Trefoil factor 2 secreted from damaged hepatocytes activates hepatic stellate cells to induce fibrogenesis

Liver fibrosis is a common characteristic of chronic liver diseases. The activation of hepatic stellate cells (HSCs) plays a key role in fibrogenesis in response to liver injury, yet the mechanism by which damaged hepatocytes modulate the activation of HSCs is poorly understood. Our previous studies have established that liver-specific deletion of O-GlcNAc transferase (OGT)leads to hepatocyte necroptosis and spontaneous fibrosis. Here, we report that OGT-deficient hepatocytes secrete trefoil factor 2 (TFF2) that activates HSCs and contributes to the fibrogenic process. The expression and secretion of TFF2 are induced in OGT-deficient hepatocytes but not in WT hepatocytes. TFF2 activates the platelet-derived growth factor receptor beta signaling pathway that promotes the proliferation and migration of primary HSCs. TFF2 protein expression is elevated in mice with carbon tetrachloride-induced liver injury. These findings identify TFF2 as a novel factor that mediates intercellular signaling between hepatocytes and HSCs and suggest a role of the hepatic OGT–TFF2 axis in the process of fibrogenesis.     

A field guide to cultivating computational biology

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions.

Biology in the digital era requires computation and collaboration. A modern research project may include multiple model systems, use multiple assay technologies, collect varying data types, and require complex computational strategies, which together make effective design and execution difficult or impossible for any individual scientist. While some labs, institutions, funding bodies, publishers, and other educators have already embraced a team science model in computational biology and thrived [1–7], others who have not yet fully adopted it risk severely lagging behind the cutting edge. We propose a general solution: “deep integration” between biology and the computational sciences. Many different collaborative models can yield deep integration, and different problems require different approaches (Fig 1).Open in a separate windowFig 1Supporting interdisciplinary team science will accelerate biological discoveries.Scientists who have little exposure to different fields build silos, in which they perform science without external input. To solve hard problems and to extend your impact, collaborate with diverse scientists, communicate effectively, recognize the importance of core facilities, and embrace research parasitism. In biologically focused parasitism, wet lab biologists use existing computational tools to solve problems; in computationally focused parasitism, primarily dry lab biologists analyze publicly available data. Both strategies maximize the use and societal benefit of scientific data.In this article, we define computational science extremely broadly to include all quantitative approaches such as computer science, statistics, machine learning, and mathematics. We also define biology broadly, including any scientific inquiry pertaining to life and its many complications. A harmonious deep integration between biology and computer science requires action—we outline 10 immediate calls to action in this article and aim our speech directly at individual scientists, institutions, funding agencies, and publishers in an attempt to shift perspectives and enable action toward accepting and embracing computational biology as a mature, necessary, and inevitable discipline (Box 1).Box 1. Ten calls to action for individual scientists, funding bodies, publishers, and institutions to cultivate computational biology. Many actions require increased funding support, while others require a perspective shift. For those actions that require funding, we believe convincing the community of need is the first step toward agencies and systems allocating sufficient support

