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Entrepreneurship in the science-based industries is often the result of collective actions undergone by entrepreneurial groups. The origins of the biotech industry provide many examples. In the plasma protein industry, which has registered a continuous growth since 1910 and an accelerated process of mergers and acquisitions in the last decades, there are three leading corporations whose history reflects collective entrepreneurship: Baxter with headquarters in the United States (start 1931), CSL Behring in Australia (start 1916) and Grifols in Spain (start in plasma business in 1940). This article provides a historical overview of the industry and how the making of collective entrepreneurship allowed a challenger like Grifols, from a late industrialized country such as Spain, to cross entry barriers in the plasma industry, buy many of the pioneering corporations, and establish a global leadership position. This article argues that the long-term trust-based personal and professional relationships established by the entrepreneurial Spanish family lab, with managers from the US and Japanese corporations, produced a collective entrepreneurial hub of connections that made possible a long-term sustained process of innovation and globalization in a highly specialized biomedical industry.

Due to the significant role in understanding cellular processes, the decomposition of Protein-Protein Interaction (PPI) networks into essential building blocks, or complexes, has received much attention for functional bioinformatics research in recent years. One of the well-known bi-clustering descriptors for identifying communities and complexes in complex networks, such as PPI networks, is modularity function. The contribution of this paper is to introduce heuristic optimization models that can collaborate with the modularity function to improve its detection ability. The definitions of the formulated heuristics are based on nodes and different levels of their neighbor properties. The modularity function and the formulated heuristics are then injected into the mechanism of a single objective Evolutionary Algorithm (EA) tailored specifically to tackle the problem, and thus, to identify possible complexes from PPI networks. In the experiments, different overlapping scores are used to evaluate the detection accuracy in both complex and protein levels. According to the evaluation metrics, the results reveal that the introduced heuristics have the ability to harness the accuracy of the existing modularity while identifying protein complexes in the tested PPI networks.

Predicting the strength of interactions between globular proteins is a central and important topic in structural bioinformatics (Moal et al., 2013). The amino acid sequence represents the chemical bonding in a protein which, along with the solvent, dictates how it folds into an ensemble of thermally accessible states. In turn, structure specifies the strength and identity of its binding partners, by establishing the specific arrangements of intermolecular interactions and the intramolecular strain required to achieve them. ; IHM received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement PIEF-GA-2012-327899. ; Peer Reviewed ; Postprint (published version)

Predicting the strength of interactions between globular proteins is a central and important topic in structural bioinformatics (Moal et al., 2013). The amino acid sequence represents the chemical bonding in a protein which, along with the solvent, dictates how it folds into an ensemble of thermally accessible states. In turn, structure specifies the strength and identity of its binding partners, by establishing the specific arrangements of intermolecular interactions and the intramolecular strain required to achieve them. ; IHM received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement PIEF-GA-2012-327899. ; Peer Reviewed ; Postprint (published version)

Synthetic linear antimicrobial peptides with cationic α-helical structures, such as BP100, have potent and specific activities against economically important plant pathogenic bacteria. They are also recognized as valuable therapeutics and preservatives. However, highly active BP100 derivatives are often phytotoxic when expressed at high levels as recombinant peptides in plants. Here we demonstrate that production of recombinant phytotoxic peptides in transgenic plants is possible by strictly limiting transgene expression to certain tissues and conditions, and specifically that minimization of this expression during transformation and regeneration of transgenic plants is essential to obtain viable plant biofactories. On the basis of whole-genome transcriptomic data available online, we identified the Os.hsp82 promoter that fulfilled this requirement and was highly induced in response to heat shock. Using this strategy, we generated transgenic rice lines producing moderate yields of severely phytotoxic BP100 derivatives on exposure to high temperature. In addition, a threshold for gene expression in selected tissues and stages was experimentally established, below which the corresponding promoters should be suitable for driving the expression of recombinant phytotoxic proteins in genetically modified plants. In view of the growing transcriptomics data available, this approach is of interest to assist promoter selection for specific purposes ; This work was financially supported by the Spanish Ministerio de Economia y Competitividad (reference AGL2010-17181/AGR). The research group belongs to 2014SGR697, recognized by the Catalonian Government. N.C. and C.R. received fellowships from Generalitat de Catalunya

Synthetic linear antimicrobial peptides with cationic α-helical structures, such as BP100, have potent and specific activities against economically important plant pathogenic bacteria. They are also recognized as valuable therapeutics and preservatives. However, highly active BP100 derivatives are often phytotoxic when expressed at high levels as recombinant peptides in plants. Here we demonstrate that production of recombinant phytotoxic peptides in transgenic plants is possible by strictly limiting transgene expression to certain tissues and conditions, and specifically that minimization of this expression during transformation and regeneration of transgenic plants is essential to obtain viable plant biofactories. On the basis of whole-genome transcriptomic data available online, we identified the Os.hsp82 promoter that fulfilled this requirement and was highly induced in response to heat shock. Using this strategy, we generated transgenic rice lines producing moderate yields of severely phytotoxic BP100 derivatives on exposure to high temperature. In addition, a threshold for gene expression in selected tissues and stages was experimentally established, below which the corresponding promoters should be suitable for driving the expression of recombinant phytotoxic proteins in genetically modified plants. In view of the growing transcriptomics data available, this approach is of interest to assist promoter selection for specific purposes ; This work was financially supported by the Spanish Ministerio de Economia y Competitividad (reference AGL2010-17181/AGR). The research group belongs to 2014SGR697, recognized by the Catalonian Government. N.C. and C.R. received fellowships from Generalitat de Catalunya

