我们要感谢安东尼. 鲍文, 他的幻灯片被作为第二个人并排比较, 以及他的幻灯片被用作第三人并排和第二次显微镜比较。

1. 印墨幻灯片的制作
<ol><li>吸管10µL 的隐球菌样本到幻灯片上。任何循环酵母菌株将工作, 但这个实验 H99 是唯一的应变使用。 注: 如果样品直接来自培养基, 用 PBS 或水稀释1:2 可以帮助防止墨汁结块。</li>
	<li>吸管2µL 印度墨水污点的样品和混合通过物理推动吸管尖端的样品和移动, 直到印度墨水出现均匀分布。</li>
	<li>通过将片的左边缘与幻灯片的表面片, 然后在样品上轻轻地、均匀地降低片的另一侧, 在样品上放置一个。</li>
	<li>允许滑动到空气干燥5分钟。</li>
	<li>轻轻地涂上一层指甲油到片边界, 形成一个印章, 并保存印度墨水污点。</li>
</ol>2. 影像幻灯片
<ol><li>将幻灯片放在明亮的野外显微镜下, 用照相机附件和已知的 pixel-to-micron 转换。调整滤镜、目标和对比度, 使细胞胶囊清晰, 细胞体聚焦, 暗色带。 注意: 各种滤镜、目标和对比度设置都可以使用, 但建议使用20x 目标、Ph1 过滤器和2x2 分。</li>
	<li>确保视野是稠密的, 但不是过度的与隐球菌细胞, 与细胞囊和背景清晰的对比, 并适当集中在细胞体可视化为一个黑暗的波段。 注意: 最佳图像的精确单元格数将因所使用的样本和目标而异。重要的方面是确保细胞不聚集或重叠, 细胞的焦平面不明显变化, 并有明显的印度墨水污点清晰可见的背景 (至少25% 的领域)。</li>
	<li>将图像保存到具有明确标题的单个目录中, 因为测量算法将在单个目录中的图像上运行, 并且输出数据将根据图像文件的名称进行组织。</li>
</ol>3. 算法设置
<ol><li>安装 Python 版本2。7</li>
	<li>通过运行 "pip 安装枕头" 和 "pip 安装 openpyxl" 命令安装附加的 python 库。</li>
	<li>按照以下说明安装 MATLAB</li>
	<li>按照 https://www.mathworks.com/help/matlab/matlab_external/install-the-matlab-engine-for-python.html 提供的说明构建 MATLAB python 库。</li>
	<li>下载这份手稿的补充材料 ("QCA", "Analysis2", 和 "TestRun m") 所需的三文件。 注意: 这些文件可以提取到任何位置, 但所有三必须在同一目录中。</li>
</ol>4. 算法的使用
<ol><li>通过双击 QCA 运行应用程序。 注意: 应用程序可能需要几分钟才能开始。"QCA" 文件包含调用 ". m" 文件的程序结构来运行实际算法。</li>
	<li>按照程序中概述的步骤操作。<ol>
<li>输入图像文件的扩展类型, 前面是句点, 用分号 (ex) 分隔。TIF;。jpeg ") 然后单击Enter按钮。</li>
		<li>通过单击选择目录"按钮并选择包含图像的文件夹, 选择图像文件所在的目录。</li>
		<li>通过单击生成图像列表按钮, 在目录中生成图像文件的列表。图像将在右侧的文本框中列出。检查并确保清单的准确性和完整性。</li>
		<li>通过单击选择随机图像"按钮, 从列表中选择一个随机图像以用作预览。 注意: 如果由于图像模式错误而无法打开图像, 该算法将仍然正常工作, 尽管不显示图像。步骤4.2.7 后, 测试图像仍将显示。</li>
		<li>输入显微镜物镜和分设置。如果默认设置与使用的显微镜不匹配, 请选择 "自定义像素转换" 并输入图像文件的 pixel-to-um 转换。选定后, 单击计算转换"按钮, 并确保根据右侧的文本框进行的转换是正确的。 注意: 在图 1中显示的具有代表性的图像是用40x 的放大倍数和2x2 分的选择来计算的。</li>
		<li>用于圆检测的输入算法参数。<ol>
<li>输入最小和最大半径可检测的外舱探测作为最小和最大胶囊半径条目。较小的范围将允许更准确的结果。</li>
			<li>输入最小和最大半径检测为细胞体探测作为最小和最大细胞体半径条目。 注意: 根据源图像, 所有四个条目都应该是以像素为单位表示各自值的数字。</li>
			<li>移动胶囊和细胞体灵敏度滑块来调整算法的灵敏度阈值。低灵敏度将是严格的, 并减少假阳性圆检测, 但也可能检测到更少的真正的圈子。反之, 高灵敏度将提高检测率, 但也可能导致假阳性圆。 注: 有代表性的结果, 最小胶囊半径为 7, 最大胶囊半径为 45, 最小体半径为 4, 最大体半径为 30, 胶囊灵敏度 87, 体灵敏度87。</li>
		</ol>
</li>
		<li>通过单击运行测试按钮来测试随机选择的图像上的参数。结果将显示在程序的上部中心, 替换原始图像。如果结果看起来准确, 建议选择一个额外的随机图像, 以确保选定的参数将适合所有选定的图像。<ol>
<li>最大化检测到的物体和胶囊的数量, 并目视检查这些圆圈是否适合正确显示。检测到的马蹄形内的主体数量将显示在右侧的文本框中。否则, 操作算法参数, 直到结果是准确的。 注: 厚色圆圈只对可视化有帮助。实际产生的测量圆是一个数学曲线计算的小贩的算法。</li>
		</ol>
</li>
		<li>单击开始分析按钮, 在整个映像文件目录中运行检测算法。每个图像将被分析, 程序将显示 "完成" 在文本框的权利, 当所有的图像都被分析。</li>
		<li>单击匹配和清除按钮。这将匹配检测到的细胞体的检测胶囊, 他们驻留在, 并计算真正的胶囊半径减去身体从胶囊。 注意: 如果该算法被用于检测荧光或其他只检测到一个圆圈的情况, 这一步是不必要的。而只需单击仅拉正文或仅拉式胶囊按钮, 即可分别只收集蓝色或绿色圆圈的数据。重要的是要注意, 如果只检索胶囊的数据, 半径将引用的细胞的总半径, 因为不能减去细胞体的半径。</li>
		<li>在映像目录中的 "CleanedOuput. csv" 文件中找到已完成的数据。如果仅选择了一条数据, 则该文件将被标记为 "CleanedBodies" 或 "CleanedCapsules. csv"。</li>
	</ol>
</li>
</ol>

