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Selenocysteine (Sec), the 21stamino acid specified by the genetic code, is a rare selenium-containing residue found in the catalytic site of selenoprotein oxidoreductases. Sec is analogous to the common cysteine (Cys) amino acid but its selenium atom offers physicalchemical properties not provided by the corresponding sulfur atom in Cys. Catalytic sites with Sec in selenoproteins of vertebrates are under strong purifying selection but one enzyme, Glutathione Peroxidase 6 (GPX6), independently exchanged Sec for Cys less than one hundred million years ago in several mammalian lineages. We reconstructed and assayed these ancient enzymes before and after Sec was lost and up to today, and found them to have lost their classic ability to reduce hydroperoxides using glutathione (GSH). This loss of function, however, was accompanied by bursts of amino acid changes in the catalytic domain, with protein sites concertedly changing under positive selection across distant lineages abandoning Sec in GPX6. This demonstrates that when sulfur in Cys impairs catalysis a narrow evolutionary path is followed, with epistasis and pleiotropy leading to convergent evolution and triggering enzymatic properties likely beyond those in classic GPXs. These findings are an unusual example of adaptive convergence towards unexplored oxidoreductase functions during mammalian evolution.

Multisubunit Tethering Complexes (MTCs) are a set of conserved protein complexes that tether vesicles at the acceptor membrane. Interactions with other components of the trafficking machinery regulate MTCs through mechanisms that are partially understood. Here, we systematically investigate the interactome that regulates MTCs. We report that P4-ATPases, a family of lipid flippases, interact with MTCs that participate in the anterograde and retrograde transport at the Golgi, such as TRAPPIII. We use the P4-ATPase Drs2 as a paradigm to investigate the mechanism and biological relevance of this interplay during transport of Atg9 vesicles. Binding of Trs85, the sole-specific subunit of TRAPPIII, to the N-terminal tail of Drs2 stabilizes TRAPPIII on membranes loaded with Atg9 and is required for Atg9 delivery during selective autophagy, a role that is independent of P4-ATPase canonical functions. This mechanism requires a conserved I(S/R)TTK motif that also mediates the interaction of the P4-ATPases Dnf1 and Dnf2 with MTCs, suggesting a broader role of P4-ATPases in MTC regulation. OG was funded by research grants from the Spanish funding agency (PGC2018-095745-B-I00, EUR2019-103815 and PID2021-127773NB-I00/FEDER UE and supported by the “Unidad de Excelencia María de Maeztu” (ref: MDM-2014-0370) funded by the MCIN/AEI/10.13039/501100011033) and a Research Grant from HFSP (ref: RGP0017/2020). The proteomics analyses were performed in the CRG/UPF Proteomics Unit which is part of the of Proteored, PRB3 and is supported by grant PT17/0019, of the PE I + D + i 2013-2016, funded by ISCIII and ERDF. We thank Josep Vilardell, Bernat Crosas, Amy Curwin, Vivek Malhotra, Michael Knop, Marko Kaksonen, Kenji Maeda, Manuel García-Muñiz and Charles Boone for providing devices, reagents, strains and plasmids. We thank the Advanced Digital Microscopy Core Facility (ADMCF), the Biostatistics/Bioinformatics and the Mass Spectrometry and Proteomics facilities of the IRB Barcelona for live-cell imaging, technical support and also sharing devices with us. We thank Simona Barankova, Radovan Dojcilovic and Daniel Castaño-Díez for fruitful discussions. We thank Raúl Méndez and Ignasi Fita for their support and mentoring during these years. IP was supported by FPI awarded by the Spanish Ministry of Economy and Competitiveness (MINECO) (ref: BES-2013-063945) and EMBO Short-Term Fellowship 7076.

