Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

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Fiji: an open-source platform for biological-image analysis

Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).

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CellProfiler: image analysis software for identifying and quantifying cell phenotypes

https://rnajc.ucsf.edu/sites/rnajc.ucsf.edu/files/mRNA_methylation.pdf

Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons

Macrophages, which are abundant in the tumour microenvironment, enhance malignancy. At metastatic sites, a distinct population of metastasis-associated macrophages promotes the extravasation, seeding and persistent growth of tumour cells. Here we define the origin of these macrophages by showing that Gr1-positive inflammatory monocytes are preferentially recruited to pulmonary metastases but not to primary mammary tumours in mice. This process also occurs for human inflammatory monocytes in pulmonary metastases of human breast cancer cells. The recruitment of these inflammatory monocytes, which express CCR2 (the receptor for chemokine CCL2), as well as the subsequent recruitment of metastasis-associated macrophages and their interaction with metastasizing tumour cells, is dependent on CCL2 synthesized by both the tumour and the stroma. Inhibition of CCL2-CCR2 signalling blocks the recruitment of inflammatory monocytes, inhibits metastasis in vivo and prolongs the survival of tumour-bearing mice. Depletion of tumour-cell-derived CCL2 also inhibits metastatic seeding. Inflammatory monocytes promote the extravasation of tumour cells in a process that requires monocyte-derived vascular endothelial growth factor. CCL2 expression and macrophage infiltration are correlated with poor prognosis and metastatic disease in human breast cancer. Our data provide the mechanistic link between these two clinical associations and indicate new therapeutic targets for treating metastatic breast cancer.

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CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis

Stromal-epithelial interactions are of particular significance in breast tissue as misregulation of these interactions can promote tumorigenesis and invasion. Moreover, collagen-dense breast tissue increases the risk of breast carcinoma, although the relationship between collagen density and tumorigenesis is not well understood. As little is known about epithelial-stromal interactions in vivo, it is necessary to visualize the stroma surrounding normal epithelium and mammary tumors in intact tissues to better understand how matrix organization, density, and composition affect tumor formation and progression. Epithelial-stromal interactions in normal mammary glands, mammary tumors, and tumor explants in three-dimensional culture were studied with histology, electron microscopy, and nonlinear optical imaging methodologies. Imaging of the tumor-stromal interface in live tumor tissue ex vivo was performed with multiphoton laser-scanning microscopy (MPLSM) to generate multiphoton excitation (MPE) of endogenous fluorophores and second harmonic generation (SHG) to image stromal collagen. We used both laser-scanning multiphoton and second harmonic generation microscopy to determine the organization of specific collagen structures around ducts and tumors in intact, unfixed and unsectioned mammary glands. Local alterations in collagen density were clearly seen, allowing us to obtain three-dimensional information regarding the organization of the mammary stroma, such as radiating collagen fibers that could not have been obtained using classical histological techniques. Moreover, we observed and defined three tumor-associated collagen signatures (TACS) that provide novel markers to locate and characterize tumors. In particular, local cell invasion was found predominantly to be oriented along certain aligned collagen fibers, suggesting that radial alignment of collagen fibers relative to tumors facilitates invasion. Consistent with this observation, primary tumor explants cultured in a randomly organized collagen matrix realigned the collagen fibers, allowing individual tumor cells to migrate out along radially aligned fibers. The presentation of these tumor-associated collagen signatures allowed us to identify pre-palpable tumors and see cells at the tumor-stromal boundary invading into the stroma along radially aligned collagen fibers. As such, TACS should provide indications that a tumor is, or could become, invasive, and may serve as part of a strategy to help identify and characterize breast tumors in animal and human tissues.

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Collagen reorganization at the tumor-stromal interface facilitates local invasion

Wayne Rasband of NIH has created ImageJ, an open source Java-written program that is now at version 1.31 and is used for many imaging applications, including those that that span the gamut from skin analysis to neuroscience. ImageJ is in the public domain and runs on any operating system (OS). ImageJ is easy to use and can do many imaging manipulations. A very large and knowledgeable group makes up the user community for ImageJ. Topics covered are imaging abilities; cross platform; image formats support as of June 2004; extensions, including macros and plug-ins; and imaging library. NIH reports tens of thousands of downloads at a rate of about 24,000 per month currently. ImageJ can read most of the widely used and significant formats used in biomedical images. Manipulations supported are read/write of image files and operations on separate pixels, image regions, entire images, and volumes (stacks in ImageJ). Basic operations supported include convolution, edge detection, Fourier transform, histogram and particle analyses, editing and color manipulation, and more advanced operations, as well as visualization. For assistance in using ImageJ, users e-mail each other, and the user base is highly knowledgeable and will answer requests on the mailing list. A thorough manual with many examples and illustrations has been written by Tony Collins of the Wright Cell Imaging Facility at Toronto Western Research Institute and is available, along with other listed resources, via the Web.

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Sunanda J. Ram

Papers

Image processing with ImageJ