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作者没有利益冲突透露。

这一技术的关键步骤是准备印度墨水幻灯片和获取显微镜图像。虽然该算法已成功地测试了各种幻灯片和图像技术的推荐协议在这篇手稿中描述。该多糖胶囊是基于印度墨水微粒从胶囊的领域排除, 因为这些粒子太大, 渗透到多糖纤维网络。印度油墨的排斥导致一个明亮的圆圈顶部的黑暗背景。该算法根据它们与背景的对比度来检测圆。因此, 大量印墨色斑会导致多糖胶囊与背景的对比度增高, 增加信噪比, 提高结果质量。相反, 细胞体被检测为一个黑暗的圆圈顶部明亮的背景。该细胞体将改变外观的基础上, 它的焦距显微镜是设置, 出现作为一个弥漫灰色圆圈在顶部或底部的细胞和作为一个凝聚黑暗带在中心。出于同样的原因, 作为一个凝聚的, 暗波段的细胞体出现的焦平面应用于图像采集, 因为这将导致最精确的圆检测。
此处报告的方法已经过多次修改和疑难解答。该算法最初被编码, 期望单元格不会小于4或大于60像素的基础上使用显微镜。为了将此算法的应用扩展到不同的放大和单元格大小, 这些限制改为由协议中描述的用户输入字段取代。用户现在可以输入特定于每个实验的参数, 以达到最大的精确度。如果将此算法应用于隐球菌胶囊测量之外的情况, 建议首先设置一系列范围查找条件, 以确定如何生成和映像样本。
这项技术最重要的限制是, 它是在设计的具体应用, 即测量隐球菌胶囊。虽然它可以很容易地修改, 以适应其他应用程序, 这个脚本只是直接适用于胶囊测量协议上面概述。然而, 这一限制也说明了该方法在其领域和现有方法方面的重要性。此外, 萌芽的酵母细胞可以提出一个问题的调查谁希望只测量父母的细胞大小。该算法能够检测芽作为唯一的细胞 (图 S2A)。首先, 这可能是一个问题, 如果调查人员在这种情况下, 他们希望删除芽测量, 或删除两个细胞, 如果它不能确定哪个检测到的圆圈是芽, 哪个是父。其次, 这可能会导致另一个问题, 如果芽被检测为一个细胞体仍然在父母胶囊的范围内 (图 S2B), 在这种情况下, 算法将测量芽在参考的父母胶囊。在此示例中, 每个单元格将被计算两次, 因为每个单元格都位于两个胶囊中。一旦协议完成, 这些问题中的任何一个都可以轻松解决。最终数据集将显示为电子表格, 其中每个检测到的单元格都根据它来自的图像文件进行标记, 而单元格体的 x 和 y 坐标 (图 S3)。调查人员可以简单地查找和排除与芽匹配的数据。尽管胶囊的大小是一个重要的和严重的研究毒力因子隐球菌字段尚未建立标准协议的胶囊测量或图像采集。这项技术的目的是以准确和方便的方式来填补这些角色, 为实验室提供最低限度的先决条件。
这项技术的未来应用主要是将其应用于其他实验。任何基于图像的检测或测量的圆形物体都应该通过这个算法分析。将该算法应用于单个激光信道, 可以对荧光显微镜图像进行分析。细菌菌落计数可以实现, 并与额外的修改可以区分半乳糖记者。利用该算法估算菌落面积大小, 也可对酵母菌落生长的测定进行评价。

