A novel bioreactor for combined magnetic resonance spectroscopy and optical imaging of metabolism in 3D cell cultures.

PURPOSE: Fluorescence lifetime imaging microscopy (FLIM) of endogenous fluorescent metabolites permits the measurement of cellular metabolism in cell, tissue and animal models. In parallel, magnetic resonance spectroscopy (MRS) of dynamic nuclear (hyper)polarized (DNP) 13 C-pyruvate enables measurement of metabolism at larger in vivo scales. Presented here are the design and initial application of a bioreactor that connects these 2 metabolic imaging modalities in vitro, using 3D cell cultures. METHODS: The model fitting for FLIM data analysis and the theory behind a model for the diffusion of pyruvate into a collagen gel are detailed. The device is MRI-compatible, including an optical window, a temperature control system and an injection port for the introduction of contrast agents. Three-dimensional printing, computer numerical control machining and laser cutting were used to fabricate custom parts. RESULTS: Performance of the bioreactor is demonstrated for 4 T1 murine breast cancer cells under glucose deprivation. Mean nicotinamide adenine dinucleotide (NADH) fluorescence lifetimes were 10% longer and hyperpolarized 13 C lactate:pyruvate (Lac:Pyr) ratios were 60% lower for glucose-deprived 4 T1 cells compared to 4 T1 cells in normal medium. Looking at the individual components of the NADH fluorescent lifetime, τ1 (free NADH) showed no significant change, while τ2 (bound NADH) showed a significant increase, suggesting that the increase in mean lifetime was due to a change in bound NADH. CONCLUSION: A novel bioreactor that is compatible with, and can exploit the benefits of, both FLIM and 13 C MRS in 3D cell cultures for studies of cell metabolism has been designed and applied.

Directional cues in the tumor microenvironment due to cell contraction against aligned collagen fibers.

It is well established that collagen alignment in the breast tumor microenvironment provides biophysical cues to drive disease progression. Numerous mechanistic studies have demonstrated that tumor cell behavior is driven by the architecture and stiffness of the collagen matrix. However, the mechanical properties within a 3D collagen microenvironment, particularly at the scale of the cell, remain poorly defined. To investigate cell-scale mechanical cues with respect to local collagen architecture, we employed a combination of intravital imaging of the mammary tumor microenvironment and a 3D collagen gel system with both acellular pNIPAAm microspheres and MDA-MB-231 breast carcinoma cells. Within the in vivo tumor microenvironment, the displacement of collagen fiber was identified in response to tumor cells migrating through the stromal matrix. To further investigate cell-scale stiffness in aligned fiber architectures and the propagation of cell-induced fiber deformations, precise control of collagen architecture was coupled with innovative methodology to measure mechanical properties of the collagen fiber network. This method revealed up to a 35-fold difference in directional cell-scale stiffness resulting from contraction against aligned fibers. Furthermore, the local anisotropy of the matrix dramatically altered the rate at which contractility-induced fiber displacements decayed over distance. Together, our results reveal mechanical properties in aligned matrices that provide dramatically different cues to the cell in perpendicular directions. These findings are supported by the mechanosensing behavior of tumor cells and have important implications for cell-cell communication within the tissue microenvironment. STATEMENT OF SIGNIFICANCE: It is widely appreciated that the architecture of the extracellular matrix impacts cellular behavior in normal and disease states. Numerous studies have determined the fundamental role of collagen matrix architecture on cellular mechanosensing, but effectively quantifying anisotropic mechanical properties of the collagen matrix at the cell-scale remains challenging. Here, we developed innovative methodology to discover that collagen alignment results in a 35-fold difference in cell-scale stiffness and alters contractile force transmission through the fiber network. Furthermore, we identified bias in cell response along the axis of alignment, where local stiffness is highest. Overall, our results define cell-scale stiffness and fiber deformations due to collagen architecture that may instruct cell communication within a broad range of tissue microenvironments.

Reduced synchroneity of intra-islet Ca2+ oscillations in vivo in Robo-deficient ß cells.