1. Respect collaborators’ specific research interests and motivationsProblem: Researchers face conflicts when their goals do not align with collaborators. For example, projects with routine analyses provide little benefit for computational biologists.Solution: Explicit discussion about interests/expertise/goals at project onset.Opportunity: Clearly defined expectations identify gaps, provide commitment to mutual benefit.
2. Seek necessary input during project design and throughout the project life cycleProblem: Modern research projects require multiple experts spanning the project’s complexity.Solution: Engage complementary scientists with necessary expertise throughout the entire project life cycle.Opportunity: Better designed and controlled studies with higher likelihood for success.
3. Provide and preserve budgets for computational biologists’ workProblem: The perception that analysis is “free” leads to collaborator budget cuts.Solution: When budget cuts are necessary, ensure that they are spread evenly.Opportunity: More accurate, reproducible, and trustworthy computational analyses.
4. Downplay publication author order as an evaluation metric for computational biologistsProblem: Computational biologist roles on publications are poorly understood and undervalued.Solution: Journals provide more equitable opportunities, funding bodies and institutions improve understanding of the importance of team science, scientists educate each other.Opportunity: Engage more computational biologist collaborators, provide opportunities for more high-impact work.
5. Value software as an academic productProblem: Software is relatively undervalued and can end up poorly maintained and supported, wasting the time put into its creation.Solution: Scientists cite software, and funding bodies provide more software funding opportunities.Opportunity: More high-quality maintainable biology software will save time, reduce reimplementation, and increase analysis reproducibility.
6. Establish academic structures and review panels that specifically reward team scienceProblem: Current mechanisms do not consistently reward multidisciplinary work.Solution: Separate evaluation structures to better align peer review to reward indicators of team science.Opportunity: More collaboration to attack complex multidisciplinary problems.
7. Develop and reward cross-disciplinary training and mentoringProblem: Academic labs and institutions are often insufficiently equipped to provide training to tackle the next generation of biological problems, which require computational skills.Solution: Create better training programs aligned to necessary on-the-job skills with an emphasis on communication, encourage wet/dry co-mentorship, and engage younger students to pursue computational biology.Opportunity: Interdisciplinary students uncover important insights in their own data.
8. Support computing and experimental infrastructure to empower computational biologistsProblem: Individual computational labs often fund suboptimal cluster computing systems and lack access to data generation facilities.Solution: Institutions can support centralized compute and engage core facilities to provide data services.Opportunity: Time and cost savings for often overlooked administrative tasks.
9. Provide incentives and mechanisms to share open data to empower discovery through reanalysisProblem: Data are often siloed and have untapped potential.Solution: Provide institutional data storage with standardized identifiers and provide separate funding mechanisms and publishing venues for data reuse.Opportunity: Foster new breed of researchers, “research parasites,” who will integrate multimodal data and enhance mechanistic insights.
10. Consider infrastructural, ethical, and cultural barriers to clinical data accessProblem: Identifiable health data, which include sensitive information that must be kept hidden, are distributed and disorganized, and thus underutilized.Solution: Leadership must enforce policies to share deidentifiable data with interoperable metadata identifiers.Opportunity: Derive new insights from multimodal data integration and build datasets with increased power to make biological discoveries.

     

The NSR1 gene encodes a protein that specifically binds nuclear localization sequences and has two RNA recognition motifs

We previously identified a protein (p67) in the yeast, Saccharomyces cerevisiae, that specifically recognizes nuclear localization sequences. We report here the partial purification of p67, and the isolation, sequencing, and disruption of the gene (NSR1) encoding this protein. p67 was purified using an affinity column conjugated with a peptide containing the histone H2B nuclear localization sequence from yeast. Using antibodies against p67 we have cloned the gene for this protein. The protein encoded by the NSR1 gene recognizes the wild-type H2B nuclear localization sequence, but does not recognize a mutant H2B sequence that is incompetent for nuclear localization in vivo. Interestingly, the NSR1 protein has two RNA recognition motifs, as well as an acidic NH2 terminus containing a series of serine clusters, and a basic COOH terminus containing arg-gly repeats. We have confirmed the nuclear localization of p67 by immunofluorescence and found that a restricted portion of the nucleus is highlighted. We have also shown that NSR1 (p67) is required for normal cell growth.     

Lithium Polyacrylate (LiPAA) as an Advanced Binder and a Passivating Agent for High‐Voltage Li‐Ion Batteries

Intensive studies of an advanced energy material are reported and lithium polyacrylate (LiPAA) is proven to be a surprisingly unique, multifunctional binder for high‐voltage Li‐ion batteries. The absence of effective passivation at the interface of high‐voltage cathodes in Li‐ion batteries may negatively affect their electrochemical performance, due to detrimental phenomena such as electrolyte solution oxidation and dissolution of transition metal cations. A strategy is introduced to build a stable cathode–electrolyte solution interphase for LiNi_0.5Mn_1.5O₄ (LNMO) spinel high‐voltage cathodes during the electrode fabrication process by simply using LiPAA as the cathode binder. LiPAA is a superb binder due to unique adhesion, cohesion, and wetting properties. It forms a uniform thin passivating film on LNMO and conducting carbon particles in composite cathodes and also compensates Li‐ion loss in full Li‐ion batteries by acting as an extra Li source. It is shown that these positive roles of LiPAA lead to a significant improvement in the electrochemical performance (e.g., cycle life, cell impedance, and rate capability) of LNMO/graphite battery prototypes, compared with that obtained using traditional polyvinylidene fluoride (PVdF) binder for LNMO cathodes. In addition, replacing PVdF with LiPAA binder for LNMO cathodes offers better adhesion, lower cost, and clear environmental advantages.     