新生隐球菌是一种致病性酵母, 在全球范围内发现无所不在, 与人类疾病主要是免疫人群有关。C. 隐球菌最显著的原因是在撒哈拉以南非洲地区因传染性疾病而导致的全年死亡的一个重要因素1。隐球菌感染的主要临床表现是脑炎, 它是在受感染的巨噬细胞 (特洛伊木马方式) 或直接越过血脑屏障之后, 通过中枢神经系统的侵袭而发生的。C. 隐球菌表达了多种致病因子, 包括在人体温度、脲酶活性、黑和多糖胶囊的形成过程中复制的能力2。该多糖胶囊是由重复 glucuronoxylomannan 和 glucoronoxylomannangalactan 聚合物和功能作为保护屏障的因素, 如环境压力和宿主免疫应答2。
虽然隐球菌多糖胶囊大小的大小并没有持续与毒力相关, 但有证据表明它是致病因素2,3,4,5, 6,7。胶囊大小与脑膜炎病理相关6, 可影响巨噬细胞控制新生感染的能力5, 如果缺席则可能导致毒力丧失8。因此, 胶囊大小测量是常见的隐球菌研究, 但没有 fieldwide 标准的方法的胶囊测量。
目前, C. 隐球菌多糖胶囊的测量是基于手工测量的显微图像, 而且图像和测量的精确方法在实验室中各有不同9,10, 11。这种方法的一个直接的关注是, 一些研究需要获得数以千计的个人测量, 这使得保持准确性和可靠性的困难。此外, 即使在公布结果时, 对测量方法的描述也往往不够充分。许多出版物不解释如何获得他们的测量, 使用了什么焦平面, 他们如何确定胶囊的识别阈值, 无论他们使用的半径或直径, 无论是使用一个测量或平均数, 或其他详细.有些出版物仅说明使用的程序的方法, 例如, "Adobe Photoshop CS3 用于测量单元格"11。这种缺乏标准化和报告细节的情况可能会使重现性困难, 如果不是不可能的话。人的视力、电脑亮度、显微镜设置、滑动照明和其他因素之间的差异不仅在个体之间, 而且在样本之间也会有所不同, 而基于像素强度值的比值的计算将保持不变,适用于样品之间。这项技术是在提供一个标准化的, 准确的, 快速的, 简单的技术来测量胶囊大小的领域中, 没有以前。
如前所述, 海隧算法是长期的, 并且脚本自动地检测圈子以前被写了。此方法在其他脚本不足的两个方面有所改进。首先, 仅仅检测圆是不够的, 因为与隐球菌细胞的两个不同的圆圈必须相互关联检测。这种方法专门检测胶囊内的细胞体, 区分两者之间, 并只对相关的身体-胶囊对进行计算。第二, 即使遵循相同的协议, 不同的调查人员最终会得到不同的获取图像。通过允许调查人员控制每个算法参数, 可以调整该工具以匹配广泛的获取方法。不需要标准化的范围、目标、筛选等。
这种技术可以很容易地应用到任何情况下, 调查人员需要检测的圆圈内的图像, 与他们的背景形成对比。两个圆圈比他们的背景更亮, 更暗, 可以检测, 计数, 并用这种技术测量。

<table><tbody><tr><td>India Ink</td><td>Becton, Dickinson and Co.</td><td>261194</td><td></td></tr><tr><td>Fisherbrand Superfrost Microscope Slides</td><td>Fisher Scientific</td><td>12-550-143</td><td>25x75x1</td></tr><tr><td>Fisherfinest Premium Cover Glass</td><td>Fisher Scientific</td><td>12-548-B</td><td>22x22-1</td></tr><tr><td>Sally Hansen HardasNails Xtreme Wear Nail Polish</td><td>Sally Hansen</td><td>N/A</td><td>109 invisible</td></tr><tr><td>SAB Media</td><td>Sigma</td><td>S3306</td><td></td></tr><tr><td>Cryptotoccus neoformans</td><td>ATCC</td><td>208821</td><td>H99 strain</td></tr><tr><td>Olympus AX70 Microscope</td><td>Olympus</td><td>AX70TRF</td><td>Discontinued ; Bright Field Microscope</td></tr><tr><td>Qimaging Retiga 1300</td><td>Qimaging</td><td>N/A</td><td>Discontinued ; Camera Microscope Attachment</td></tr><tr><td>MATLAB</td><td>MathWorks</td><td>N/A</td><td>Most recent version recommended</td></tr><tr><td>Python Programming Language</td><td>Python</td><td>N/A</td><td>Version 2 necessary ; 2.7 recommended</td></tr><tr><td>Microsoft Excel</td><td>Microsoft</td><td>N/A</td><td>Most recent version recommended</td></tr><tr><td>Phosphate Buffered Saline (PBS)</td><td>Sigma</td><td>P3813</td><td></td></tr></tbody></table>

automated measurement of cryptococcal species polysaccharide capsule and cell body

