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Genome-wide association studies of human personality have been carried out, but transcription of the whole genome has not been studied in relation to personality in humans. We collected genome-wide expression profiles of adults to characterize the regulation of expression and function in genes related to human personality. We devised an innovative multi-omic approach to network analysis to identify the key control elements and interactions in multi-modular networks. We identified sets of transcribed genes that were co-expressed in specific brain regions with genes known to be associated with personality. Then we identified the minimum networks for the co-localized genes using bioinformatic resources. Subjects were 459 adults from the Young Finns Study who completed the Temperament and Character Inventory and provided peripheral blood for genomic and transcriptomic analysis. We identified an extrinsic network of 45 regulatory genes from seed genes in brain regions involved in self-regulation of emotional reactivity to extracellular stimuli (e.g., self-regulation of anxiety) and an intrinsic network of 43 regulatory genes from seed genes in brain regions involved in self-regulation of interpretations of meaning (e.g., production of concepts and language). We discovered that interactions between the two networks were coordinated by a control hub of 3 miRNAs and 3 protein-coding genes shared by both. Interactions of the control hub with proteins and ncRNAs identified more than 100 genes that overlap directly with known personality-related genes and more than another 4000 genes that interact indirectly. We conclude that the six-gene hub is the crux of an integrative network that orchestrates information-transfer throughout a multi-modular system of over 4000 genes enriched in liquid-liquid-phase-separation (LLPS)-related RNAs, diverse transcription factors, and hominid-specific miRNAs and lncRNAs. Gene expression networks associated with human personality regulate neuronal plasticity, epigenesis, and adaptive functioning by the interactions of salience and meaning in self-awareness., (© 2024. The Author(s).)

Background: Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge., Objectives: To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management., Methods: In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM., Results: We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample., Conclusions: These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Association of Dermatologists.)

Bradyrhizobium diazoefficiens can live inside soybean root nodules and in free-living conditions. In both states, when oxygen levels decrease, cells adjust their protein pools by gene transcription modulation. PhaR is a transcription factor involved in polyhydroxyalkanoate (PHA) metabolism but also plays a role in the microaerobic network of this bacterium. To deeply uncover the function of PhaR, we applied a multipronged approach, including the expression profile of a phaR mutant at the transcriptional and protein levels under microaerobic conditions, and the identification of direct targets and of proteins associated with PHA granules. Our results confirmed a pleiotropic function of PhaR, affecting several phenotypes, in addition to PHA cycle control. These include growth deficiency, regulation of carbon and nitrogen allocation, and bacterial motility. Interestingly, PhaR may also modulate the microoxic-responsive regulatory network by activating the expression of fixK 2 and repressing nifA , both encoding two transcription factors relevant for microaerobic regulation. At the molecular level, two PhaR-binding motifs were predicted and direct control mediated by PhaR determined by protein-interaction assays revealed seven new direct targets for PhaR. Finally, among the proteins associated with PHA granules, we found PhaR, phasins, and other proteins, confirming a dual function of PhaR in microoxia.

The human brain's resting-state functional connectivity (rsFC) provides stable trait-like measures of differences in the perceptual, cognitive, emotional, and social functioning of individuals. The rsFC of the prefrontal cortex is hypothesized to mediate a person's rational self-government, as is also measured by personality, so we tested whether its connectivity networks account for vulnerability to psychosis and related personality configurations. Young adults were recruited as outpatients or controls from the same communities around psychiatric clinics. Healthy controls (n = 30) and clinically stable outpatients with bipolar disorder (n = 35) or schizophrenia (n = 27) were diagnosed by structured interviews, and then were assessed with standardized protocols of the Human Connectome Project. Data-driven clustering identified five groups of patients with distinct patterns of rsFC regardless of diagnosis. These groups were distinguished by rsFC networks that regulate specific biopsychosocial aspects of psychosis: sensory hypersensitivity, negative emotional balance, impaired attentional control, avolition, and social mistrust. The rsFc group differences were validated by independent measures of white matter microstructure, personality, and clinical features not used to identify the subjects. We confirmed that each connectivity group was organized by differential collaborative interactions among six prefrontal and eight other automatically-coactivated networks. The temperament and character traits of the members of these groups strongly accounted for the differences in rsFC between groups, indicating that configurations of rsFC are internal representations of personality organization. These representations involve weakly self-regulated emotional drives of fear, irrational desire, and mistrust, which predispose to psychopathology. However, stable outpatients with different diagnoses (bipolar or schizophrenic psychoses) were highly similar in rsFC and personality. This supports a diathesis-stress model in which different complex adaptive systems regulate predisposition (which is similar in stable outpatients despite diagnosis) and stress-induced clinical dysfunction (which differs by diagnosis)., (© 2023. The Author(s).)

Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value < 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research., (© 2023. The Author(s).)

Reactive oxygen species (ROS) act as secondary messengers that can be sensed by specific redox-sensitive proteins responsible for the activation of signal transduction culminating in altered gene expression. The subcellular site, in which modifications in the ROS/oxidation state occur, can also act as a specific cellular redox network signal. The chemical identity of ROS and their subcellular origin is actually a specific imprint on the transcriptome response. In recent years, a number of transcriptomic studies related to altered ROS metabolism in plant peroxisomes have been carried out. In this study, we conducted a meta-analysis of these transcriptomic findings to identify common transcriptional footprints for plant peroxisomal-dependent signaling at early and later time points. These footprints highlight the regulation of various metabolic pathways and gene families, which are also found in plant responses to several abiotic stresses. Major peroxisomal-dependent genes are associated with protein and endoplasmic reticulum (ER) protection at later stages of stress while, at earlier stages, these genes are related to hormone biosynthesis and signaling regulation. Furthermore, in silico analyses allowed us to assign human orthologs to some of the peroxisomal-dependent proteins, which are mainly associated with different cancer pathologies. Peroxisomal footprints provide a valuable resource for assessing and supporting key peroxisomal functions in cellular metabolism under control and stress conditions across species., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Terrón-Camero, Peláez-Vico, Rodríguez-González, del Val, Sandalio and Romero-Puertas.)

Prostate cancer (PCa) is a tumor with a great heterogeneity, both at a molecular and clinical level. Despite its global good prognosis, cases can vary from indolent to lethal metastatic and scientific efforts are aimed to discern those with worse outcomes. Current prognostic markers, as Gleason score, fall short when it comes to distinguishing these cases. Identification of new early biomarkers to enable a better PCa distinction and classification remains a challenge. In order to identify new genes implicated in PCa progression we conducted several differential gene expression analyses over paired samples comparing primary PCa tissue against healthy prostatic tissue of PCa patients. The results obtained show that this approach is a serious alternative to overcome patient heterogeneity. We were able to identify 250 genes whose expression varies along with tissue differentiation-healthy to tumor tissue, 161 of these genes are described here for the first time to be related to PCa. The further manual curation of these genes allowed to annotate 39 genes with antitumoral activity, 22 of them described for the first time to be related to PCa proliferation and metastasis. These findings could be replicated in different cohorts for most genes. Results obtained considering paired differential expression, functional annotation and replication results point to: CGREF1, UNC5A, C16orf74, LGR6, IGSF1, QPRT and CA14 as possible new early markers in PCa. These genes may prevent the progression of the disease and their expression should be studied in patients with different outcomes., (© 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences., (© 2019. The Author(s).)

Corona virus spike protein S is a large homo-trimeric protein anchored in the membrane of the virion particle. Protein S binds to angiotensin-converting-enzyme 2, ACE2, of the host cell, followed by proteolysis of the spike protein, drastic protein conformational change with exposure of the fusion peptide of the virus, and entry of the virion into the host cell. The structural elements that govern conformational plasticity of the spike protein are largely unknown. Here, we present a methodology that relies upon graph and centrality analyses, augmented by bioinformatics, to identify and characterize large H-bond clusters in protein structures. We apply this methodology to protein S ectodomain and find that, in the closed conformation, the three protomers of protein S bring the same contribution to an extensive central network of H-bonds, and contribute symmetrically to a relatively large H-bond cluster at the receptor binding domain, and to a cluster near a protease cleavage site. Markedly different H-bonding at these three clusters in open and pre-fusion conformations suggest dynamic H-bond clusters could facilitate structural plasticity and selection of a protein S protomer for binding to the host receptor, and proteolytic cleavage. From analyses of spike protein sequences we identify patches of histidine and carboxylate groups that could be involved in transient proton binding., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