Protein citrullination (deimination) is the post-translational modification of arginine to the non-coded amino acid citrulline and is catalyzed by the peptidyl arginine deiminase (PADI) enzyme family. The most widely expressed of the PADIs family, PADI2, regulates cellular processes that impact several diseases. How PADI2 has evolved in mammals to gain its fundamental function is not fully understood. By performing a systematic evolutionary analysis, we now identify 20 positively selected residues in PADI2, 16 of which are structurally exposed mainly on the N-terminal and middle domains of PADI2. Our integrated evolutionary and structural analyses suggest that these residues have roles in maintaining the PADI2 interactions with cognate proteins. We experimentally demonstrate that one of the loops in the middle domain participates in the interactions of PADI2 with the positive-transcription elongation factor (P-TEFb), which is essential for active transcription and cellular proliferation. This interpretation is supported by our finding that L162 within this loop evolved under positive selection. Our work demonstrates the power of combining sequence-based phylogenetic methods with structural information for investigating the selective function of the middle domain of PADI2 in modulating transcription. This in-depth knowledge could be key to understanding the role of PADI2 overexpression in disease and points to potential targetable regions of the protein.Significance StatementA systematic evolutionary analysis identified positively selected residues in the non-catalytic domain of PADI2. We established a link between the positive evolution of key residues in the PADI2 and their role in transcription. Specifically, we identified the structurally exposed loop encompassing the positively selected L162 in the PADI2 middle domain and its role in transcription and cellular proliferation. This loop contributes to the PADI2 interaction with the P-TEFb complex and cellular proliferation. Our results showcase the use of combining evolutionary and experimental approaches to dissect the dynamic of evolutionary processes.

RNA-binding proteins (RBPs) have been relatively overlooked in cancer research despite their contribution to virtually every cancer hallmark. Here, we use RNA interactome capture (RIC) to characterize the melanoma RBPome and uncover novel RBPs involved in melanoma progression. Comparison of RIC profiles of a non-tumoral versus a metastatic cell line revealed prevalent changes in RNA-binding capacities that were not associated with changes in RBP levels. Extensive functional validation of a selected group of 24 RBPs using five different in vitro assays unveiled unanticipated roles of RBPs in melanoma malignancy. As proof-of-principle we focused on PDIA6, an ER-lumen chaperone that displayed a novel RNA-binding activity. We show that PDIA6 is involved in metastatic progression, map its RNA-binding domain, and find that RNA binding is required for PDIA6 tumorigenic properties. These results exemplify how RIC technologies can be harnessed to uncover novel vulnerabilities of cancer cells. N.M. was supported by an FPI fellowship from the Ministry of Economy and Competitiveness; F.G. was supported by national grants BFU2015-68741-P from MINECO, PGC2018-099697-B-I00 from MICINN, ‘la Caixa’ Foundation [100010434] under the agreement LCF/PR/HR17/52150016, Marató-TV3 Foundation [20131430]; Catalan Agency for Research and Universities [2017SGR534]; CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is member of ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I + D + i 2013–2016 from the Instituto de Salud Carlos III (ISCIII), ERDF, and ‘Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya’ [2017SGR595]. A.C. is funded by the MRC Career Development Award (MR/L019434/1) and the ERC Consolidator 101001634 vRNP-capture. We acknowledge the support of the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033), and the Generalitat de Catalunya through the CERCA Programme. Funding for open access charge: MINECO [PGC2018-099697-B-I00].

Around 3–7% of patients with non-small cell lung cancer (NSCLC), which represent 85% of diagnosed lung cancers, have a rearrangement in the ALK gene that produces an abnormal activity of the ALK protein cell signaling pathway. The developed ALK tyrosine kinase inhibitors (TKIs), such as crizotinib, ceritinib, alectinib, brigatinib and lorlatinb present good performance treating ALK+ NSCLC, although all patients invariably develop resistance due to ALK secondary mutations or bypass mechanisms. In the present study, we compare the potential differences between brigatinib and alectinib’s mechanisms of action as first-line treatment for ALK+ NSCLC in a systems biology-based in silico setting. Therapeutic performance mapping system (TPMS) technology was used to characterize the mechanisms of action of brigatinib and alectinib and the impact of potential resistances and drug interferences with concomitant treatments. The analyses indicate that brigatinib and alectinib affect cell growth, apoptosis and immune evasion through ALK inhibition. However, brigatinib seems to achieve a more diverse downstream effect due to a broader cancer-related kinase target spectrum. Brigatinib also shows a robust effect over invasiveness and central nervous system metastasis-related mechanisms, whereas alectinib seems to have a greater impact on the immune evasion mechanism. Based on this in silico head to head study, we conclude that brigatinib shows a predicted efficacy similar to alectinib and could be a good candidate in a first-line setting against ALK+ NSCLC. Future investigation involving clinical studies will be needed to confirm these findings. These in silico systems biology-based models could be applied for exploring other unanswered questions.