这项技术的目的是为大量的多糖胶囊测量提供一个一致的, 准确的, 可管理的过程。
首先, 根据每个图像的唯一计算的强度值生成阈值图像。然后, 利用完备的圆霍夫变换 (红隧) 算法, 根据对象和背景的对比度来检测圆。最后, 根据中心坐标和半径大小对检测到的细胞胶囊和体进行匹配, 并在可管理的电子表格中将数据导出到用户。
这种技术的优点很简单但意义重大。首先, 由于这些计算是由一个算法而不是一个人来执行的, 所以精确度和可靠性都提高了。 无论分析多少样品, 准确度或可靠性都没有下降。其次, 此方法为 "隐球菌" 字段建立了一个潜在的标准操作过程, 而不是实验室中的胶囊测量变化的当前情况。第三, 由于手动胶囊测量是缓慢和单调的, 自动化允许快速测量大量的酵母细胞, 反过来又有利于高吞吐量数据分析和日益强大的统计。
该技术的主要局限性来自于该算法的功能。首先, 该算法将只生成圆。当隐球菌细胞及其胶囊采用圆形形态时, 很难将这种技术应用于非圆形物体的检测。其次, 由于如何检测圆, 红隧算法可以根据多个簇圆的外边缘检测出巨大的 pseudo-circles。但是, 在 pseudo-circle 中捕获的任何错误的单元格都可以很容易地检测到并从结果数据集中删除。
本技术是以印度油墨的光场显微镜为基础, 测定新生种的圆形多糖胶囊;虽然它可以应用于其他基于对比度的圆形物体测量。