SecA is an essential component of the Sec protein secretion pathway in bacteria. Secretory proteins targeted to the Sec pathway by their N-terminal signal peptide bind to SecA, which couples binding and hydrolysis of adenosine triphosphate with movement of the secretory protein across the membrane-embedded SecYEG protein translocon. The phylogenetic diversity of bacteria raises the important question as to whether the region of SecA where the pre-protein binds has conserved sequence features that might impact the reaction mechanism of SecA. To address this question we established a large data set of SecA protein sequences and implemented a protocol to cluster and analyze these sequences according to features of two of the SecA functional domains, the protein binding domain and the nucleotide-binding domain 1. We identify remarkable sequence diversity of the protein binding domain, but also conserved motifs with potential role in protein binding. The N-terminus of SecA has sequence motifs that could help anchor SecA to the membrane. The overall sequence length and net estimated charge of SecA sequences depend on the organism., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

In breast cancer (BC), the presence of cancer stem cells (CSCs) has been related to relapse, metastasis, and radioresistance. Radiotherapy (RT) is an extended BC treatment, but is not always effective. CSCs have several mechanisms of radioresistance in place, and some miRNAs are involved in the cellular response to ionizing radiation (IR). Here, we studied how IR affects the expression of miRNAs related to stemness in different molecular BC subtypes. Exposition of BC cells to radiation doses of 2, 4, or 6 Gy affected their phenotype, functional characteristics, pluripotency gene expression, and in vivo tumorigenic capacity. This held true for various molecular subtypes of BC cells (classified by ER, PR and HER-2 status), and for BC cells either plated in monolayer, or being in suspension as mammospheres. However, the effect of IR on the expression of eight stemness- and radioresistance-related miRNAs (miR-210, miR-10b, miR-182, miR-142, miR-221, miR-21, miR-93, miR-15b) varied, depending on cell line subpopulation and clinicopathological features of BC patients. Therefore, clinicopathological features and, potentially also, chemotherapy regimen should be both taken into consideration, for determining a potential miRNA signature by liquid biopsy in BC patients treated with RT. Personalized and precision RT dosage regimes could improve the prognosis, treatment, and survival of BC patients., (© 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.)

Colorectal cancer treatment has advanced over the past decade. The drug 5-fluorouracil is still used with a wide percentage of patients who do not respond. Therefore, a challenge is the identification of predictive biomarkers. The protein kinase R (PKR also called EIF2AK2) and its regulator, the non-coding pre-mir-nc886, have multiple effects on cells in response to numerous types of stress, including chemotherapy. In this work, we performed an ambispective study with 197 metastatic colon cancer patients with unresectable metastases to determine the relative expression levels of both nc886 and PKR by qPCR, as well as the location of PKR by immunohistochemistry in tumour samples and healthy tissues (plasma and colon epithelium). As primary end point, the expression levels were related to the objective response to first-line chemotherapy following the response evaluation criteria in solid tumours (RECIST) and, as the second end point, with survival at 18 and 36 months. Hierarchical agglomerative clustering was performed to accommodate the heterogeneity and complexity of oncological patients' data. High expression levels of nc886 were related to the response to treatment and allowed to identify clusters of patients. Although the PKR mRNA expression was not associated with chemotherapy response, the absence of PKR location in the nucleolus was correlated with first-line chemotherapy response. Moreover, a relationship between survival and the expression of both PKR and nc886 in healthy tissues was found. Therefore, this work evaluated the best way to analyse the potential biomarkers PKR and nc886 in order to establish clusters of patients depending on the cancer outcomes using algorithms for complex and heterogeneous data.

