E-cadherin maintains the undifferentiated state of mouse spermatogonial progenitor cells via ß-catenin.

BACKGROUND: Cadherins play a pivotal role in facilitating intercellular interactions between spermatogonial progenitor cells (SPCs) and their surrounding microenvironment. Specifically, E-cadherin serves as a cellular marker of SPCs in many species. Depletion of E-cadherin in mouse SPCs showed no obvious effect on SPCs homing and spermatogenesis. RESULTS: Here, we investigated the regulatory role of E-cadherin in regulating SPCs fate. Specific deletion of E-cadherin in germ cells was shown to promote SPCs differentiation, evidencing by reduced PLZF+ population and increased c-Kit+ population in mouse testes. E-cadherin loss down-regulated the expression level of ß-catenin, leading to the reduced ß-catenin in nuclear localization for transcriptional activity. Remarkably, increasing expression level of Cadherin-22 (CDH22) appeared specifically after E-cadherin deletion, indicating CDH22 played a synergistic effect with E-cadherin in SPCs. By searching for the binding partners of ß-catenin, Lymphoid enhancer-binding factor 1 (LEF1), T-cell factor (TCF3), histone deacetylase 4 (HDAC4) and signal transducer and activator 3 (STAT3) were identified as suppressors of SPCs differentiation by regulating acetylation of differentiation genes with PLZF. CONCLUSIONS: Two surface markers of SPCs, E-cadherin and Cadherin-22, synergically maintain the undifferentiation of SPCs via the pivotal intermediate molecule ß-catenin. LEF1, TCF3, STAT3 and HDAC4 were identified as co-regulatory factors of ß-catenin in regulation of SPC fate. These observations revealed a novel regulatory pattern of cadherins on SPCs fate.

Hyperactive reactive oxygen species impair function of porcine Sertoli cells via suppression of surface protein ITGB1 and connexin-43.

Gap junctions regulate intercellular communication between Sertoli cells and germ cells in male testes and play vital functions in spermatogenesis. Many factors in animal breeding and husbandry can induce oxidative stress, which can impair the testis microenvironment and male animal fertility. However, the underlying mechanisms are largely unknown. Recently, we identified that androgen signals promote the expression of connexin-43 (Cx43), a key component of gap junctions, to regulate spermatogenesis. Thus, we asked whether hyperactive reactive oxygen species (ROS) can impair gap junctions by interfering with Cx43 in porcine testes. Using a porcine Sertoli cell in vitro system, we found that hyperactive ROS caused extensive apoptosis in Sertoli cells, remarkable decrease in Cx43 expression, and failed maintenance of co-cultured spermatogonial stem cells (SSCs), indicating that ROS impaired the function of Sertoli cells and promoted loss of SSCs. This observation provides a possible mechanism for the impact of ROS on fertility of male animals.

Androgen Indirectly Regulates Gap Junction Component Connexin 43 Through Wilms Tumor-1 in Sertoli Cells.

In mammals, spermatogenesis is closely related to intercellular interactions of germ cells and surrounding Sertoli cells, that is, blood-testis barrier and gap junction, which are subjected to hormone signals in testicular seminiferous tubules. Androgen signal plays pivotal role in regulating spermatogenesis, but the underlying mechanism is largely unknown. Our recent study demonstrated a novel regulatory pattern of androgen in regulation of spermatogonia differentiation, in which androgen indirectly regulates the expression of ITGB1 on Sertoli Cells through intermediate molecule Wilms tumor-1 (Wt-1) during spermatogenesis. In this study, we identified that Connexin 43 (Cx43), the key component for gap junction distributed between spermatogonia and Sertoli cells, was also regulated by androgen signal. Chromatin immunoprecipitation quantitative polymerase chain reaction (ChIP-qPCR) demonstrated that WT1 occupied Cx43 promoter in Sertoli cells, suggesting WT1 as an intermediate molecule in regulation of Cx43. Finally, we revealed a regulatory pattern of Cx43 by androgen in Sertoli cells, and the Sertoli cells in germ cell depleted microenvironment were sensitive to androgen signal, which enhances the understanding of the mechanism of spermatogenesis.

Large-Scale Unsupervised Hashing with Shared Structure Learning.

Hashing methods are effective in generating compact binary signatures for images and videos. This paper addresses an important open issue in the literature, i.e., how to learn compact hash codes by enhancing the complementarity among different hash functions. Most of prior studies solve this problem either by adopting time-consuming sequential learning algorithms or by generating the hash functions which are subject to some deliberately-designed constraints (e.g., enforcing hash functions orthogonal to one another). We analyze the drawbacks of past works and propose a new solution to this problem. Our idea is to decompose the feature space into a subspace shared by all hash functions and its complementary subspace. On one hand, the shared subspace, corresponding to the common structure across different hash functions, conveys most relevant information for the hashing task. Similar to data de-noising, irrelevant information is explicitly suppressed during hash function generation. On the other hand, in case that the complementary subspace also contains useful information for specific hash functions, the final form of our proposed hashing scheme is a compromise between these two kinds of subspaces. To make hash functions not only preserve the local neighborhood structure but also capture the global cluster distribution of the whole data, an objective function incorporating spectral embedding loss, binary quantization loss, and shared subspace contribution is introduced to guide the hash function learning. We propose an efficient alternating optimization method to simultaneously learn both the shared structure and the hash functions. Experimental results on three well-known benchmarks CIFAR-10, NUS-WIDE, and a-TRECVID demonstrate that our approach significantly outperforms state-of-the-art hashing methods.