图像首先由印度墨水幻灯片的显微镜, 使用明亮的野外显微镜和相机 (图 1a) 来获得。重要的是要使细胞分离, 并在足够低的密度不压倒的视野, 以及使用足够的污渍, 以创造对比细胞和背景。如协议中所述, 最佳图像的单元格的确切数目将因所使用的样本、显微镜和目标而异。重要的方面是确保细胞不聚集或重叠, 细胞的焦平面不明显变化, 并有明显的印度墨水污点清晰可见的背景 (至少25% 的领域)。这些方向允许算法通过取平均像素强度值和添加标准偏差来确定每个图像的唯一阈值。任何亮度值高于所述阀值的像素被认为是白色的, 任何具有强度值的低点都被认为是黑色的。生成的图像允许对胶囊的结束位置 (图 1B) 进行明确而清晰的区分。该算法然后有一个强大的底对比度为基础的圆形检测胶囊和原始图像提供了一个健壮的白色圆的细胞体。作为程序的一部分 (图 1C), 将生成检测到的圆的有代表性的可视化。这样, 用户就可以快速分析经过处理的图像并确保结果正确无误。
必须遵循精确的协议来获取最佳图像。子优化图像通常是由于胶囊和墨水之间缺乏对比 (图 2a)。最佳对比度和采集参数将根据样品、实验、相机和显微镜模型等不同而有所不同。一个最佳的图像是, 如果可能的话, 酵母细胞分离, 其中外边缘的胶囊有明显的对比, 印度墨水染色, 并在那里的细胞体是集中显示作为一个黑暗带, 与它的背景形成鲜明对比。如果在视图中有太多的单元格, 或者如果污渍太轻, 则像素强度值将会聚集, 程序将无法建立一个能够阐明胶囊大小的阈值 (图 2B)。当使用了次优图像时, 程序可以检测到大小不正确的圆, 无法检测任何圆, 或者基于阈值图像中的工件检测多个 pseudo-circles (图 2C)。
检测细胞体构成一个类似的问题, 在细胞的身体必须被形象化为一个强大的黑色圆圈的白色背景下的胶囊。在描述所需的图像采集焦平面时, 该问题在协议中得到了解决。要使用的最佳焦平面是将单元格体显示为深色、集中的带 (图 3a)。这个焦平面是可以接受的标准, 因为它适当地聚焦于细胞。这是证实通过可视化细胞壁与 Uvitex, 甲壳素染色 (图 3B)。Uvitex 染色清楚地显示了一个脆, 集中的细胞壁与微弱的信号在中心 (那里的顶部和底部的细胞体将被染色, 不集中)。
在这一方法的开发中, 确定该算法能准确地确定胶囊和细胞体的测量值也很重要。虽然代表圈子在早先数字是有为的, 实际测量在计算机和人的测量之间被比较。在准确地跟踪协议并获得最佳图像后, 该算法准确可靠 (图 4A)。然而, 如果协议被错误地跟随, 并且得到次优图象是由于糟糕的染色、过度拥挤或其他早先被提及的参量, 算法丢失准确性并且不能重述人的测量 (图 4B).由于这项技术最初是为一个特定的个体 (第一作者) 开发的, 不同的个体被要求使用它来确定染色和测量风格之间的差异是否会影响准确度, 尽管遵循了协议。结果表明, 只要协议遵循指示 (图 4C), 该技术就能广泛应用。同样, 这种技术可以与任何能够获得印墨幻灯片相衬图像的显微镜一起使用。为了确保该算法与其他显微镜设置保持准确, 该实验由第三位研究者使用不同的明亮场显微镜与相机相结合, 并与人工测量的胶囊直径进行比较。直径.计算机和人体测量之间没有显著差异 (图 4D)。
最后, 从荧光染色的角度探讨了该算法的应用前景。由于荧光成像仍然是基于信噪比的像素强度值, 该算法应易于适用于荧光图像, 只要染色是圆形的性质。当算法能够成功地从先前描述的图像 (图 5A, 5B) 中检测到 Uvitex 染色的细胞体时, 此应用程序被确认。用户应注意优化其实验的算法参数, 并在将来为任何新的应用开发标准化的协议。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56957/56957fig1.jpg"> 图 1: 获得最佳图像的代表性结果。A.印墨幻灯片的明亮场显微镜所获得的初始图像。B.使用从添加到标准偏差的平均像素强度值计算的阈值创建的二进制图像。该阈值以上的所有数值都被认为是白色的, 下面所有的都被视为黑色。C.算法所检测到的胶囊 (绿色) 和细胞体 (蓝色) 的可视化。所有图像均以2x2 分40x 放大倍数获得。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56957/56957fig2.jpg"> 图 2: sub-optimally 获得的图像的代表性结果。A.最初印度墨水幻灯片通过明亮的现场显微镜获得。不均匀和不充分的染色结果在一个特别明亮的背景与梯度强度。B.产生的二进制图像, 由于高背景信号, 胶囊不能明显区分。C.几个胶囊是无法检测到的。所有图像均以2x2 分40x 放大倍数获得。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56957/56957fig3.jpg"> 图 3:检测单元格体。A.以首选焦平面为中心的胶囊的明亮场图像。B. Uvitex 在首选焦平面上的细胞体的荧光图像。以2x2 分100x 放大倍数获得图像。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56957/56957fig4.jpg"> 图 4:算法 (黑色) 和人 (灰色) 分析结果的比较。A.当根据协议准备幻灯片并获得最佳图像时, 测量之间没有明显差异。B.如果不遵循该协议, 则算法不能准确地识别和测量胶囊。在这里具体的背景是不一致的, 并没有明确的对比之间的胶囊和背景。通过 t 检验计算出的显著变化为 P 值 < 0.05。C.要求独立调查员遵循该协议, 并将其分析与该算法进行比较。只要正确获取图像, 就能在观察者之间保持可靠性。D.使用第二个显微镜的第二个独立调查员确认该算法在个人和硬件之间保持准确性。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56957/56957fig5.jpg"> 图 5: 一种潜在的替代应用的算法: 荧光显微镜的识别和测量.细胞体被染色和影像与 Uvitex, 然后通过算法识别。检测到的圆将被标记为细胞壁, 因为检测是基于荧光信号。该检测算法可以通过修改用于生成图 1B和2B中所表示的初始二进制图像的阈值来专门识别最亮的信号 (细胞壁) 堆积。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Supplemental Figure 1" src="/files/ftp_upload/56957/56957supfig1.jpg"> 补充图 1: 在 Windows 环境中运行的应用程序的代表性屏幕快照.<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957supfig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Supplemental Figure 2" src="/files/ftp_upload/56957/56957supfig2.jpg"> 补充图 2: 检测到的发芽酵母细胞的表示.缩放条代表10µm. A.母细胞和芽在各自的囊中作为单独的细胞计算。B.一个母细胞和芽每两次计数, 一次为他们自己的胶囊和一次为其他细胞胶囊, 导致四总细胞检测从一个父母和一个芽。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957supfig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Supplemental Figure 3" src="/files/ftp_upload/56957/56957supfig3.jpg"> 补充图 3: 在单元检测和测量后提供的最后数据的表示形式.图像文件是指原始图像的名称。总半径是指代表绿色圆的半径、胶囊和细胞体的结合。胶囊 x 和胶囊 y 指的是该数据所适用的胶囊的坐标。身体半径是指代表蓝色圆圈的半径。胶囊半径指的是总半径减去身体半径, 导致半径仅为胶囊。只要用户在步骤3.2.5 中包含 pixel-to-micron 转换比率, 这些值就会在微米内。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/56957/56957supfig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Automated Measurement of Cryptococcal Species Polysaccharide Capsule and Cell Body at JoVE.com

Automated Measurement of Cryptococcal Species Polysaccharide Capsule and Cell Body

自动测量隐球菌种多糖胶囊和细胞体

该技术描述了一种用于测量多糖胶囊和体半径的自动批处理图像处理器。最初设计为新生隐球菌胶囊测量时, 自动图像处理器也可应用于其他基于对比度的圆形物体检测。

The purpose of this technique is to provide a consistent, accurate, and manageable process for large numbers of polysaccharide capsule measurements.
...

automated-measurement-cryptococcal-species-polysaccharide-capsule

Universidad San Sebastian

Research

JoVE Journal

Immunology and Infection

Automated Measurement of Cryptococcal Species Polysaccharide Capsule and Cell Body