Synthetic linear antimicrobial peptides with cationic α-helical structures, such as BP100, have potent and specific activities against economically important plant pathogenic bacteria. They are also recognized as valuable therapeutics and preservatives. However, highly active BP100 derivatives are often phytotoxic when expressed at high levels as recombinant peptides in plants. Here we demonstrate that production of recombinant phytotoxic peptides in transgenic plants is possible by strictly limiting transgene expression to certain tissues and conditions, and specifically that minimization of this expression during transformation and regeneration of transgenic plants is essential to obtain viable plant biofactories. On the basis of whole-genome transcriptomic data available online, we identified the Os.hsp82 promoter that fulfilled this requirement and was highly induced in response to heat shock. Using this strategy, we generated transgenic rice lines producing moderate yields of severely phytotoxic BP100 derivatives on exposure to high temperature. In addition, a threshold for gene expression in selected tissues and stages was experimentally established, below which the corresponding promoters should be suitable for driving the expression of recombinant phytotoxic proteins in genetically modified plants. In view of the growing transcriptomics data available, this approach is of interest to assist promoter selection for specific purposes ; This work was financially supported by the Spanish Ministerio de Economia y Competitividad (reference AGL2010-17181/AGR). The research group belongs to 2014SGR697, recognized by the Catalonian Government. N.C. and C.R. received fellowships from Generalitat de Catalunya

Abstract
Indole is a major component of the bacterial exometabolome, and the mechanisms for its wide-ranging effects on bacterial physiology are biomedically significant, although they remain poorly understood. Here, we determined how indole modulates the functions of a widely conserved motility apparatus, the bacterial flagellum. Our experiments in Escherichia coli revealed that indole influences the rotation rates and reversals in the flagellum's direction of rotation via multiple mechanisms. At concentrations higher than 1 mM, indole decreased the membrane potential to dissipate the power available for the rotation of the motor that operates the flagellum. Below 1 mM, indole did not dissipate the membrane potential. Instead, experiments and modeling indicated that indole weakens cooperative protein interactions within the flagellar complexes to inhibit motility. The metabolite also induced reversals in the rotational direction of the motor to promote a weak chemotactic response, even when the chemotaxis response regulator, CheY, was lacking. Experiments further revealed that indole does not require the transporter Mtr to cross the membrane and influence motor functions. Based on these findings, we propose that indole modulates intra- and inter-protein interactions in the cell to influence several physiological functions.

Protein-protein Interactions are involved in most fundamental biological processes, with disease causing mutations enriched at their interfaces. Here we present mCSM-PPI2, a novel machine learning computational tool designed to more accurately predict the effects of missense mutations on protein-protein interaction binding affinity. mCSM-PPI2 uses graph-based structural signatures to model effects of variations on the inter-residue interaction network, evolutionary information, complex network metrics and energetic terms to generate an optimised predictor. We demonstrate that our method outperforms previous methods, ranking first among 26 others on CAPRI blind tests. mCSM-PPI2 is freely available as a user friendly webserver at http://biosig.unimelb.edu.au/mcsm_ppi2/. ; This work was supported by the Australian Government Research Training Program Scholarship [to C.H.M.R and Y.M.]; the Jack Brockhoff Foundation [JBF 4186, 2016 to D.B.A.]; a Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) [MR/M026302/1 to D.B.A. and D.E.V.P.]; the National Health and Medical Research Council of Australia [APP1072476 to D.B.A.]; the Victorian Life Sciences Computation Initiative (VLSCI), an initiative of the Victorian Government, Australia, on its Facility hosted at the University of Melbourne [UOM0017]; the Instituto René Rachou (IRR/FIOCRUZ Minas), Brazil and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [to D.E.V.P.] and the Department of Biochemistry and Molecular Biology, University of Melbourne [to D.B.A.]. Supported in part by the Victorian Government's OIS Program.