Cadmium (Cd), which is a toxic non-essential heavy metal capable of entering plants and thus the food chain, constitutes a major environmental and health concern worldwide. An understanding of the tools used by plants to overcome Cd stress could lead to the production of food crops with lower Cd uptake capacity and of plants with greater Cd uptake potential for phytoremediation purposes in order to restore soil efficiency in self-sustaining ecosystems. The signalling molecule nitric oxide (NO), whose function remains unclear, has recently been involved in responses to Cd stress. Using different mutants, such as nia1nia2, nox1, argh1-1 and Atnoa1, which were altered in NO metabolism, we analysed various parameters related to reactive oxygen and nitrogen species (ROS/RNS) metabolism and seedling fitness following germination and growth under Cd treatment conditions for seven days. Seedling roots were the most affected, with an increase in ROS and RNS observed in wild type (WT) seedling roots, leading to increased oxidative damage and fitness loss. Mutants that showed lower NO levels in seedling roots under Cd stress were more resistant than WT seedlings due to the maintenance of antioxidant systems which protect against oxidative damage., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Anthropogenic activities, such as industrial processes, mining, and agriculture, lead to an increase in heavy metal concentrations in soil, water, and air. Given their stability in the environment, heavy metals are difficult to eliminate and can constitute a human health risk by entering the food chain through uptake by crop plants. An excess of heavy metals is toxic for plants, which have various mechanisms to prevent their accumulation. However, once metals enter the plant, oxidative damage sometimes occurs, which can lead to plant death. Initial production of nitric oxide (NO), which may play a role in plant perception, signalling, and stress acclimation, has been shown to protect against heavy metals. Very little is known about NO-dependent mechanisms downstream from signalling pathways in plant responses to heavy metal stress. In this review, using bioinformatic techniques, we analyse studies of the involvement of NO in plant responses to heavy metal stress, its possible role as a cytoprotective molecule, and its relationship with reactive oxygen species. Some conclusions are drawn and future research perspectives are outlined to further elucidate the signalling mechanisms underlying the role of NO in plant responses to heavy metal stress., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

PsbO is an extrinsic subunit of photosystem II engaged in complex binding interactions within photosystem II. At the interface between PsbO, D1 and D2 subunits of photosystem II, a cluster of charged and polar groups of PsbO is part of an extended hydrogen-bond network thought to participate in proton transfer. The precise role of specific amino acid residues at this complex binding interface remains a key open question. Here, we address this question by carrying out extensive bioinformatics analyses and molecular dynamics simulations of PsbO proteins with mutations at the binding interface. We find that PsbO proteins from cyanobacteria vs. plants have specific preferences for the number and composition of charged amino acid residues that may ensure that PsbO proteins avoid aggregation and expose long unstructured loops for binding to photosystem II. A cluster of conserved charged groups with dynamic hydrogen bonds provides PsbO with structural plasticity at the binding interface with photosystem II., (Copyright © 2017. Published by Elsevier B.V.)

The Bacillus pumilus 15.1 strain, a recently described entomopathogenic strain active against Ceratitis capitata, contains at least two extrachromosomal elements, pBp15.1S and pBp15.1B. Given that B. pumilus is not a typical entomopathogenic bacterium, the acquisition of this extrachromosomal DNA may explain why B. pumilus 15.1 is toxic to an insect. One of the plasmids present in the strain, the pBp15.1S plasmid, was sub-cloned, sequenced and analyzed using bioinformatics to identify any potential virulence factor. The pBp15.1S plasmid was found to be 7785 bp in size with a GC content of 35.7% and 11 putative ORFs. A replication module typical of a small rolling circle plasmid and a sensing and regulatory system specific for plasmids was found in pBp15.1S. Additionally, we demonstrated the existence of ssDNA in plasmid preparations suggesting that pBp15.1S replicates by the small rolling circle mechanism. A gene cluster present in plasmid pPZZ84 from a distantly isolated B. pumilus strain was also present in pBp15.1S. The plasmid copy number of pBp15.1S in exponentially growing B. pumilus cells was determined to be 33 copies per chromosome. After an extensive plasmid characterization, no known virulence factor was found so a search in the other extrachromosomal elements of the bacteria is needed., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