7.2K 次观看.  Johns Hopkins Bloomberg School of Public Health. 该技术描述了一种用于测量多糖胶囊和体半径的自动批处理图像处理器。最初设计为新生隐球菌胶囊测量时, 自动图像处理器也可应用于其他基于对比度的圆形物体检测。

视频: Automated Measurement of Cryptococcal Species Polysaccharide Capsule and Cell Body

Separating Bacteria by Capsule Amount Using a Discontinuous Density Gradient

Capsule is a key virulence factor in many bacterial species, mediating immune evasion and resistance to various physical stresses. While many methods are available to quantify and compare capsule production between different strains or mutants, there is no widely used method for sorting bacteria based on how much capsule they produce. We have developed a method to separate bacteria by capsule amount, using a discontinuous density gradient. This method is used to compare capsule amounts semi-quantitatively between cultures, to isolate mutants with altered capsule production, and to purify capsulated bacteria from complex samples. This method can also be coupled with transposon-insertion sequencing to identify genes involved in capsule regulation. Here, the method is demonstrated in detail, including how to optimize the gradient conditions for a new bacterial species or strain, and how to construct and run the density gradient.

We demonstrate the use of discontinuous density gradients to separate bacterial populations based on capsule production. This method is used to compare capsule amount between cultures, isolate mutants with a specific capsule phenotype, or to identify capsule regulators. Described here is the optimization and running of the assay.

用不连续密度梯度用胶囊分离细菌

Capsule is a key virulence factor in many bacterial species, mediating immune evasion and resistance to various physical stresses. While many methods are ...

科研

遗传学

Use of Image Cytometry for Quantification of Pathogenic Fungi in Association with Host Cells

Studies of the cellular pathogenesis mechanisms of pathogenic yeasts such as Candida albicans, Histoplasma capsulatum, and Cryptococcus neoformans commonly employ infection of mammalian hosts or host cells (i.e. macrophages) followed by yeast quantification using colony forming unit analysis or flow cytometry. While colony forming unit enumeration has been the most commonly used method in the field, this technique has disadvantages and limitations, including slow growth of some fungal species on solid media and low and/or variable plating efficiencies, which is of particular concern when comparing growth of wild-type and mutant strains. Flow cytometry can provide rapid quantitative information regarding yeast viability, however, adoption of flow cytometric detection for pathogenic yeasts has been limited for a number of practical reasons including its high cost and biosafety considerations. Here, we demonstrate an image-based cytometric methodology using the Cellometer Vision (Nexcelom Bioscience, LLC) for the quantification of viable pathogenic yeasts in co-culture with macrophages. Our studies focus on detection of two human fungal pathogens: Histoplasma capsulatum and Candida albicans. H. capsulatum colonizes alveolar macrophages by replicating within the macrophage phagosome, and here, we quantitatively assess the growth of H. capsulatum yeasts in RAW 264.7 macrophages using acridine orange/propidium iodide staining in combination with image cytometry. Our method faithfully recapitulates growth trends as measured by traditional colony forming unit enumeration, but with significantly increased sensitivity. Additionally, we directly assess infection of live macrophages with a GFP-expressing strain of C. albicans. Our methodology offers a rapid, accurate, and economical means for detection and quantification of important human fungal pathogens in association with host cells.

Here, we demonstrate how image cytometry can be used for quantification of pathogenic fungi in association with host cells in culture. This technique can be used as an alternative to CFU enumeration.

使用的细胞图像分析仪量化致病真菌与宿主细胞协会

Studies of the cellular pathogenesis mechanisms of pathogenic yeasts such as Candida albicans, Histoplasma capsulatum, and Cryptococcus neoformans ...

免疫与感染

A Microscopic Phenotypic Assay for the Quantification of Intracellular Mycobacteria Adapted for High-throughput/High-content Screening

Despite the availability of therapy and vaccine, tuberculosis (TB) remains one of the most deadly and widespread bacterial infections in the world. Since several decades, the sudden burst of multi- and extensively-drug resistant strains is a serious threat for the control of tuberculosis. Therefore, it is essential to identify new targets and pathways critical for the causative agent of the tuberculosis, Mycobacterium tuberculosis (Mtb) and to search for novel chemicals that could become TB drugs. One approach is to set&#160;up methods suitable for the genetic and chemical screens of large scale libraries enabling the search of a needle in a haystack. To this end, we developed a phenotypic assay relying on the detection of fluorescently labeled Mtb within fluorescently labeled host&#160;cells using automated confocal microscopy. This in vitro assay allows an image based quantification of the colonization process of Mtb&#160;into the host and was optimized for the 384-well microplate format, which is proper for screens of siRNA-, chemical compound- or Mtb mutant-libraries. The images are then processed for multiparametric analysis, which provides read&#160;out inferring on the pathogenesis of Mtb&#160;within host cells.

Here, we describe a phenotypic assay applicable to the High-throughput/High-content screens of small-interfering synthetic RNA (siRNA), chemical compound, and Mycobacterium tuberculosis mutant libraries. This method relies on the detection of fluorescently labeled Mycobacterium tuberculosis within fluorescently labeled host&#160;cell using automated confocal microscopy.

