Background and aims Liver fibrosis is a wound-healing response that disrupts the liver architecture and function by replacing functional parenchyma with scar tissue. Recent progress has advanced our knowledge of this scarring process, but the detailed mechanism of liver fibrosis is far from clear. Methods The fibrotic specimens of patients and HLF (hepatic leukemia factor) PB/PB mice were used to assess the expression and role of HLF in liver fibrosis. Primary murine hepatic stellate cells (HSCs) and human HSC line Lx2 were used to investigate the impact of HLF on HSC activation and the underlying mechanism. Results Expression of HLF was detected in fibrotic livers of patients, but it was absent in the livers of healthy individuals. Intriguingly, HLF expression was confined to activated HSCs rather than other cell types in the liver. The loss of HLF impaired primary HSC activation and attenuated liver fibrosis in HLF PB/PB mice. Consistently, ectopic HLF expression significantly facilitated the activation of human HSCs. Mechanistic studies revealed that upregulated HLF transcriptionally enhanced interleukin 6 (IL-6) expression and intensified signal transducer and activator of transcription 3 (STAT3) phosphorylation, thus promoting HSC activation. Coincidentally, IL-6/STAT3 signalling in turn activated HLF expression in HSCs, thus completing a feedforward regulatory circuit in HSC activation. Moreover, correlation between HLF expression and alpha-smooth muscle actin, IL-6 and p-STAT3 levels was observed in patient fibrotic livers, supporting the role of HLF/IL-6/STAT3 cascade in liver fibrosis. Conclusions In aggregate, we delineate a paradigm of HLF/IL-6/STAT3 regulatory circuit in liver fibrosis and propose that HLF is a novel biomarker for activated HSCs and a potential target for antifibrotic therapy.

The HLF/IL-6/STAT3 feedforward circuit drives hepatic stellate cell activation to promote liver fibrosis.

IDPs (intrinsically disordered proteins) are highly abundant in eukaryotic proteomes and important for cellular functions, especially in cell signalling and transcriptional regulation. An IDR (intrinsically disordered region) within an IDP often undergoes disorder-to-order transitions upon binding to various partners, allowing an IDP to recognize and bind different partners at various binding interfaces. Plant-specific GRAS proteins play critical and diverse roles in plant development and signalling, and act as integrators of signals from multiple plant growth regulatory and environmental inputs. Possessing an intrinsically disordered N-terminal domain, the GRAS proteins constitute the first functionally required unfoldome from the plant kingdom. Furthermore, the N-terminal domains of GRAS proteins contain MoRFs (molecular recognition features), short interaction-prone segments that are located within IDRs and are able to recognize their interacting partners by undergoing disorder-to-order transitions upon binding to these specific partners. These MoRFs represent potential protein-protein binding sites and may be acting as molecular bait in recognition events during plant development. Intrinsic disorder provides GRAS proteins with a degree of binding plasticity that may be linked to their functional versatility. As an overview of structure-function relationships for GRAS proteins, the present review covers the main biological functions of the GRAS family, the IDRs within these proteins and their implications for understanding mode-of-action.

GRAS proteins: the versatile roles of intrinsically disordered proteins in plant signalling.

Generating stable, high-producing mammalian cell lines is a major bottleneck in the manufacture of recombinant therapeutic proteins. Conventional gene transfer methods for cell line generation rely on random plasmid integration, resulting in unpredictable and highly variable levels of transgene expression. As a consequence, a large number of stably transfected cells must be analyzed to recover a few high-producing clones. Here we present an alternative gene transfer method for cell line generation based on transgene integration mediated by the piggyBac (PB) transposon. Recombinant Chinese hamster ovary (CHO) cell lines expressing a tumor necrosis factor receptor:Fc fusion protein were generated either by PB transposition or by conventional transfection. Polyclonal populations and isolated clonal cell lines were characterized for the level and stability of transgene expression for up to 3 months in serum-free suspension culture. Pools of transposed cells produced up to fourfold more recombinant protein than did the pools generated by standard transfection. For clonal cell lines, the frequency of high-producers was greater following transposition as compared to standard transfection, and these clones had a higher volumetric productivity and a greater number of integrated transgenes than did those generated by standard transfection. In general, the volumetric productivity of the cell pools and individual cell lines generated by transposition was stable for up to 3 months in the absence of selection. Our results indicate that the PB transposon supports the generation of cell lines with high and stable transgene expression at an elevated frequency relative to conventional transfection. Thus, PB-mediated gene delivery is expected to reduce the extent of recombinant cell line screening. Biotechnol. Bioeng. 2011;108:2141–2150. © 2011 Wiley Periodicals, Inc.

The PiggyBac transposon enhances the frequency of CHO stable cell line generation and yields recombinant lines with superior productivity and stability.

As the wide popularization of online social networks, online users are not content only with keeping online friendship with social friends in real life any more. They hope the system designers can help them exploring new friends with common interest. However, the large amount of online users and their diverse and dynamic interests possess great challenges to support such a novel feature in online social networks. In this paper, by leveraging interest-based features, we design a general friend recommendation framework, which can characterize user interest in two dimensions: context (location, time) and content, as well as combining domain knowledge to improve recommending quality. We also design a potential friend recommender system in a real online social network of biology field to show the effectiveness of our proposed framework.

Potential Friend Recommendation in Online Social Network

A major biomedical challenge is the interpretation of genetic variation and the ability to design functional novel sequences. Since the space of all possible genetic variation is enormous, there is a concerted effort to develop reliable methods that can capture genotype to phenotype maps. State-of-art computational methods rely on models that leverage evolutionary information and capture complex interactions between residues. However, current methods are not suitable for a large number of important applications because they depend on robust protein or RNA alignments. Such applications include genetic variants with insertions and deletions, disordered proteins, and functional antibodies. Ideally, we need models that do not rely on assumptions made by multiple sequence alignments. Here we borrow from recent advances in natural language processing and speech synthesis to develop a generative deep neural network-powered autoregressive model for biological sequences that captures functional constraints without relying on an explicit alignment structure. Application to unseen experimental measurements of 42 deep mutational scans predicts the effect of insertions and deletions while matching state-of-art missense mutation prediction accuracies. We then test the model on single domain antibodies, or nanobodies, a complex target for alignment-based models due to the highly variable complementarity determining regions. We fit the model to a naive llama immune repertoire and generate a diverse, optimized library of 105 nanobody sequences for experimental validation. Our results demonstrate the power of the ‘alignment-free’ autoregressive model in mutation effect prediction and design of traditionally challenging sequence families.

/pdf/accelerating-protein-design-using-autoregressive-generative-34ufdqf0pa.pdf

Accelerating Protein Design Using Autoregressive Generative Models

Background
Insertional mutagenesis is an effective method for functional genomic studies in various organisms. It can rapidly generate easily tractable mutations. A large-scale insertional mutagenesis with the piggyBac (PB) transposon is currently performed in mice at the Institute of Developmental Biology and Molecular Medicine (IDM), Fudan University in Shanghai, China. This project is carried out via collaborations among multiple groups overseeing interconnected experimental steps and generates a large volume of experimental data continuously. Therefore, the project calls for an efficient database system for recording, management, statistical analysis, and information exchange.

/pdf/development-of-a-database-system-for-mapping-insertional-cvk2hg6jtg.pdf

Development of a database system for mapping insertional mutations onto the mouse genome with large-scale experimental data.

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Development of a database system for mapping insertional mutations onto the mouse genome with large-scale experimental data.