Objective: The authors sought to demonstrate that schizophrenia is a heterogeneous group of heritable disorders caused by different genotypic networks that cause distinct clinical syndromes., Method: In a large genome-wide association study of cases with schizophrenia and controls, the authors first identified sets of interacting single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (SNP sets) regardless of clinical status. Second, they examined the risk of schizophrenia for each SNP set and tested replicability in two independent samples. Third, they identified genotypic networks composed of SNP sets sharing SNPs or subjects. Fourth, they identified sets of distinct clinical features that cluster in particular cases (phenotypic sets or clinical syndromes) without regard for their genetic background. Fifth, they tested whether SNP sets were associated with distinct phenotypic sets in a replicable manner across the three studies., Results: The authors identified 42 SNP sets associated with a 70% or greater risk of schizophrenia, and confirmed 34 (81%) or more with similar high risk of schizophrenia in two independent samples. Seventeen networks of SNP sets did not share any SNP or subject. These disjoint genotypic networks were associated with distinct gene products and clinical syndromes (i.e., the schizophrenias) varying in symptoms and severity. Associations between genotypic networks and clinical syndromes were complex, showing multifinality and equifinality. The interactive networks explained the risk of schizophrenia more than the average effects of all SNPs (24%)., Conclusions: Schizophrenia is a group of heritable disorders caused by a moderate number of separate genotypic networks associated with several distinct clinical syndromes.

Trypanosomes are early-branched eukaryotes that show an unusual dependence on post-transcriptional mechanisms to regulate gene expression. RNA-binding proteins are crucial in controlling mRNA fate in these organisms, but their RNA substrates remain largely unknown. Here we have analyzed on a global scale the mRNAs associated with the Trypanosoma brucei RNA-binding protein DRBD3/PTB1, by capturing ribonucleoprotein complexes using UV cross-linking and subsequent immunoprecipitation. DRBD3/PTB1 associates with many transcripts encoding ribosomal proteins and translation factors. Consequently, silencing of DRBD3/PTB1 expression altered the protein synthesis rate. DRBD3/PTB1 also binds to mRNAs encoding the enzymes required to obtain energy through the oxidation of proline to succinate. We hypothesize that DRBD3/PTB1 is a key player in RNA regulon-based gene control influencing protein synthesis in trypanosomes., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Motivation: Small non-coding RNAs (sRNAs) have major roles in the post-transcriptional regulation in prokaryotes. The experimental validation of a relatively small number of sRNAs in few species requires developing computational algorithms capable of robustly encoding the available knowledge and using this knowledge to predict sRNAs within and across species., Results: We present a novel methodology designed to identify bacterial sRNAs by incorporating the knowledge encoded by different sRNA prediction methods and optimally aggregating them as potential predictors. Because some of these methods emphasize specificity, whereas others emphasize sensitivity while detecting sRNAs, their optimal aggregation constitutes trade-off solutions between these two contradictory objectives that enhance their individual merits. Many non-redundant optimal aggregations uncovered by using multiobjective optimization techniques are then combined into a multiclassifier, which ensures robustness during detection and prediction even in genomes with distinct nucleotide composition. By training with sRNAs in Salmonella enterica Typhimurium, we were able to successfully predict sRNAs in Sinorhizobium meliloti, as well as in multiple and poorly annotated species. The proposed methodology, like a meta-analysis approach, may begin to lay a possible foundation for developing robust predictive methods across a wide spectrum of genomic variability., Availability and Implementation: Scripts created for the experimentation are available at http://m4m.ugr.es/SupInfo/sRNAOS/sRNAOSscripts.zip., Contact: delval@decsai.ugr.es, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Channelrhodopsins are microbial-type rhodopsins that function as light-gated cation channels. Understanding how the detailed architecture of the protein governs its dynamics and specificity for ions is important, because it has the potential to assist in designing site-directed channelrhodopsin mutants for specific neurobiology applications. Here we use bioinformatics methods to derive accurate alignments of channelrhodopsin sequences, assess the sequence conservation patterns and find conserved motifs in channelrhodopsins, and use homology modeling to construct three-dimensional structural models of channelrhodopsins. The analyses reveal that helices C and D of channelrhodopsins contain Cys, Ser, and Thr groups that can engage in both intra- and inter-helical hydrogen bonds. We propose that these polar groups participate in inter-helical hydrogen-bonding clusters important for the protein conformational dynamics and for the local water interactions. This article is part of a Special Issue entitled: Retinal Proteins - You can teach an old dog new tricks., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Long-distance proton transfers by proton pumps occurs in discrete steps that may involve the direct participation of protein sidechains and water molecules, and coupling of protonation changes to structural rearrangements of the protein matrix. Here we explore the role of inter-helical hydrogen bonding in long-distance protein conformational coupling and dynamics of internal water molecules. From molecular dynamics simulations of wild type and nine different bacteriorhodopsin mutants we find that both intra- and inter-helical hydrogen bonds are important determinants of the local protein structure, dynamics, and water interactions. Based on molecular dynamics and bioinformatics analyses, we identify an aspartate/threonine inter-helical hydrogen-bonding motif involved in controlling the local conformational dynamics. Perturbation of inter-helical hydrogen bonds can couple to rapid changes in water dynamics., (Copyright © 2014. Published by Elsevier Inc.)

