Graphical AbstractHighlights d The magnitude of centromere tension is sensed by the cell during mitosis d The cellular response to low metaphase tension is dose dependent in nature d The primary cellular response to low metaphase tension is detachment of kinetochores d Tension-dependent phosphorylation of the kinetochore underlies the tension response SUMMARY During mitosis, motor proteins associate with microtubules to exert pushing forces that establish a mitotic spindle. These pushing forces generate opposing tension in the chromatin that connects oppositely attached sister chromatids, which may then act as a mechanical signal to ensure the fidelity of chromosome segregation during mitosis. However, the role of tension in mitotic cellular signaling remains controversial. In this study, we generated a gradient in tension over multiple isogenic budding yeast cell lines by genetically altering the magnitude of motor-based spindle forces. We found that a decreasing gradient in tension led to an increasing gradient in the rates of kinetochore detachment and anaphase chromosome mis-segregration, and in metaphase time. Simulations and experiments indicated that these tension responses originate from a tension-dependent kinetochore phosphorylation gradient. We conclude that the cell is exquisitely tuned to the magnitude of tension as a signal to detect potential chromosome segregation errors during mitosis.

The lung changes functionally and structurally with aging. However, age-related effects on the extracellular matrix (ECM) and corresponding effects on lung cell behavior are not well understood. We hypothesized that ECM from aged animals would induce aging-related phenotypic changes in healthy inoculated cells. Decellularized whole organ scaffolds provide a powerful model for examining how ECM cues affect cell phenotype. The effects of age on ECM composition in both native and decellularized mouse lungs were assessed as was the effect of young vs old acellular ECM on human bronchial epithelial cells (hBECs) and lung fibroblasts (hLFs). Native aged (1 year) lungs demonstrated decreased expression of laminins α3 and α4, elastin and fibronectin, and elevated collagen, compared to young (3 week) lungs. Proteomic analyses of decellularized ECM demonstrated similar findings, and decellularized aged lung ECM contained less diversity in structural proteins compared to young ECM. When seeded in old ECM, hBECs and hLFs demonstrated lower gene expression of laminins α3 and α4, respectively, as compared to young ECM, paralleling the laminin deficiency of aged ECM. ECM changes appear to be important factors in potentiating aging-related phenotypes and may provide clues to mechanisms that allow for aging-related lung diseases.

In Idiopathic Pulmonary Fibrosis (IPF), there is unrelenting scarring of the lung mediated by pathological mesenchymal progenitor cells (MPCs) that manifest autonomous fibrogenicity in xenograft models. To determine where along their differentiation trajectory IPF MPCs acquire fibrogenic properties, we analyzed the transcriptome of 335 MPCs isolated from the lungs of 3 control and 3 IPF patients at the single-cell level. Using transcriptional entropy as a metric for differentiated state, we found that the least differentiated IPF MPCs displayed the largest differences in their transcriptional profile compared to control MPCs. To validate entropy as a surrogate for differentiated state functionally, we identified increased CD44 as a characteristic of the most entropic IPF MPCs. Using FACS to stratify IPF MPCs based on CD44 expression, we determined that CD44hi IPF MPCs manifested an increased capacity for anchorage-independent colony formation compared to CD44lo IPF MPCs. To validate our analysis morphologically, we used two differentially expressed genes distinguishing IPF MPCs from control (CD44, cell surface; and MARCKS, intracellular). In IPF lung tissue, pathological MPCs resided in the highly cellular perimeter region of the fibroblastic focus. Our data support the concept that IPF fibroblasts acquire a cell-autonomous pathological phenotype early in their differentiation trajectory.

Chronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer but the underlying mechanisms remain unknown. We hypothesise that the COPD stroma contains molecular mechanisms supporting tumourigenesis.We conducted an unbiased multi-omic analysis to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumour and adjacent non-malignant tissue) and those with COPD without lung cancer for profiling of proteomic and mRNA (both cytoplasmic and polyribosomal). We used the Joint and Individual Variation Explained (JIVE) method to integrate and analyse across the three datasets.JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples (tumour, adjacent and control). Predictive variables that associated with the tumour, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas predictive variables associated with adjacent tissue, compared to controls, were represented at the translatomic level. Pathway analysis revealed extracellular matrix and phosphatidylinositol-4,5-bisphosphate 3-kinase-protein kinase B signalling pathways as important signals in the tumour adjacent stroma.The multi-omic approach distinguishes tumour adjacent stroma in lung cancer and reveals two stromal expression patterns associated with cancer.

IntroductionExacerbations are a leading cause of morbidity in COPD. The objective of this study was to identify metabolomic biomarkers of acute exacerbations of COPD (AECOPD).MethodsWe measured metabolites via mass spectrometry (MS) in plasma drawn within 24 hours of admission to the hospital for 33 patients with an AECOPD (day 0) and 30 days later and for 65 matched controls. Individual metabolites were measured via selective reaction monitoring with mass spectrometry. We used a mixed-effect model to compare metabolite levels in cases compared to controls and a paired t-test to test for differences between days 0 and 30 in the AECOPD group.ResultsWe identified 377 analytes at a false discovery rate of 5% that differed between cases (day 0) and controls, and 31 analytes that differed in the AECOPD cases between day 0 and day 30 (false discovery rate: 5%). Tryptophan was decreased at day 0 of AECOPD compared to controls corresponding to an increase in indoleamine 2,3-dioxygenase activity.ConclusionPatients with AECOPD have a unique metabolomic signature that includes a decrease in tryptophan levels consistent with an increase in indoleamine 2,3-dioxygenase activity.