cluster. First, we assessed interpersonal variation of all samples before washing and after washing using Bray-Curtis index and found that samples had a high level of variation in community structure in both before and after samples across patients (Figure 3(A)). When comparing intrapersonal variation of samples before and after washing within each patient, community structure variation was reduced. This finding suggests that community structure is more similar within a patient than across patients, supporting the high diversity of VLU microbiomes. Previous studies surveying the healthy skin microbiome9,10 have similarly found that interpersonal variation is greater than intrapersonal variation.
To address whether particular bacteria were more or less affected by the washing procedure, we compared the relative abundance of each bacterial genera across patients before and after washing (Figure 3(B)). We found that no bacterial genera had increasing or decreasing trends following wound washing across all patients. However, particular patients exhibited increases or decreases in specific genera. Moreover, strikingly, the salient genera defining each cluster decreased after wash in all patients. Namely, Oxalobacteraceae decreased in P-42 defining Cluster 1, Alcaligenaceae decreased in all Cluster 2 patients, Proteus decreased in all Cluster 3 patients, and Morganella decreased in all Cluster 4 patients (Table 3). Interestingly, 2 of the 3 patients in Cluster 3 exhibiting the most pronounced decrease in Proteus following washing displayed concomitant increases in Pseudomonas (P-30, P-40), though in other clusters,increases in Proteus following washing did not correlate to a decrease in Pseudomonas (P-42). We also found no correlation in number of genera with Bray–Curtis dissimilarity measure (Figure 3(A)) before and after wash, suggesting that the degree of change in community structure following wash is not tied to the number of genera present before wash.
3.4 Culture-based analysis reveals decrease in abundance of viable bacteria
We qualitatively measured the presence or absence of bacteria using standard culturing methods as complimentary analysis to our 16S rRNA gene sequencing results (Figure 4). We found that samples before wash unanimously had bacterial growth on tryptic soy agar (TSA). Most samples excluding P-33 contained gram-negative bacteria in their pre-wash samples as seen by presence of bacteria on MacConkey growth media plates. All samples except P-33 showed growth on Streptococcus selective plates in prewash samples. Six of 11 samples showed growth on MSA plates indicative of Staphylococcus or Micrococcus. After wash, one patient showed an absence of bacterial growth on TSA. Most patients' samples contained gramnegative bacteria. Interestingly, the majority of patients showed an overall loss in Streptococcus and Staphylococcus/Micrococcus species after washing. These results suggest specific bacteria genera are affected by the washing process as several genera were newly detected or lost due to washing.
4 DISCUSSION
Our 16S sequencing classification of bacterial genera in VLU wounds illustrates that microbiome differences within and across patients before and after washing are diverse and individual to the patient. We identified that patients' microbiomes in wounds prior to washing ranged from being predominantly characterized by a few genera to many genera and that relative abundances of genera were highly variable across patients. Trends in the number and distribution of genera within patients before and after washing were variable, with both increases and decreases in diversity. Thus, no consistent trend in diversity was observed. Though the number of patients in this study was relatively small, we were able to find trends in VLU microbiome community structure within small clusters of patients prior to washing and a reduction in predominant genera within these groups of patients. Although washing did not consistently affect overall diversity of bacterial populations across patients, individual genera in certain patients displayed increases or decreases in abundance following washing treatment. Most strikingly, the salient genus within each cluster consistently decreased in relative abundance following washing.
Chronic wound infections have been shown to be polymicrobial, yet biofilms can also be predominantly populated with one bacterial species. Interestingly, before washing of wounds in this patient cohort, an average of 7 bacterial genera, and as many as 15 genera, could be detected. However, two patients had wounds with a single genera colonizing at more than 50% relative abundance. The varying degree to which patient samples were polymicrobial agrees with previous research that found that most wounds are polymicrobial, but a small percentage of wounds were predominantly colonized by one or two species.20
Bacteria ranging from commensals to known pathogens have been shown to form biofilms in studies of VLU microbiomes. In our study, patient wounds with predominantly one genus were comprised of Proteus. Proteus, an opportunistic pathogen, has been shown to be an infectious agent in soft tissue infections, and was seen as a dominant genera colonizing VLUs in another study, though only in a few patient samples.28 In diabetic foot ulcers with monoculture wounds, Proteus mirablis was associated with limb loss. In the same study, Morganella, another predominant colonizer in this study, and known contributor to soft tissue infections, was also found associated with limb loss in diabetic foot ulcers.29 Members of the family Alcaligenacea were also highly represented in two patient samples. Genera within Alcaligenacea are gram-negative rods found in a variety of environments including the human body, and have shown conflicting results in regards to promoting or inhibiting wound healing. Interestingly, one study has implicated Alcaligenes faecalis as a causative agent in skin and soft tissue infections in a small number of patients with vascular30 In contrast, a more recent study examining the microbiome of diabetic foot ulcers found that Alcaligenes faecalis promoted wound healing in an in vitro skin model suggesting that host, environment, or organism factors determine wound disease outcome in relation to this 31 We also found that a genera identified as Pseudomonas was highly represented in patient samples, particularly before wash. P. aeruginosa is the most common producer of single organism biofilms and is sometimes associated with poor prognosis for wound20 However, Pseudomonas representatives have also been shown to be able to colonize wounds without delaying wound healing, suggesting that organisms in this genus may have a diverse role in the wound microbiome.32 The presence of Proteus, Alcaligenacea, and Pseudomonas in patients in this dataset as predominating colonizers before wash may be suggestive of wounds that have formed biofilms and therefore may be more recalcitrant to therapy.
