云杉木材酶解的延时三维图像数据集

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Solmaz Hossein Khani , Noah Remy , Khadidja Ould Amer , Berangère Lebas , Anouck Habrant , Grégoire Malandain , Gabriel Paës , Yassin Refahi
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引用次数: 0

摘要

在气候变化的背景下,利用植物细胞壁作为化石碳资源的替代品是很重要的。为了实现经济上可行的植物细胞壁转化为生物燃料和生物材料,有必要更好地了解细胞壁酶解并克服其解构的顽固性。虽然大多数研究的重点是纳米尺度的顽固标记物的鉴定,但在微尺度上对细胞壁水解的定量研究,特别是细胞壁形态参数的研究,仍然相对不够充分。这主要是由于缺乏在微尺度上细胞壁酶解的定量数据。众所周知,获取和处理可靠的微尺度数据集具有挑战性;样品需要保持在恒温下进行有效的酶解,并在相当长的时间内成像。处理获得的数据集以提取细胞壁形态参数也是具有挑战性的,因为细胞壁在酶水解过程中会发生解构和变形。在高度解构的条件下,这变得特别具有挑战性。这里展示的数据集包括使用荧光共聚焦显微镜获得的高度解构的预处理云杉木材的延时3D图像,以及所获得的延时的细胞分辨率分割。与此水解数据集一起,还提供了未添加酶鸡尾酒的预处理云杉木材样品的控制延时图像。控制数据集包括6505个分割和跟踪的细胞。水解数据集包括6699个处于广泛解构不同阶段的跟踪细胞。总的来说,这些数据集提供了一套可靠和全面的延时3D图像来研究细胞和组织尺度上的细胞壁酶解,这可以更好地用于了解植物生物量有效转化为可持续产品的微观限制因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time-lapse 3D image datasets of spruce tree wood enzymatic deconstruction
The transition to use plant cell walls as an alternative to fossil carbon resources is important in the context of climate change. To achieve an economically viable plant cell wall transformation into biofuels and biomaterials, it is essential to better understand cell wall enzymatic deconstruction and overcome its recalcitrance to deconstruction. While identification of nanoscale markers of recalcitrance has been the focus of the majority of studies, quantitative investigation of cell wall hydrolysis at microscale, particularly the cell wall morphological parameters, remains relatively insufficiently addressed. This is mainly due to the lack of quantitative data on cell wall enzymatic deconstruction at microscale. Acquisition and processing of reliable microscale datasets are notoriously challenging; the sample needs to be kept at a constant temperature for efficient enzymatic hydrolysis and imaged over a considerable number of hours. Processing the acquired datasets to extract cell wall morphological parameters is also challenging due to cell wall deconstruction and deformations occurring during enzymatic hydrolysis. This becomes particularly challenging under high deconstruction conditions. The datasets presented here include time-lapse 3D images of highly deconstructed pretreated spruce wood acquired using fluorescence confocal microscopy, together with cell resolution segmentations of the acquired time-lapses. Along with this hydrolysis dataset, control time-lapse images of pretreated spruce wood samples acquired without adding enzymatic cocktail are also presented. The control dataset includes 6505 segmented and tracked cells. The hydrolysis dataset includes 6699 tracked cells at various stages of extensive deconstruction. Overall, these datasets provide a reliable and comprehensive set of time-lapse 3D images to study cell wall enzymatic deconstruction at cell and tissue scales, which can be used to better understand the microscale limiting factors of efficient transformation of plant biomass into sustainable products.
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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