用于适应高通量/高含量筛查的细胞内分枝杆菌定量的微观表型检测

Despite the availability of therapy and vaccine, tuberculosis (TB) remains one of the most deadly and widespread bacterial infections in the world. Since ...

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within a cell, tissue, organ, biological fluid, or organism. Metabolomics traditionally focuses on water-soluble metabolites. The water-soluble metabolome is the final product of a complex cellular network that integrates various genomic, epigenomic, transcriptomic, proteomic, and environmental factors. Hence, the metabolomic analysis directly assesses the outcome of the action for all these factors in a plethora of biological processes within various organisms. One of these organisms is the budding yeast Saccharomyces cerevisiae, a unicellular eukaryote with the fully sequenced genome. Because S. cerevisiae is amenable to comprehensive molecular analyses, it is used as a model for dissecting mechanisms underlying many biological processes within the eukaryotic cell. A versatile analytical method for the robust, sensitive, and accurate quantitative assessment of the water-soluble metabolome would provide the essential methodology for dissecting these mechanisms. Here we present a protocol for the optimized conditions of metabolic activity quenching in and water-soluble metabolite extraction from S. cerevisiae cells. The protocol also describes the use of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of the extracted water-soluble metabolites. The LC-MS/MS method of non-targeted metabolomics described here is versatile and robust. It enables the identification and quantification of more than 370 water-soluble metabolites with diverse structural, physical, and chemical properties, including different structural isomers and stereoisomeric forms of these metabolites. These metabolites include various energy carrier molecules, nucleotides, amino acids, monosaccharides, intermediates of glycolysis, and tricarboxylic cycle intermediates. The LC-MS/MS method of non-targeted metabolomics is sensitive and allows the identification and quantitation of some water-soluble metabolites at concentrations as low as 0.05 pmol/&#181;L. The method has been successfully used for assessing water-soluble metabolomes of wild-type and mutant yeast cells cultured under different conditions.

Quantitative Metabolomics of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol for the identification and quantitation of major classes of water-soluble metabolites in the yeast Saccharomyces cerevisiae. The described method is versatile, robust, and sensitive. It allows the separation of structural isomers and stereoisomeric forms of water-soluble metabolites from each other.

使用液体色谱加上串联质谱法的 糖核 酸菌的定量元细胞学

Metabolomics is a methodology used for the identification and quantification of many low-molecular-weight intermediates and products of metabolism within ...

生物化学

Size Matters: Measurement of Capsule Diameter in Cryptococcus neoformans

The polysaccharide capsule of Cryptococcus neoformans is the primary virulence factor and one of the most commonly studied aspects of this pathogenic yeast. Capsule size can vary widely between strains, has the ability to grow rapidly when introduced to stressful or low nutrient conditions, and has been positively correlated with strain virulence. For these reasons, the size of the capsule is of great interest to C. neoformans researchers. The growth of the C. neoformans capsule is induced during phenotypic testing to help understand the effects of different treatments on the yeast or size differences between strains. Here we describe one of the standard methods of capsule induction and compare two accepted methods of staining and measuring capsule diameter: (i) India ink, a negative stain, used in conjunction with conventional light microscopy and (ii) co-staining with fluorescent dyes of both the cell wall and capsule followed by confocal microscopy. Finally, we show how measurement of capsule diameter from India ink-stained samples can be automated using computational image analysis.

Size Matters: Measurement of Capsule Diameter in Cryptococcus neoformans

The polysaccharide capsule is the primary virulence factor in Cryptococcus neoformans, and its size correlates with strain virulence. Capsule diameter measurements are used in phenotypic testing and to gauge therapeutic efficacy. Here a standard method of capsule induction is presented, and two methods of staining and measuring diameter are compared.

尺寸事项:新生隐球菌中胶囊直径的测定

The polysaccharide capsule of Cryptococcus neoformans is the primary virulence factor and one of the most commonly studied aspects of this pathogenic ...

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

The method presented in this paper aims to automate Bio-AFM experiments and the recording of force curves. Using this method, it is possible to record forces curves on 1000 cells in 4 hours automatically. To maintain a 4 hour analysis time, the number of force curves per cell is reduced to 9 or 16. The method combines a Jython based program and a strategy for assembling cells on defined patterns. The program, implemented on a commercial Bio-AFM, can center the tip on the first cell of the array and then move, automatically, from cell to cell while recording force curves on each cell. Using this methodology, it is possible to access the biophysical parameters of the cells such as their rigidity, their adhesive properties, etc. With the automation and the large number of cells analyzed, one can access the behavior of the cell population. This is a breakthrough in the Bio-AFM field where data have, so far, been recorded on only a few tens of cells.

Automation of Bio-Atomic Force Microscope Measurements on Hundreds of C. albicans Cells

This protocol aims to automate AFM measurements on hundreds of microbial cells. First, microbes are immobilized into PDMS stamp microstructures and then force spectroscopy measurements are performed automatically on hundreds of immobilized cells.

数百个 C.白化病 细胞生物原子力显微镜测量自动化

The method presented in this paper aims to automate Bio-AFM experiments and the recording of force curves. Using this method, it is possible to record ...