Pathogenic RIPK1 variants have been described as the cause of two different inborn errors of immunity. Biallelic loss-of-function variants cause the recessively inherited RIPK1 deficiency, while monoallelic variants impairing the caspase-8-mediated RIPK1 cleavage provoke a novel autoinflammatory disease (AID) called cleavage-resistant RIPK1-induced autoinflammatory (CRIA) syndrome. The aim of this study was to characterize the pathogenicity of two novel RIPK1 variants located at the cleavage site of caspase-8 detected in patients with dominantly-inherited, early-onset undefined AID. RIPK1 genotyping was performed by Sanger and next-generation sequencing. Clinical and analytical data were collected from medical charts, and in silico and in vitro assays were performed to evaluate the functional consequences. Genetic analyses identified two novel heterozygous RIPK1 variants at the caspase-8 cleavage site (p.Leu321Arg and p.Asp324Gly), which displayed a perfect intrafamilial phenotype-genotype segregation following a dominant inheritance pattern. Structural analyses suggested that these variants disrupt the normal RIPK1 structure, probably making it less accessible to and/or less cleavable by caspase-8. In vitro experiments confirmed that the p.Leu321Arg and p.Asp324Gly RIPK1 variants were resistant to caspase-8-mediated cleavage and induced a constitutive activation of necroptotic pathway in a similar manner that previously characterized RIPK1 variants causing CRIA syndrome. All these results strongly supported the pathogenicity of the two novel RIPK1 variants and the diagnosis of CRIA syndrome in all enrolled patients. Moreover, the evidences here collected expand the phenotypic and genetic diversity of this recently described AID, and provide interesting data about effectiveness of treatments that may benefit future patients. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work has been partially funded by the following: Grants from the Spanish Ministry of Science, Innovation and Universities and co-funded by the European Regional Development Fund / Agencia Estatal de Investigación: RTI2018-096824-B-C21 (JIA); RTI2018-096824-B-C22 (FC); SAF2017-88276-R (PP). Grant from the Spanish Ministry of Science and Innovation / Agencia Estatal de Investigación (10.13039/501100011033): PID2020-116709RB-I00 (PP). Grant from Instituto de Salud Carlos III and co-funded by the European Union: PI19/01567 (AM-V). Grants from Fundación Séneca: 20859/PI/18 (PP); 21081/PDC/19 (PP); 0003/COVI/20 (PP). Grants from European Research Council: ERC-2013-CoG 614578 (PP); ERC-2019-PoC 899636 (PP)

Alzheimer's disease and Type 2 diabetes are pathological processes associated to ageing. Moreover, there are evidences supporting a mechanistic link between Alzheimer's disease and insulin resistance (one of the first hallmarks of Type 2 diabetes). Regarding Alzheimer's disease, amyloid β-peptide aggregation into β-sheets is the main hallmark of Alzheimer's disease. At monomeric state, amyloid β-peptide is not toxic but its function in brain, if any, is unknown. Here we show, by in silico study, that monomeric amyloid β-peptide 1-40 shares the tertiary structure with insulin and is thereby able to bind and activate insulin receptor. We validated this prediction experimentally by treating human neuroblastoma cells with increasing concentrations of monomeric amyloid β-peptide 1-40. Our results confirm that monomeric amyloid β-peptide 1-40 activates insulin receptor autophosphorylation, triggering downstream enzyme phosphorylations and the glucose Transporter 4 translocation to the membrane. On the other hand, neuronal insulin resistance is known to be associated to Alzheimer's disease since early stages. We thus modelled the docking of oligomeric amyloid β-peptide 1-40 to insulin receptor. We found that oligomeric amyloid β-peptide 1-40 blocks insulin receptor, impairing its activation. It was confirmed in vitro by observing the lack of insulin receptor autophosphorylation, and also the impairment of insulin-induced intracellular enzyme activations and the glucose Transporter 4 translocation to the membrane. By biological system analysis, we have carried out a mathematical model recapitulating the process that turns amyloid β-peptide binding to insulin receptor from the physiological to the pathophysiological regime. Our results suggest that monomeric amyloid β-peptide 1-40 contributes to mimic insulin effects in the brain, which could be good when neurons have an extra requirement of energy beside the well-known protective effects on insulin intracellular signalling, while its accumulation and subsequent oligomerization blocks the insulin receptor producing insulin resistance and compromising neuronal metabolism and protective pathways. This work was supported by the Spanish Ministry of Science and Innovation and Agencia Estatal de Investigación plus European Regional Development Fund (FEDER Funds) through grants PID2020-117691RB-I00/AEI/10.13039/501100011033 (F.J.M.), SAF2017-83372-R (F.J.M.), BIO2017-85329-R (B.O.), PGC2018-101251-B-I00 (J.G.-O.) and RTI2018-094579-B-I00 (X.F.-B.). This work was also funded by the Spanish Institute of Health Carlos III by project reference AC20/00009 -FEDER/UE and European Research Era Net (ERANET) ERA-CVD_JTC2020-015 (J.G.-O.), by the ‘María de Maeztu Programme’ for Units of Excellence in Research and Development (R&D; award CEX2018-000792-M), Generalitat de Catalunya (Spain) through the grant 2017-SGR-908 (X.F.-B.) and Fundación QUAES through Cátedra QUAES-UPF de Biomedicina e Ingeniería Biomédica. The Instituto de Salud Global de Barcelona (ISGlobal) and Institute for Bioengineering of Catalonia (IBEC) are members of the Centres de Recerca de Catalunya (CERCA) Programme, Generalitat de Catalunya (Spain). We acknowledge support from the Spanish Ministry of Science, Innovation and Universities through the ‘Centro de Excelencia Severo Ochoa 2019–2023’ Programme (CEX2018-000806-S). This research is part of ISGlobal's Programme on the Molecular Mechanisms of Malaria, which is partially supported by the Fundación Ramón Areces. J.G.-O. also acknowledges support from the Institució Catalana de Recerca i Estudis Avançats (ICREA) Academia programme.

