Intraluminal vesicles of multivesicular endosomes are either sorted for cargo degradation into lysosomes or secreted as exosomes into the extracellular milieu. The mechanisms underlying the sorting of membrane into the different populations of intraluminal vesicles are unknown. Here, we find that cargo is segregated into distinct subdomains on the endosomal membrane and that the transfer of exosome-associated domains into the lumen of the endosome did not depend on the function of the ESCRT (endosomal sorting complex required for transport) machinery, but required the sphingolipid ceramide. Purified exosomes were enriched in ceramide, and the release of exosomes was reduced after the inhibition of neutral sphingomyelinases. These results establish a pathway in intraendosomal membrane transport and exosome formation.

Oligodendrocytes secrete vesicles into the extracellular space, where they might play a role in neuron–glia communication. These exosomes are small vesicles with a diameter of 50–100 nm that are formed within multivesicular bodies and are released after fusion with the plasma membrane. The intracellular pathways that generate exosomes are poorly defined. Because Rab family guanosine triphosphatases (GTPases) together with their regulators are important membrane trafficking organizers, we investigated which Rab GTPase-activating proteins interfere with exosome release. We find that TBC1D10A–C regulate exosome secretion in a catalytic activity–dependent manner. We show that Rab35 is the target of TBC1D10A–C and that the inhibition of Rab35 function leads to intracellular accumulation of endosomal vesicles and impairs exosome secretion. Rab35 localizes to the surface of oligodendroglia in a GTP-dependent manner, where it increases the density of vesicles, suggesting a function in docking or tethering. These findings provide a basis for understanding the biogenesis and function of exosomes in the central nervous system.

The estrogen receptor-α (ERα) determines the phenotype of breast cancers where it serves as a positive prognostic indicator. ERα is a well-established target for breast cancer therapy, but strategies to target its function remain of interest to address therapeutic resistance and further improve treatment. Recent findings indicate that proteasome inhibition can regulate estrogen-induced transcription, but how ERα function might be regulated was uncertain. In this study, we investigated the transcriptome-wide effects of the proteasome inhibitor bortezomib on estrogen-regulated transcription in MCF7 human breast cancer cells and showed that bortezomib caused a specific global decrease in estrogen-induced gene expression. This effect was specific because gene expression induced by the glucocorticoid receptor was unaffected by bortezomib. Surprisingly, we observed no changes in ERα recruitment or assembly of its transcriptional activation complex on ERα target genes. Instead, we found that proteasome inhibition caused a global decrease in histone H2B monoubiquitination (H2Bub1), leading to transcriptional elongation defects on estrogen target genes and to decreased chromatin dynamics overall. In confirming the functional significance of this link, we showed that RNA interference–mediated knockdown of the H2B ubiquitin ligase RNF40 decreased ERα-induced gene transcription. Surprisingly, RNF40 knockdown also supported estrogen-independent cell proliferation and activation of cell survival signaling pathways. Most importantly, we found that H2Bub1 levels decrease during tumor progression. H2Bub1 was abundant in normal mammary epithelium and benign breast tumors but absent in most malignant and metastatic breast cancers. Taken together, our findings show how ERα activity is blunted by bortezomib treatment as a result of reducing the downstream ubiquitin-dependent function of H2Bub1. In supporting a tumor suppressor role for H2Bub1 in breast cancer, our findings offer a rational basis to pursue H2Bub1-based therapies for future management of breast cancer. Cancer Res; 71(17); 5739–53. ©2011 AACR.

Bistability plays an important role in cellular memory and cell-fate determination. A positive feedback loop can generate bistability if it contains ultrasensitive molecular reactions. It is often difficult to detect bistability based on such molecular mechanisms due to its intricate interaction with cellular growth. We constructed transcriptional feedback loops in yeast. To eliminate growth alterations, we reduced the protein levels of the transcription factors by tuning the translation rates over two orders of magnitude with designed RNA stem loops. We modulated two ultrasensitive reactions, homodimerization and the cooperative binding of the transcription factor to the promoter. Either of them is sufficient to generate bistability on its own, and when acting together, a particularly robust bistability emerges. This bistability persists even in the presence of a negative feedback loop. Given that protein homodimerization is ubiquitous, it is likely to play a major role in the behavior of regulatory networks.

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit.

Alternative cell fates represent a form of non-genetic diversity, which can promote adaptation and functional specialization. It is difficult to predict the rate of the transition between two cell fates due to the strong effect of noise on feedback loops and missing parameters. We opened synthetic positive feedback loops experimentally to obtain open-loop functions. These functions allowed us to identify a deterministic model of bistability by bypassing noise and the requirement to resolve individual processes in the loop. Combining the open-loop function with kinetic measurements and reintroducing the measured noise, we were able to predict the transition rates for the feedback systems without parameter tuning. Noise in gene expression was the key determinant of the transition rates inside the bistable range. Transitions between two cell fates were also observed outside of the bistable range, evidenced by bimodality and hysteresis. In this case, a slow transient process was the rate-limiting step in the transitions. Thus, feedback opening is an effective approach to identify the determinants of cell fate transitions and to predict their rates.