Inferring cellular contractile forces and work using deep morphology traction microscopy.

Traction-force microscopy (TFM) has emerged as a widely used standard methodology to measure cell-generated traction forces and determine their role in regulating cell behavior. While TFM platforms have enabled many discoveries, their implementation remains limited due to complex experimental procedures, specialized substrates, and the ill-posed inverse problem whereby low-magnitude high-frequency noise in the displacement field severely contaminates the resulting traction measurements. Here, we introduce deep morphology traction microscopy (DeepMorphoTM), a deep-learning alternative to conventional TFM approaches. DeepMorphoTM first infers cell-induced substrate displacement solely from a sequence of cell shapes and subsequently computes cellular traction forces, thus avoiding the requirement of a specialized fiduciarily marked deformable substrate or force-free reference image. Rather, this technique drastically simplifies the overall experimental methodology, imaging, and analysis needed to conduct cell-contractility measurements. We demonstrate that DeepMorphoTM quantitatively matches conventional TFM results while offering stability against the biological variability in cell contractility for a given cell shape. Without high-frequency noise in the inferred displacement, DeepMorphoTM also resolves the ill-posedness of traction computation, increasing the consistency and accuracy of traction analysis. We demonstrate the accurate extrapolation across several cell types and substrate materials, suggesting robustness of the methodology. Accordingly, we present DeepMorphoTM as a capable yet simpler alternative to conventional TFM for characterizing cellular contractility in two dimensions.

Metabolic networks of the human gut microbiota.

The human gut microbiota controls factors that relate to human metabolism with a reach far greater than originally expected. Microbial communities and human (or animal) hosts entertain reciprocal exchanges between various inputs that are largely controlled by the host via its genetic make-up, nutrition and lifestyle. The composition of these microbial communities is fundamental to supply metabolic capabilities beyond those encoded in the host genome, and contributes to hormone and cellular signalling that support the dynamic adaptation to changes in food availability, environment and organismal development. Poor functional exchange between the microbial communities and their human host is associated with dysbiosis, metabolic dysfunction and disease. This review examines the biology of the dynamic relationship between the reciprocal metabolic state of the microbiota-host entity in balance with its environment (i.e. in healthy states), the enzymatic and metabolic changes associated with its imbalance in three well-studied diseases states such as obesity, diabetes and atherosclerosis, and the effects of bariatric surgery and exercise.

CdGAP is a talin-binding protein and a target of TGF-ß signaling that promotes HER2-positive breast cancer growth and metastasis.

Epithelial-to-mesenchymal transition (EMT) plays a crucial role in metastasis, which is the leading cause of death in breast cancer patients. Here, we show that Cdc42 GTPase-activating protein (CdGAP) promotes tumor formation and metastasis to lungs in the HER2-positive (HER2+) murine breast cancer model. CdGAP facilitates intravasation, extravasation, and growth at metastatic sites. CdGAP depletion in HER2+ murine primary tumors mediates crosstalk with a Dlc1-RhoA pathway and is associated with a transforming growth factor ß (TGF-ß)-induced EMT transcriptional signature. CdGAP is positively regulated by TGF-ß signaling during EMT and interacts with the adaptor talin to modulate focal adhesion dynamics and integrin activation. Moreover, HER2+ breast cancer patients with high CdGAP mRNA expression combined with a high TGF-ß-EMT signature are more likely to present lymph node invasion. Our results suggest CdGAP as a candidate therapeutic target for HER2+ metastatic breast cancer by inhibiting TGF-ß and integrin/talin signaling pathways.