While multiple technologies for small allele genome editing exist, robust technologies for targeted integration of large DNA fragments in mammalian genomes are still missing. Here we develop a gene delivery tool (FiCAT) combining the precision of a CRISPR-Cas9 (find module), and the payload transfer efficiency of an engineered piggyBac transposase (cut-and-transfer module). FiCAT combines the functionality of Cas9 DNA scanning and targeting DNA, with piggyBac donor DNA processing and transfer capacity. PiggyBac functional domains are engineered providing increased on-target integration while reducing off-target events. We demonstrate efficient delivery and programmable insertion of small and large payloads in cellulo (human (Hek293T, K-562) and mouse (C2C12)) and in vivo in mouse liver. Finally, we evolve more efficient versions of FiCAT by generating a targeted diversity of 394,000 variants and undergoing 4 rounds of evolution. In this work, we develop a precise and efficient targeted insertion of multi kilobase DNA fragments in mammalian genomes., Mammalian genome engineering has advanced tremendously over the last decade, however there is still a need for robust gene writing with size scaling capacity. Here the authors present Find Cut-and-Transfer (FiCAT) technology to delivery large targeted payload insertion in cell lines and in vivo in mouse models.

Objective: Autoinflammatory diseases are inherited disorders of innate immunity that usually start during childhood. However, several recent reports have described an increasing number of patients with autoinflammatory disease starting in adulthood. This study was undertaken to investigate the underlying cause of a case of late-onset uncharacterized autoinflammatory disease. Methods: Genetics studies were performed using Sanger sequencing and next-generation sequencing (NGS) methods. In silico, in vitro, and ex vivo analyses were performed to determine the functional consequences of the detected variant. Results: We studied a 57-year-old woman who at the age of 47 years began to have recurrent episodes of fever, myalgias, arthralgias, diffuse abdominal pain, diarrhea, adenopathies, and systemic inflammation, which were relatively well controlled with anti-interleukin-1 (anti-IL-1) drugs. NGS analyses did not detect germline variants in any of the known autoinflammatory disease-associated genes, but they identified the p.Ser171Phe NLRC4 variant in unfractionated blood, with an allele fraction (2-4%) compatible with gene mosaicism. Structural modeling analyses suggested that this missense variant might favor the open, active conformation of the NLRC4 protein, and in vitro and ex vivo analyses confirmed its propensity to oligomerize and activate the NLRC4 inflammasome, with subsequent overproduction of IL-18. Conclusion: Our findings indicate that the postzygotic p.Ser171Phe NLRC4 variant is a plausible cause of the disease in the enrolled patient. Functional and structural studies clearly support, for the first time, its gain-of-function behavior, consistent with previously reported NLRC4 pathogenic variants. These novel findings should be considered in the diagnostic evaluation of patients with adult-onset uncharacterized autoinflammatory disease.