Previous studies have also found anaerobic bacterial species to predominate in the wound.8 In our study, 8 of the top 10 taxa were from genera usually identified as anaerobes. Wounds can be well aerated at the surface with oxygen becoming less available to deeper levels of the wound. Unlike typical clinical culturing methods, the methodology used in this study, including wound sampling technique, namely the application of pressure to express wound exudate, and isolation of bacterial DNA followed by targeted sequencing of 16S rRNA genes, allowed for identification of anaerobes in wound18.
The stability of the microbiome in chronic wounds over time is associated with poor wound healing.7 Topical antibiotics and antiseptics are more efficacious when they are able to change the dynamics of the wound microbiome.7,27 In this study, wounds were washed with chlorohexidine gluconate and hypocholorous acid, each of which is commonly used independently in wound cleansing.33 Chlorohexidine, when used in isolation, has been shown in a previous study to confound the effects of DNA sequencing through retention of DNA on the skin surface leading to an inability to detect changes in genera or patient microbiome diversity post-wash. The authors hypothesized that the inflammatory reaction induced by chlorohexidine could lead to disruption of the skin barrier surface and promote DNA retention; however, the molecular mechanism of DNA retention was not formally tested in this study.22 In contrast, although wound washing did not affect overall diversity in our study population, washing was able to destabilize the microbiomes of several patients, as shown by the poor correlation of before and after samples, as well as changes in the relative abundance of bacteria. We hypothesize that we could capture microbiome changes because chlorohexidine and hypochlorous acid were added in combination. The addition of hypochlorous acid, which can reduce the inflammatory response and disrupt the polysaccharide matrix in biofilms,34 may ameliorate the immune-related skin barrier defects as well as potentially reduce general adhesion of DNA to skin. We were unable to find another study that examined these two wash solutions in combination. Thus, further characterization of skin inflammatory response and DNA retention in this context is an interesting avenue for future research.
A known caveat of sequencing is its inability to distinguish live and dead bacteria; however, culturing techniques suffer from an inability to grow all bacterial genera present in a sample. Though these drawbacks in experimental techniques exist, our study highlights that we are able to show shifts in structure of bacterial genera due to washing, suggesting that these techniques can in fact highlight trends in microbial community dynamics, particularly in combination. Indeed, culturing with media that specifically enriched for Streptococcus and Staphylococcus/Micrococcus revealed a decrease of these genera after wash in most patient samples, complimenting the sequencing results that captured increases and decreases in genera that could not be cultured. Results from both sequencing and culturing suggest a disruption of specific genera after wash, which could potentially be beneficial to the healing process. The knowledge that standard of care therapies can achieve disruption of microbiome genera may inform the frequency at which dressings need to be changed and duration of wash in order to have the wounds appropriately cleansed. Future studies examining correlations between washing, microbiome dynamics, and patient healing time will be informative to understanding possible mechanisms by which wound washing may be beneficial to healing through modulation of the microbiome.
Microbiome dynamics with respect to wound treatments are an actively researched area, yet studies have mainly focused on temporal dynamics of chronic wounds with respect to healing time. Few studies have focused on the effects of treatment modalities, particularly standard of care wound therapies, on the microbiome.7,27 Our study examined a standard of care therapy, wound washing, prior to applying dressing to the wound, and its effects on wound microbiome dynamics, adding to the knowledge from existing studies examining chronic wound microbiomes and effects of standard of care therapies.22,36,37 Washing and wound debridement, or removal of dead tissue from the wound, is a common standard-of-care therapy with a proven track record of success in regards to improvements in healing outcomes.35,36,37 Verbanic et al. examined the immediate effects of wound debridement on the wound microbiome of patients and found no difference in diversity between the woundpre- and post- debridement. Like Verbanic et al., we found no global increase or decrease in overall diversity of bacteria with standard of care therapy. We did not record debridement as part of standard of care for this patient cohort; however, we recognize that there could potentially be differences in specific genera in patient microbiomes that may be due to debridement in conjunction with washing. Though diversity of microbiomes was unaffected by washing regimens, individuals in the cohort displayed large shifts in microbiome composition with poor correlation in relative abundances of bacteria before and after wash. Interestingly, wounds with shifting microbiomes may promote wound healing, particularly when a pathogenic bacteria is displaced from the wound niche.7 Washing, in this patient cohort, had varying effects and it will be interesting to understand the impact of washing and microbiome dynamics on wound healing in future studies.