It has been proposed that single nucleotide polymorphisms (SNPs) discovered by genome-wide association studies (GWAS) account for only a small fraction of the genetic variation of complex traits in human population. The remaining unexplained variance or missing heritability is thought to be due to marginal effects of many loci with small effects and has eluded attempts to identify its sources. Combination of different studies appears to resolve in part this problem. However, neither individual GWAS nor meta-analytic combinations thereof are helpful for disclosing which genetic variants contribute to explain a particular phenotype. Here, we propose that most of the missing heritability is latent in the GWAS data, which conceals intermediate phenotypes. To uncover such latent information, we propose the PGMRA server that introduces phenomics--the full set of phenotype features of an individual--to identify SNP-set structures in a broader sense, i.e. causally cohesive genotype-phenotype relations. These relations are agnostically identified (without considering disease status of the subjects) and organized in an interpretable fashion. Then, by incorporating a posteriori the subject status within each relation, we can establish the risk surface of a disease in an unbiased mode. This approach complements-instead of replaces-current analysis methods. The server is publically available at http://phop.ugr.es/fenogeno.

We combined systematic bioinformatics analyses and molecular dynamics simulations to assess the conservation patterns of Ser and Thr motifs in membrane proteins, and the effect of such motifs on the structure and dynamics of α-helical transmembrane (TM) segments. We find that Ser/Thr motifs are often present in β-barrel TM proteins. At least one Ser/Thr motif is present in almost half of the sequences of α-helical proteins analyzed here. The extensive bioinformatics analyses and inspection of protein structures led to the identification of molecular transporters with noticeable numbers of Ser/Thr motifs within the TM region. Given the energetic penalty for burying multiple Ser/Thr groups in the membrane hydrophobic core, the observation of transporters with multiple membrane-embedded Ser/Thr is intriguing and raises the question of how the presence of multiple Ser/Thr affects protein local structure and dynamics. Molecular dynamics simulations of four different Ser-containing model TM peptides indicate that backbone hydrogen bonding of membrane-buried Ser/Thr hydroxyl groups can significantly change the local structure and dynamics of the helix. Ser groups located close to the membrane interface can hydrogen bond to solvent water instead of protein backbone, leading to an enhanced local solvation of the peptide.

Electrophysiological experiments showed that the light-activated cation channel channelrhodopsin-2 (ChR2) pumps protons in the absence of a membrane potential. We determined here the kinetics of transient pH change using a water-soluble pH-indicator. It is shown that ChR2 released protons prior to uptake with a stoichiometry of 0.3 protons per ChR2. Comparison to the photocycle kinetics revealed that proton release and uptake match rise and decay of the P(3)(520) intermediate. As the P(3)(520) state also represents the conductive state of cation channeling, the concurrence of proton pumping and channel gating implies an intimate mechanistic link of the two functional modes. Studies on the E123T and S245E mutants show that these residues are not critically involved in proton translocation., (Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.)