The enormous mammal’s lifespan variation is the result of each species’ adaptations to their own biological trade-offs and ecological conditions. Comparative genomics have demonstrated that genomic factors underlying both, species lifespans and longevity of individuals, are in part shared across the tree of life. Here, we compared protein-coding regions across the mammalian phylogeny to detect individual amino acid (AA) changes shared by the most long-lived mammals and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 AA in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (P = 0.003). These genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 AA showed a significant association with maximum lifespan in a phylogenetic test. Interestingly, most of the detected AA positions do not vary in extant human populations (81.2%) or have allele frequencies below 1% (99.78%). Consequently, almost none of these putatively important variants could have been detected by genome-wide association studies. Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected, successfully demonstrating for the first time that comparative genomics can be used to enhance interpretation of human genome-wide association studies. Finally, we show that the human longevity-associated proteins are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan., This work was supported by AEI-PGC2018-101927-BI00 (FEDER/UE), the Spanish National Institute of Bioinformatics of the Instituto de Salud Carlos III (PT17/0009/0020), FEDER (Fondo Europeo de Desarrollo Regional)/FSE (Fondo Social Europeo), “Unidad de Excelencia María de Maeztu,” funded by the AEI (CEX2018-000792-M) and Secretaria d’Universitats i Recerca and CERCA Programme del Departament d’Economia i Coneixement de la Generalitat de Catalunya (GRC 2017 SGR 880)., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2018-000792-M).

Mammals vary 100-fold in their maximum lifespan. This enormous variation is the result of the adaptations of each species to their own biological trade-offs and ecological conditions. Comparative genomics studies have demonstrated that the genomic factors underlying the lifespans of species and the longevity of individuals are shared across the tree of life. Here, we set out to compare protein-coding regions across the mammalian phylogeny, aiming to detect individual amino acid changes shared by the most long-lived mammal species and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 amino acid changes in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p=0.003). The detected genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 amino acids, located in 996 different genes, showed a significant association with maximum lifespan in a phylogenetically controlled test. Interestingly, most of the detected amino acids positions do not vary in extant human populations (>81.2%) or have allele frequencies below 1% (99.78%), Consequently, almost none could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected by chance, successfully demonstrating for the first time that comparative genomics can be used to enhance the interpretation of human GWAS. Finally, we show that the human longevity-associated proteins coded by the detected genes are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

The highly conserved 5’–3’ exonuclease Xrn1 regulates gene expression in eukaryotes by coupling nuclear DNA transcription to cytosolic mRNA decay. By integrating transcriptome-wide analyses of translation with biochemical and functional studies, we demonstrate an unanticipated regulatory role of Xrn1 in protein synthesis. Xrn1 promotes translation of a specific group of transcripts encoding membrane proteins. Xrn1-dependence for translation is linked to poor structural RNA contexts for translation initiation, is mediated by interactions with components of the translation initiation machinery and correlates with an Xrn1-dependence for mRNA localization at the endoplasmic reticulum, the translation compartment of membrane proteins. Importantly, for this group of mRNAs, Xrn1 stimulates transcription, mRNA translation and decay. Our results uncover a crosstalk between the three major stages of gene expression coordinated by Xrn1 to maintain appropriate levels of membrane proteins., The exonuclease Xrn1 mediates crosstalk between transcription and mRNA decay in yeast. Here the authors demonstrate that Xrn1 promotes translation of mRNAs encoding membrane proteins, coupling transcription, translation, and mRNA decay.

Alzheimer's disease (AD) is a neurodegenerative process characterized by the accumulation of extracellular deposits of amyloid β-peptide (Aβ), which induces neuronal death. Monomeric Aβ is not toxic but tends to aggregate into β-sheets that are neurotoxic. Therefore to prevent or delay AD onset and progression one of the main therapeutic approaches would be to impair Aβ assembly into oligomers and fibrils and to promote disaggregation of the preformed aggregate. Albumin is the most abundant protein in the cerebrospinal fluid and it was reported to bind Aβ impeding its aggregation. In a previous work we identified a 35-residue sequence of clusterin, a well-known protein that binds Aβ, that is highly similar to the C-terminus (CTerm) of albumin. In this work, the docking experiments show that the average binding free energy of the CTerm-Aβ1–42 simulations was significantly lower than that of the clusterin-Aβ1–42 binding, highlighting the possibility that the CTerm retains albumin's binding properties. To validate this observation, we performed in vitro structural analysis of soluble and aggregated 1 μM Aβ1–42 incubated with 5 μM CTerm, equimolar to the albumin concentration in the CSF. Reversed-phase chromatography and electron microscopy analysis demonstrated a reduction of Aβ1–42 aggregates when the CTerm was present. Furthermore, we treated a human neuroblastoma cell line with soluble and aggregated Aβ1–42 incubated with CTerm obtaining a significant protection against Aβ-induced neurotoxicity. These in silico and in vitro data suggest that the albumin CTerm is able to impair Aβ aggregation and to promote disassemble of Aβ aggregates protecting neurons., Graphical Abstract Unlabelled Image, Highlights • Albumin binds amyloid with higher affinity than clusterin. • The albumin C-terminus retains the amyloid binding ability of the whole albumin. • The albumin C-terminus impairs amyloid assembly. • The albumin C-terminus favors the disassemble of amyloid aggregates. • The albumin C-terminus protects neurons against aggregated amyloid.