The spatial architecture of the islets of Langerhans is hypothesized to facilitate synchronized insulin secretion among ß cells, yet testing this in vivo in the intact pancreas is challenging. Robo ßKO mice, in which the genes Robo1 and Robo2 are deleted selectively in ß cells, provide a unique model of altered islet spatial architecture without loss of ß cell differentiation or islet damage from diabetes. Combining Robo ßKO mice with intravital microscopy, we show here that Robo ßKO islets have reduced synchronized intra-islet Ca2+ oscillations among ß cells in vivo. We provide evidence that this loss is not due to a ß cell-intrinsic function of Robo, mis-expression or mis-localization of Cx36 gap junctions, or changes in islet vascularization or innervation, suggesting that the islet architecture itself is required for synchronized Ca2+ oscillations. These results have implications for understanding structure-function relationships in the islets during progression to diabetes as well as engineering islets from stem cells.

Targeted matrisome analysis identifies thrombospondin-2 and tenascin-C in aligned collagen stroma from invasive breast carcinoma.

Increasing evidence demonstrates an important role for the extracellular matrix (ECM) in breast cancer progression. Collagen type I, a core constituent of the fibrous ECM, undergoes a significant set of changes that accompany tumor progression, termed Tumor Associated Collagen Signatures (TACS). Late stages of this progression are characterized by the presence of bundled, straight collagen (TACS-2) that become oriented perpendicular to the tumor-stromal boundary (TACS-3). Importantly, the presence of TACS-3 collagen is an independent predictor of poor patient outcome. At present, it remains unclear whether reorganization of the collagen matrix is the consequence of mechanical or compositional tissue remodeling. Here, we identify compositional changes in ECM correlating to collagen fiber reorganization from nineteen normal and invasive ductal carcinoma (IDC) patient biopsies using matrisome-targeted proteomics. Twenty-seven ECM proteins were significantly altered in IDC samples compared to normal tissue. Further, a set of nineteen matrisome proteins positively correlate and five proteins inversely correlate with IDC tissues containing straightened collagen fibers. Tenascin-C and thrombospondin-2 significantly co-localized with aligned collagen fibers in IDC tissues. This study highlights the compositional change in matrisome proteins accompanying collagen re-organization during breast cancer progression and provides candidate proteins for investigation into cellular and structural influences on collagen alignment.

In Vivo Visualization of Stromal Macrophages via label-free FLIM-based metabolite imaging.

Macrophage infiltration and recruitment in breast tumors has been correlated with poor prognosis in breast cancer patients and has been linked to tumor cell dissemination. Much of our understanding comes from animal models in which macrophages are labeled by expression of an extrinsic fluorophore. However, conventional extrinsic fluorescence labeling approaches are not readily applied to human tissue and clinical use. We report a novel strategy that exploits endogenous fluorescence from the metabolic co-factors NADH and FAD with quantitation from Fluorescence Lifetime Imaging Microscopy (FLIM) as a means to non-invasively identify tumor-associated macrophages in the intact mammary tumor microenvironment. Macrophages were FAD(HI) and demonstrated a glycolytic-like NADH-FLIM signature that was readily separated from the intrinsic fluorescence signature of tumor cells. This non-invasive quantitative technique provides a unique ability to discern specific cell types based upon their metabolic signatures without the use of exogenous fluorescent labels. Not only does this provide high resolution temporal and spatial views of macrophages in live animal breast cancer models, this approach can be extended to other animal disease models where macrophages are implicated and has potential for clinical applications.

Advanced Intestinal Cancers often Maintain a Multi-Ancestral Architecture.

A widely accepted paradigm in the field of cancer biology is that solid tumors are uni-ancestral being derived from a single founder and its descendants. However, data have been steadily accruing that indicate early tumors in mice and humans can have a multi-ancestral origin in which an initiated primogenitor facilitates the transformation of neighboring co-genitors. We developed a new mouse model that permits the determination of clonal architecture of intestinal tumors in vivo and ex vivo, have validated this model, and then used it to assess the clonal architecture of adenomas, intramucosal carcinomas, and invasive adenocarcinomas of the intestine. The percentage of multi-ancestral tumors did not significantly change as tumors progressed from adenomas with low-grade dysplasia [40/65 (62%)], to adenomas with high-grade dysplasia [21/37 (57%)], to intramucosal carcinomas [10/23 (43%]), to invasive adenocarcinomas [13/19 (68%)], indicating that the clone arising from the primogenitor continues to coexist with clones arising from co-genitors. Moreover, neoplastic cells from distinct clones within a multi-ancestral adenocarcinoma have even been observed to simultaneously invade into the underlying musculature [2/15 (13%)]. Thus, intratumoral heterogeneity arising early in tumor formation persists throughout tumorigenesis.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer.

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.