Engineering surface hydrophobicity improves activity of Bacillus thermocatenulatus lipase 2 enzyme

Bacillus thermocatenulatus lipase 2 (BTL2) is a promising industrial enzyme used in biodiesel production. Although BTL2 has high thermostability and good resistance to organic solvents, the activity of BTL2 is suboptimal for industrial processes. To improve BTL2 activity, we engineered BTL2 lipase by modulating hydrophobicity of its lid domain. Through site‐directed mutagenesis, we constructed three mutants, namely Y225F+S232A, S232A+T236V and Q185L, to cover all uncharged hydrophilic amino acids within the lid domain. Activities of these mutants were characterized. Our findings suggest that one mutant (Y225F+S232A) showed ～35% activity increase in catalyzing heterogeneous hydrolytic reactions relevant for industrial applications. A mathematical framework was established to account for different molecular events that contribute to the observed apparent catalytic activities. Increases in hydrophobicity of lid domains were associated with increased interfacial adsorption of lipases and lower molecular enzymatic activities. The measured apparent activities of lipases include contributions from both events. Lid hydrophobicity can thus result in different changes in lipase activities depending on the mutation site. Our work demonstrates the feasibility of increasing BTL2 activity by modulating the hydrophobicity of lid domains and provides some guidelines for further improving BTL2 activity.     

Insect life history and the evolution of bacterial mutualism

Bacterial symbiosis has played a fundamental role in the evolution of eukaryotes. However, we still know little about how cooperative relationships with bacteria originate, and why they form in some host species but not others. Facultative symbionts that are beneficial, but not essential, provide unique insights into these processes. We use data from over a hundred aphid species to test if host life history is associated with the presence of facultative symbionts. We find that aphid species that have mutualistic associations with ants that protect them from natural enemies are less likely to carry symbionts that provide similar benefits. We also find one symbiont species occurs more frequently in unrelated aphid species that specialise on certain plant genera. In addition, aphid species that attack multiple plants often carry different symbiont complements. Our findings provide evidence of the ecological conditions that facilitate stable, mutually beneficial relationships between microbes and eukaryotic hosts.     

The Anoctamin Family Channel Subdued Mediates Thermal Nociception in Drosophila

Calcium-permeable and thermosensitive transient receptor potential (TRP) channels mediate the nociceptive transduction of noxious temperature in Drosophila nociceptors. However, the underlying molecular mechanisms are not completely understood. Here we find that Subdued, a calcium-activated chloride channel of the Drosophila anoctamin family, functions in conjunction with the thermo-TRPs in thermal nociception. Genetic analysis with deletion and the RNAi-mediated reduction of subdued show that subdued is required for thermal nociception in nociceptors. Further genetic analysis of subdued mutant and thermo-TRP mutants show that they interact functionally in thermal nociception. We find that Subdued expressed in heterologous cells mediates a strong chloride conductance in the presence of both heat and calcium ions. Therefore, our analysis suggests that Subdued channels may amplify the nociceptive neuronal firing that is initiated by thermo-TRP channels in response to thermal stimuli.     

RNA-Dependent RNA Polymerase (NIb) of the Potyviruses Is an Avirulence Factor for the Broad-Spectrum Resistance Gene Pvr4 in Capsicum annuum cv. CM334

Potyviruses are one of the most destructive viral pathogens of Solanaceae plants. In Capsicum annuum landrace CM334, a broad-spectrum gene, Pvr4 is known to be involved in resistance against multiple potyviruses, including Pepper mottle virus (PepMoV), Pepper severe mosaic virus (PepSMV), and Potato virus Y (PVY). However, a potyvirus avirulence factor against Pvr4 has not been identified. To identify the avirulence factor corresponding to Pvr4 in potyviruses, we performed Agrobacterium-mediated transient expressions of potyvirus protein coding regions in potyvirus-resistant (Pvr4) and -susceptible (pvr4) pepper plants. Hypersensitive response (HR) was observed only when a RNA-dependent RNA polymerase (NIb) of PepMoV, PepSMV, or PVY was expressed in Pvr4-bearing pepper leaves in a genotype-specific manner. In contrast, HR was not observed when the NIb of Tobacco etch virus (TEV), a virulent potyvirus, was expressed in Pvr4-bearing pepper leaves. Our results clearly demonstrate that NIbs of PepMoV, PepSMV, and PVY serve as avirulence factors for Pvr4 in pepper plants.