生物工程

Adhesion of Candida parapsilosis to Bovine Serum Albumin under Fluid Shear

C. parapsilosis (Cp) is an emerging cause of bloodstream infections in certain populations. The&#160;Candida clade, including Cp, is increasingly developing resistance to the first and the second line of antifungals. Cp is frequently isolated from hands and skin surfaces, as well as the GI tract. Colonization by Candida predisposes individuals to invasive bloodstream infections. To successfully colonize or invade the host, yeast must be able to rapidly adhere to the body surfaces to prevent elimination by host defense mechanisms. Here we describe a method to measure adhesion of Cp to immobilized proteins under physiologic fluid shear, using an end-point adhesion assay in a commercially available multichannel microfluidic device. This method is optimized to improve reproducibility, minimize subjectivity, and allow for the fluorescent quantification of individual isolates. We also demonstrate that some clinical isolates of Cp show increased adhesion when grown in conditions mimicking a mammalian host, whereas a frequently used lab strain, CDC317, is non-adhesive under fluid shear.

Adhesion of Candida parapsilosis to Bovine Serum Albumin under Fluid Shear

Adhesion is an important first step in colonization and pathogenesis for Candida. Here, an in vitro assay is described to measure adhesion of C. parapsilosis isolates to immobilized proteins under fluid shear. A multichannel microfluidics device is used to compare multiple samples in parallel, followed by quantification using fluorescence imaging.

C. parapsilosis (Cp) is an emerging cause of bloodstream infections in certain populations. The&#160;Candida clade, including Cp, is increasingly ...

<meta charset="utf8"></head><body>与真菌伴侣共培养蔗糖分泌蓝细菌的方案

Assembly and Quantification of Co-Cultures Combining Heterotrophic Yeast with Phototrophic Sugar-Secreting Cyanobacteria

With the increasing demand for sustainable biotechnologies, mixed consortia containing a phototrophic microbe and heterotrophic partner species are being explored as a method for solar-driven bioproduction. One approach involves the use of CO2-fixing cyanobacteria that secrete organic carbon to support the metabolism of a co-cultivated heterotroph, which in turn transforms the carbon into higher-value goods or services. In this protocol, a technical description to assist the experimentalist in the establishment of a co-culture combining a sucrose-secreting cyanobacterial strain with a fungal partner(s), as represented by model yeast species, is provided. The protocol describes the key prerequisites for co-culture establishment: Defining the media composition, monitoring the growth characteristics of individual partners, and the analysis of mixed cultures with multiple species combined in the same growth vessel. Basic laboratory techniques for co-culture monitoring, including microscopy, cell counter, and single-cell flow cytometry, are summarized, and examples of nonproprietary software to use for data analysis of raw flow cytometry standard (FCS) files in line with FAIR (Findable, Accessible, Interoperable, Reusable) principles are provided. Finally, commentary on the bottlenecks and pitfalls frequently encountered when attempting to establish a co-culture with sugar-secreting cyanobacteria and a novel heterotrophic partner is included. This protocol provides a resource for researchers attempting to establish a new pair of co-cultured microbes that includes a cyanobacterium and a heterotrophic microbe.

<meta charset="utf8"></head><body>异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

This protocol provides a comprehensive guideline for the setup and quantitative monitoring of co-cultures, including photoautotrophic sugar-secreting cyanobacteria and heterotrophic yeasts.

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

With the increasing demand for sustainable biotechnologies, mixed consortia containing a phototrophic microbe and heterotrophic partner species are being ...

自动测量隐球菌种多糖胶囊和细胞体

摘要

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此视频中的章节

用不连续密度梯度用胶囊分离细菌

使用的细胞图像分析仪量化致病真菌与宿主细胞协会

用于适应高通量/高含量筛查的细胞内分枝杆菌定量的微观表型检测

使用液体色谱加上串联质谱法的糖核酸菌的定量元细胞学

尺寸事项:新生隐球菌中胶囊直径的测定

数百个 C.白化病细胞生物原子力显微镜测量自动化

Adhesion of Candida parapsilosis to Bovine Serum Albumin under Fluid Shear

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

自动测量隐球菌种多糖胶囊和细胞体

摘要

探索更多视频

此视频中的章节

用不连续密度梯度用胶囊分离细菌

使用的细胞图像分析仪量化致病真菌与宿主细胞协会

用于适应高通量/高含量筛查的细胞内分枝杆菌定量的微观表型检测

使用液体色谱加上串联质谱法的 糖核 酸菌的定量元细胞学

尺寸事项:新生隐球菌中胶囊直径的测定

数百个 C.白化病 细胞生物原子力显微镜测量自动化

Adhesion of Candida parapsilosis to Bovine Serum Albumin under Fluid Shear

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

异养酵母与光养分泌糖的蓝细菌相结合的共培养物的组装和定量

使用液体色谱加上串联质谱法的糖核酸菌的定量元细胞学

数百个 C.白化病细胞生物原子力显微镜测量自动化