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Fully Automatic Determination of Soil Bacterium Numbers Cell Volumes and Frequencies of Dividing Cells by Confocal Laser Scanning Microscopy and Image Analysis

机译:共聚焦激光扫描显微镜和图像分析全自动测定土壤细菌数量细胞体积和分裂细胞的频率

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摘要

We describe a fully automatic image analysis system capable of measuring cell numbers, volumes, lengths, and widths of bacteria in soil smears. The system also determines the number of cells in agglomerates and thus provides the frequency of dividing cells (FDC). Images are acquired from a confocal laser scanning microscope. The grey images are smoothed by convolution and by morphological erosion and dilation to remove noise. The background is equalized by flooding holes in the image and is then subtracted by two top hat transforms. Finally, the grey image is sharpened by delineation, and all particles above a fixed threshold are detected. The number of cells in each detected particle is determined by counting the number of local grey-level maxima in the particle. Thus, up to 1,500 cells in 10 fields of view in a soil smear are analyzed in 30 min without human intervention. Automatic counts of cell numbers and FDC were similar to visual counts in field samples. In microcosms, automatic measurements showed significant increases in cell numbers, FDC, mean cell volume, and length-to-width ratio after amendment of the soil. Volumes of fluorescent microspheres were measured with good approximation, but the absolute values obtained were strongly affected by the settings of the detector sensitivity. Independent measurements of bacterial cell numbers and volumes by image analysis and of cell carbon by a total organic carbon analyzer yielded an average specific carbon content of 200 fg of C (mu)m(sup-3), which indicates that our volume estimates are reasonable.
机译:我们描述了一种全自动图像分析系统,该系统能够测量土壤涂片中细菌的细胞数量,体积,长度和宽度。该系统还确定团聚体中的细胞数量,从而提供分裂细胞的频率(FDC)。从共聚焦激光扫描显微镜获取图像。通过卷积以及通过形态腐蚀和扩张以去除噪声来平滑灰度图像。通过淹没图像中的背景来均衡背景,然后通过两次高顶转换将其减去。最后,通过描绘使灰色图像变清晰,并检测出所有高于固定阈值的粒子。通过对粒子中局部灰度最大值的计数来确定每个检测到的粒子中的细胞数。因此,无需人工干预,即可在30分钟内分析土壤涂片中10个视野中的多达1,500个细胞。细胞数量和FDC的自动计数与现场样本中的视觉计数相似。在微观世界中,自动测量显示,土壤改良后细胞数量,FDC,平均细胞体积和长宽比显着增加。荧光微球的体积可以很好地进行测量,但是获得的绝对值受检测器灵敏度设置的强烈影响。通过图像分析对细菌细胞数量和体积进行独立测量,并通过总有机碳分析仪对细胞碳进行独立测量,得出的平均比碳含量为200 fg C(μm(sup-3)),这表明我们的体积估计是合理的。

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