MotivationDirect-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. Current algorithms for DCA, although efficient, have a high computational cost of determining Direct Information (DI) values for large proteins or domains. In this paper, we present RADI (Reduced Alphabet Direct Information), a variation of the original DCA algorithm that simplifies the computation of DI values by grouping physicochemically equivalent residues.ResultsWe have compared the first top ranking 40 pairs of DI values and their closest paired contact in 3D. The ranking is also compared with results obtained using a similar but faster approach based on Mutual Information (MI). When we simplify the number of symbols used to describe a protein sequence to 9, RADI achieves similar results as the original DCA (i.e. with the classical alphabet of 21 symbols), while reducing the computation time around 30-fold on large proteins (with length around 1000 residues) and with higher accuracy than predictions based on MI. Interestingly, the simplification produced by grouping amino acids into only two groups (polar and non-polar) is still representative of the physicochemical nature that characterizes the protein structure, having a relevant and useful predictive value, while the computation time is reduced between 100 and 2500-fold.AvailabilityRADI is available at https://github.com/structuralbioinformatics/RADIContactbaldo.oliva@upf.eduSupplementary informationSupplementary data is available in the git repository.

HighlightsPeptidyl arginine deiminase 2 (PADI2) citrullinates arginine1810 (cit1810) present at carboxy-terminal domain of RNA polymerase II (RNAP2-CTD).PADI2 and R1810 of RNAP2-CTD regulate transcription and proliferation of breast cancer cells.Absence of cit1810 at RNAP2-CTD leads to RNAP2 accumulation at proximal promoter regions.Cit1810 at RNAP2-CTD facilitate interaction with P-TFEb complex.SUMMARYThe post-translational modification of key residues at the carboxy-terminal domain of RNA polymerase II (RNAP2-CTD), coordinates transcription, splicing, and RNA processing by modulating its capacity to act as a landing platform for a variety of protein complexes. Here, we identify a new modification at the CTD, the deimination of arginine and its conversion to citrulline by peptidyl arginine deiminase 2 (PADI2), an enzyme that has been associated with several diseases including cancer. We show that among PADI family members, only PADI2 citrullinates R1810 (Cit1810) at repeat 31 of the CTD. Depletion of PADI2 or loss of R1810 result in accumulation of RNAP2 at transcription start sites, reduced gene expression and inhibition of cell proliferation. Cit1810 is needed for interaction with the P-TEFb (positive transcription elongation factor b) kinase complex and for its recruitment to chromatin. In this way, CTD-Cit1810 favors RNAP2 pause release and efficient transcription in breast cancer cells.

