Fourier‐transform Infrared (FT‐IR) spectroscopy fingerprints subpopulations of extracellular vesicles of different sizes and cellular origin

指纹(计算) 主成分分析 细胞外小泡 傅里叶变换红外光谱 计算生物学 傅里叶变换 化学 光谱学 生物系统 生物 计算机科学 物理 细胞生物学 人工智能 光学 量子力学
作者
Lucia Paolini,Stefania Federici,Giovanni Consoli,Diletta Arceri,Annalisa Radeghieri,Ivano Alessandri,Paolo Bergese
出处
期刊:Journal of extracellular vesicles [Taylor & Francis]
卷期号:9 (1) 被引量:45
标识
DOI:10.1080/20013078.2020.1741174
摘要

Identification of extracellular vesicle (EV) subpopulations remains an open challenge. To date, the common strategy is based on searching and probing set of molecular components and physical properties intended to be univocally characteristics of the target subpopulation. Pitfalls include the risk to opt for an unsuitable marker set - which may either not represent the subpopulation or also cover other unintended subpopulations - and the need to use different characterization techniques and equipment. This approach focused on specific markers may result inadequate to routinely deal with EV subpopulations that have an intrinsic high level of heterogeneity. In this paper, we show that Fourier-transform Infrared (FT-IR) spectroscopy can provide a collective fingerprint of EV subpopulations in one single experiment. FT-IR measurements were performed on large (LEVs, ~600 nm), medium (MEVs, ~200 nm) and small (SEVs ~60 nm) EVs enriched from two different cell lines medium: murine prostate cancer (TRAMP-C2) and skin melanoma (B16). Spectral regions between 3100-2800 cm-1 and 1880-900 cm-1, corresponding to functional groups mainly ascribed to lipid and protein contributions, were acquired and processed by Principal Component Analysis (PCA). LEVs, MEVs and SEVs were separately grouped for both the considered cell lines. Moreover, subpopulations of the same size but from different sources were assigned (with different degrees of accuracy) to two different groups. These findings demonstrate that FT-IR has the potential to quickly fingerprint EV subpopulations as a whole, suggesting an appealing complement/alternative for their characterization and grading, extendable to healthy and pathological EVs and fully artificial nanovesicles.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
Flm发布了新的文献求助10
1秒前
我是老大应助陈哈哈采纳,获得10
2秒前
doller应助朱洪帆采纳,获得10
3秒前
moya发布了新的文献求助10
5秒前
blueming完成签到,获得积分10
5秒前
5秒前
bobo发布了新的文献求助10
6秒前
7秒前
9秒前
皮卡丘发布了新的文献求助10
12秒前
英俊的铭应助路遥知马力采纳,获得10
12秒前
科研通AI6.3应助大猫采纳,获得10
13秒前
14秒前
干净铅笔完成签到,获得积分10
14秒前
linxiang发布了新的文献求助30
15秒前
CHEN完成签到 ,获得积分10
16秒前
bobo完成签到,获得积分10
17秒前
传统的捕发布了新的文献求助10
20秒前
桐桐应助goodman采纳,获得10
21秒前
22秒前
一禾叶完成签到,获得积分10
22秒前
22秒前
23秒前
24秒前
26秒前
洋洋晓晓完成签到 ,获得积分10
26秒前
左友铭发布了新的文献求助10
28秒前
悦0806发布了新的文献求助10
28秒前
29秒前
31秒前
31秒前
皮卡丘完成签到,获得积分10
32秒前
34秒前
天天快乐应助朱洪帆采纳,获得10
36秒前
无花果应助小黄小黄辉煌采纳,获得10
36秒前
maxdie111发布了新的文献求助10
37秒前
打打应助Flm采纳,获得10
37秒前
搜集达人应助左友铭采纳,获得10
37秒前
荆轲刺秦王完成签到 ,获得积分10
38秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Development Across Adulthood 1000
Chemistry and Physics of Carbon Volume 18 800
The formation of Australian attitudes towards China, 1918-1941 660
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6448421
求助须知:如何正确求助?哪些是违规求助? 8261456
关于积分的说明 17600542
捐赠科研通 5510788
什么是DOI,文献DOI怎么找? 2902644
邀请新用户注册赠送积分活动 1879708
关于科研通互助平台的介绍 1720622