RNA-binding proteins (RBPs) are crucial factors of post-transcriptional gene regulation and their modes of action are intensely investigated. At the center of attention are RNA motifs that guide where RBPs bind. However, sequence motifs are often poor predictors of RBP-RNA interactions in vivo. It is hence believed that many RBPs recognize RNAs as complexes, to increase specificity and regulatory possibilities. To probe the potential for complex formation among RBPs, we assembled a library of 978 mammalian RBPs and used rec-Y2H matrix screening to detect direct interactions between RBPs, sampling > 600 K interactions. We discovered 1994 new interactions and demonstrate that interacting RBPs bind RNAs adjacently in vivo. We further find that the mRNA binding region and motif preferences of RBPs deviate, depending on their adjacently binding interaction partners. Finally, we reveal novel RBP interaction networks among major RNA processing steps and show that splicing impairing RBP mutations observed in cancer rewire spliceosomal interaction networks. The dataset we provide will be a valuable resource for understanding the combinatorial interactions of RBPs with RNAs and the resulting regulatory outcomes. ; Spanish Ministry of Economy and Competitiveness (MINECO) [BFU2017-85361-P, BFU2014-54278-P, BFU2015-62550-ERC]; Spanish Ministry of Economy and Competitiveness to the EMBL partnership, 'Centro de Excelencia Severo Ochoa' [SEV-2012–0208 and SEV‐2015‐0533]; Spanish Ministry of Science and Innovation-State Research Agency (AEI), through the 'Severo Ochoa Programme for Centres of Excellence in R&D' [SEV-2015-0533 and CEX2019-000902-S]; CERCA Programme/Generalitat de Catalunya; European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie [793135 to B.L.]. Funding for open access charge: Ministerio de Economía y Competitividad. ; Peer reviewed

RNA-binding proteins (RBPs) are crucial factors of post-transcriptional gene regulation and their modes of action are intensely investigated. At the center of attention are RNA motifs that guide where RBPs bind. However, sequence motifs are often poor predictors of RBP-RNA interactions in vivo. It is hence believed that many RBPs recognize RNAs as complexes, to increase specificity and regulatory possibilities. To probe the potential for complex formation among RBPs, we assembled a library of 978 mammalian RBPs and used rec-Y2H matrix screening to detect direct interactions between RBPs, sampling > 600 K interactions. We discovered 1994 new interactions and demonstrate that interacting RBPs bind RNAs adjacently in vivo. We further find that the mRNA binding region and motif preferences of RBPs deviate, depending on their adjacently binding interaction partners. Finally, we reveal novel RBP interaction networks among major RNA processing steps and show that splicing impairing RBP mutations observed in cancer rewire spliceosomal interaction networks. The dataset we provide will be a valuable resource for understanding the combinatorial interactions of RBPs with RNAs and the resulting regulatory outcomes. ; Spanish Ministry of Economy and Competitiveness (MINECO) [BFU2017-85361-P, BFU2014-54278-P, BFU2015-62550-ERC]; Spanish Ministry of Economy and Competitiveness to the EMBL partnership, 'Centro de Excelencia Severo Ochoa' [SEV-2012–0208 and SEV‐2015‐0533]; Spanish Ministry of Science and Innovation-State Research Agency (AEI), through the 'Severo Ochoa Programme for Centres of Excellence in R&D' [SEV-2015-0533 and CEX2019-000902-S]; CERCA Programme/Generalitat de Catalunya; European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie [793135 to B.L.]. Funding for open access charge: Ministerio de Economía y Competitividad.

The increasing number of experimentally detected interactions between proteins makes it difficult for researchers to extract the interactions relevant for specific biological processes or diseases. This makes it necessary to accompany the large-scale detection of protein-protein interactions (PPIs) with strategies and tools to generate meaningful PPI subnetworks. To this end, we generated the Human Integrated Protein-Protein Interaction rEference or HIPPIE (http://cbdm.uni-mainz.de/hippie/). HIPPIE is a one-stop resource for the generation and interpretation of PPI networks relevant to a specific research question. We provide means to generate highly reliable, context-specific PPI networks and to make sense out of them. We just released the second major update of HIPPIE, implementing various new features. HIPPIE grew substantially over the last years and now contains more than 270 000 confidence scored and annotated PPIs. We integrated different types of experimental information for the confidence scoring and the construction of context-specific networks. We implemented basic graph algorithms that highlight important proteins and interactions. HIPPIE's graphical interface implements several ways for wet lab and computational scientists alike to access the PPI data. ; German Research Foundation [SCHA 1933/1-1]; Spanish Ministry of Economy and Competitiveness, 'Centro de Excelencia Severo Ochoa 2013-2017' [SEV-2012-0208]; European Union Seventh Framework Programme (FP7/2007-2013) [n° HEALTH-F4-2011-278568 (PRIMES)]; Spanish Ministerio de Economía y Competitividad [Plan Nacional BIO2012-39754]; European Fund for Regional Development (EFRD). Funding for open access charge: University of Mainz.

A. Einleitung -- B. Aufgabenstellung -- C. Theoretischer Teil -- 1. Isolierung der bei Oxydation von Wolle mit Perameisensäure in Lösung gehenden Proteinfraktionen -- 2. Isolierung der bei Oxydation von Wolle mit Peressigsäure in Lösung gehenden Proteinfraktionen -- 3. Eigenschaften der ? -Keratose -- 4. Fraktionierung der ? -Keratose -- 5. Charakterisierung einer hochgereinigten tyrosinreichen Fraktion aus ? -Keratose -- 6. Zusammenfassende Diskussion -- D. Experimenteller Teil -- 1. Allgemeines -- 2. Oxydation von Wolle -- 3. Analytische Untersuchungen -- 4. Fraktionierung der ? -Keratose -- 5. Molekulargewichtsbestimmungen an geeichten Sephadex-Säulen -- E. Anhang -- Zusammenfassung -- Danksagung -- Abbildungen -- Abkürzungen.