The packaging of genetic information in form of chromatin within the nucleus provides cells with the ability to store and protect massive amounts of information within a compact space. Storing information within chromatin allows selective access to specific DNA sequences by regulating the various levels of chromatin structure from nucleosomes, to chromatin fibers, loops and topological associating domains (TADs) using mechanisms that are being progressively unravelled. However, a relatively unexplored aspect is the energetic cost of changing the chromatin configuration to gain access to DNA information. Among the enzymes responsible for regulating chromatin access are the ATP-dependent chromatin remodellers that act on nucleosomes and use the energy of ATP hydrolysis to make chromatin DNA more accessible. It is assumed that the ATP used by these enzymes is provided by the mitochondria or by cytoplasmic glycolysis. We hypothesize that though this may be the case for cells in steady state, when gene expression has to be globally reprogramed in response to externals signals or stress conditions, the cell directs energy production to the cell nucleus, where rapid chromatin reorganization is needed for cell survival. We discovered that in response to hormones a nuclear ATP synthesis mechanism is activated that utilizing ADP-ribose and pyrophosphate as substrates. 1 This extra view aims to put this process within its historical context, to describe the enzymatic steps in detail, to propose a possible structure of the ATP synthesising enzyme, and to shed light on how this may link to other reactions within the cell providing a perspective for future lines of investigation.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the pathological aggregation of the amyloid-β peptide (Aβ). Monomeric soluble Aβ can switch from helicoidal to β-sheet conformation, promoting its assembly into oligomers and subsequently to amyloid fibrils. Oligomers are highly toxic to neurons and have been reported to induce synaptic transmission impairments. The progression from oligomers to fibrils forming senile plaques is currently considered a protective mechanism to avoid the presence of the highly toxic oligomers. Protein nitration is a frequent post-translational modification under AD nitrative stress conditions. Aβ can be nitrated at tyrosine 10 (Y10) by peroxynitrite. Based on our analysis of ThT binding, Western blot and electron and atomic force microscopy, we report that Aβ nitration stabilizes soluble, highly toxic oligomers and impairs the formation of fibrils. We propose a mechanism by which fibril elongation is interrupted upon Y10 nitration: Nitration disrupts fibril-forming folds by preventing H14-mediated bridging, as shown with an Aβ analog containing a single residue (H to E) replacement that mimics the behavior of nitrated Aβ related to fibril formation and neuronal toxicity. The pathophysiological role of our findings in AD was highlighted by the study of these nitrated oligomers on mouse hippocampal neurons, where an increased NMDAR-dependent toxicity of nitrated Aβ oligomers was observed. Our results show that Aβ nitrotyrosination is a post-translational modification that increases Aβ synaptotoxicity. SIGNIFICANCE STATEMENT: We report that nitration (i.e., the irreversible addition of a nitro group) of the Alzheimer-related peptide amyloid-β (Aβ) favors the stabilization of highly toxic oligomers and inhibits the formation of Aβ fibrils. The nitrated Aβ oligomers are more toxic to neurons due to increased cytosolic calcium levels throughout their action on NMDA receptors. Sustained elevated calcium levels trigger excitotoxicity, a characteristic event in Alzheimer's disease. This work was supported by Spanish Plan Estatal de I+D+I 2013-2016 and the ISCIII-Subdirección General de Evaluación y Fomento de la Investigación Grants PI13/00408 and Red HERACLES RD12/0042/0014 and FEDER Funds, Spanish Ministerio de Economía y Competitividad BIO2014-57518-R, BIO2014-52872-R, and AGL2014-52395-C2-2-R and FEDER Funds, the Generalitat de Catalunya (Spain) 2014-SGR-938, and Chilean Funds for Science CONICYTPFB 12/2007 and FONDECYT N° 1160724. A.P.-M. was the recipient of the Universitat Autònoma de Barcelona-Programa Banco de Santander Fellowship

The regions of the polypeptide chain immediately preceding or following an α-helix are known as Nt- and Ct cappings, respectively. Cappings play a central role stabilizing α-helices due to lack of intrahelical hydrogen bonds in the first and last turn. Sequence patterns of amino acid type preferences have been derived for cappings but the structural motifs associated to them are still unclassified. CAPS-DB is a database of clusters of structural patterns of different capping types. The clustering algorithm is based in the geometry and the (ϕ–ψ)-space conformation of these regions. CAPS-DB is a relational database that allows the user to search, browse, inspect and retrieve structural data associated to cappings. The contents of CAPS-DB might be of interest to a wide range of scientist covering different areas such as protein design and engineering, structural biology and bioinformatics. The database is accessible at: http://www.bioinsilico.org/CAPSDB. Research Councils United Kingdom Academic Fellow scheme (to N.F.F.); internal scholarship awarded by the Leeds Institute of Molecular Medicine (to J.S.M.); MICINN and FEDER (BIO2011-22568) to B.O. Funding for open access charge: Research Councils United Kingdom (RCUK)

Molecular dynamics (MD) simulations of the activation domain of porcine procarboxypeptidase B (ADBp) were performed to examine the effect of using the particle-particle particle-mesh (P3M) or the reaction field (RF) method for calculating electrostatic interactions in simulations of highly charged proteins. Several structural, thermodynamic, and dynamic observables were derived from the MD trajectories, including estimated entropies and solvation free energies and essential dynamics (ED). The P3M method leads to slightly higher atomic positional fluctuations and deviations from the crystallographic structure, along with somewhat lower values of the total energy and solvation free energy. However, the ED analysis of the system leads to nearly identical results for both simulations. Because of the strong similarity between the results, both methods appear well suited for the simulation of highly charged globular proteins in explicit solvent. However, the lower computational demand of the RF method in the present implementation represents a clear advantage over the P3M method.

Objective: The European INFOBIOMED Network of Excellence[1][1] recognized that a successful education program in biomedical informatics should include not only traditional teaching activities in the basic sciences but also the development of skills for working in multidisciplinary teams. Design: A carefully developed 3-year training program for biomedical informatics students addressed these educational aspects through the following four activities: (1) an internet course database containing an overview of all Medical Informatics and BioInformatics courses, (2) a BioMedical Informatics Summer School, (3) a mobility program based on a ‘brokerage service’ which published demands and offers, including funding for research exchange projects, and (4) training challenges aimed at the development of multi-disciplinary skills. Measurements: This paper focuses on experiences gained in the development of novel educational activities addressing work in multidisciplinary teams. The training challenges described here were evaluated by asking participants to fill out forms with Likert scale based questions. For the mobility program a needs assessment was carried out. Results: The mobility program supported 20 exchanges which fostered new BMI research, resulted in a number of peer-reviewed publications and demonstrated the feasibility of this multidisciplinary BMI approach within the European Union. Students unanimously indicated that the training challenge experience had contributed to their understanding and appreciation of multidisciplinary teamwork. Conclusion: The training activities undertaken in INFOBIOMED have contributed to a multi-disciplinary BMI approach. It is our hope that this work might provide an impetus for training efforts in Europe, and yield a new generation of biomedical informaticians. [1]: #ref-1

The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75% at sensitivity of 10%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks., Author Summary Recent advances in experimental methods have produced a deluge of protein–protein interactions data. However, these methods do not supply information on which specific protein regions are physically in contact during the interactions. Identifying these regions (interfaces) is fundamental for scientific disciplines that require detailed characterizations of protein interactions. In this work, we present a computational method that identifies groups of proteins with similar interfaces. This is achieved by relying on the observation that proteins with common interaction partners tend to interact through similar interfaces. The proposed method retrieves protein interactions from public data repositories and groups proteins that share a sensible number of interacting partners. Proteins within the same group are then labeled with the same “interacting motif” identifier (iMotif). The evaluation performed using known protein domains and structural binding sites suggests that the method is better suited for proteins with multiple interacting partners (hubs). Using yeast data, we show that the cellular essentiality of a gene better correlates with the number of interacting motifs than with the absolute number of interactions.

We present a fragment-search based method for predicting loop conformations in protein models. A hierarchical and multidimensional database has been set up that currently classifies 105,950 loop fragments and loop flanking secondary structures. Besides the length of the loops and types of bracing secondary structures the database is organized along four internal coordinates, a distance and three types of angles characterizing the geometry of stem regions. Candidate fragments are selected from this library by matching the length, the types of bracing secondary structures of the query and satisfying the geometrical restraints of the stems and subsequently inserted in the query protein framework where their fit is assessed by the root mean square deviation (r.m.s.d.) of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed phi/psi main chain dihedral angle propensities. Confidence Z-score cut-offs were determined for each loop length that identify those predicted fragments that outperform a competitive ab initio method. A web server implements the method, regularly updates the fragment library and performs prediction. Predicted segments are returned, or optionally, these can be completed with side chain reconstruction and subsequently annealed in the environment of the query protein by conjugate gradient minimization. The prediction method was tested on artificially prepared search datasets where all trivial sequence similarities on the SCOP superfamily level were removed. Under these conditions it is possible to predict loops of length 4, 8 and 12 with coverage of 98, 78 and 28% with at least of 0.22, 1.38 and 2.47 A of r.m.s.d. accuracy, respectively. In a head-to-head comparison on loops extracted from freshly deposited new protein folds the current method outperformed in a approximately 5:1 ratio an earlier developed database search method.

In humans, familial prion diseases are linked to mutations in the PRNP gene. We have sequenced part of this gene in a large sample of common chimpanzee, Pan troglodytes ( n =130 chromosomes). No variation in codons 129 and 219 has been observed: all chimpanzees were homozygous for the Met allele, which in humans increases susceptibility to Creutzfeldt–Jakob disease. We found two sequence variants: one is a synonymous polymorphism unique to the chimpanzee at codon 226, TAC to TAT (Y), with a TAC allele frequency of 80.6%; the other is a non-synonymous change at codon 148 (R148H) that falls in the target epitope for some common commercial antibodies used for prion diagnostics, and is highly conserved across species. The pathogenicity of this mutation is still unknown.

Understanding the basic principles of structural biology is becoming a major subject of study in most undergraduate level programs in biology. In the genomic and proteomic age, it is becoming indispensable for biology students to master concepts related to the sequence and structure of proteins in order to develop skills that may be useful in a wide range of applications. Within this context, this article shows a scheme for teaching structural biology based on hands-on computer approaches, including computational genomics, and structural bioinformatics tools. The students learn to use most of the leading computer programs available for the complete path that goes from sequence to structure and eventually function. During the course, they are taught to build models of proteins based on sequence and structure information. The students are also provided with a critical point of view on automatic procedures and learn to discern between likely and unlikely structures of their final models.