We have performed a computational comparative analysis of six small non-coding RNA (sRNA) families in α-proteobacteria. Members of these families were first identified in the intergenic regions of the nitrogen-fixing endosymbiont S. meliloti by a combined bioinformatics screen followed by experimental verification. Consensus secondary structures inferred from covariance models for each sRNA family evidenced in some cases conserved motifs putatively relevant to the function of trans-encoded base-pairing sRNAs i.e., Hfq-binding signatures and exposed anti Shine-Dalgarno sequences. Two particular family models, namely αr15 and αr35, shared own sub-structural modules with the Rfam model suhB (RF00519) and the uncharacterized sRNA family αr35b, respectively. A third sRNA family, termed αr45, has homology to the cis-acting regulatory element speF (RF00518). However, new experimental data further confirmed that the S. meliloti αr45 representative is an Hfq-binding sRNA processed from or expressed independently of speF, thus refining the Rfam speF model annotation. All the six families have members in phylogenetically related plant-interacting bacteria and animal pathogens of the order of the Rhizobiales, some occurring with high levels of paralogy in individual genomes. In silico and experimental evidences predict differential regulation of paralogous sRNAs in S. meliloti 1021. The distribution patterns of these sRNA families suggest major contributions of vertical inheritance and extensive ancestral duplication events to the evolution of sRNAs in plant-interacting bacteria.

The SecY/Sec61 translocon complex, located in the endoplasmic reticulum membrane of eukaryotes (Sec61) or the plasma membrane of prokaryotes (SecY), mediates the transmembrane secretion or insertion of nascent proteins. Mutations that permit the secretion of nascent proteins with defective signal sequences (Prl-phenotype), or interfere with the transmembrane orientation of newly synthesized protein segments, can affect protein topogenesis. The crystallographic structure of SecYEbeta from Methanococcus jannaschii revealed widespread distribution of mutations causing topogenesis defects, but not their molecular mechanisms. Based upon prolonged molecular dynamics simulations of wild-type M. jannaschii SecYEbeta and an extensive sequence-conservation analysis, we show that the closed state of the translocon is stabilized by hydrogen-bonding interactions of numerous highly conserved amino acids. Perturbations induced by mutation at various locations are rapidly relayed to the plug segment that seals the wild-type closed-state translocon, leading to displacement and increased hydration of the plug., (Copyright 2010 Elsevier Ltd. All rights reserved.)

An increasing amount of expressed sequence tag (EST) and genomic data, predominantly for the cnidarians Acropora, Hydra and Nematostella, reveals that cnidarians have a high genomic complexity, despite being one of the morphologically simplest multicellular animals. Considering the diversity of cnidarians, we performed an EST project on the hydroid Hydractinia echinata, to contribute towards a broader coverage of this phylum. After random sequencing of almost 9000 clones, EST characterization revealed a broad diversity in gene content. Corroborating observations in other cnidarians, Hydractinia sequences exhibited a higher sequence similarity to vertebrates than to ecdysozoan invertebrates. A significant number of sequences were hitherto undescribed in metazoans, suggesting that these may be either cnidarian innovations or ancient genes lost in the bilaterian genomes analysed so far. However, we cannot rule out some degree of contamination from commensal bacteria. The identification of unique Hydractinia sequences emphasizes that the acquired genomic information generated so far is not large enough to be representative of the highly diverse cnidarian phylum. Finally, a database was created to store all the acquired information (http://www.mchips.org/hydractinia&#95;echinata.html).

Background: A large amount of computational and experimental work has been devoted to uncovering network motifs in gene regulatory networks. The leading hypothesis is that evolutionary processes independently selected recurrent architectural relationships among regulators and target genes (motifs) to produce characteristic expression patterns of its members. However, even with the same architecture, the genes may still be differentially expressed. Therefore, to define fully the expression of a group of genes, the strength of the connections in a network motif must be specified, and the cis-promoter features that participate in the regulation must be determined., Results: We have developed a model-based approach to analyze proteobacterial genomes for promoter features that is specifically designed to account for the variability in sequence, location and topology intrinsic to differential gene expression. We provide methods for annotating regulatory regions by detecting their subjacent cis-features. This includes identifying binding sites for a transcriptional regulator, distinguishing between activation and repression sites, direct and reverse orientation, and among sequences that weakly reflect a particular pattern; binding sites for the RNA polymerase, characterizing different classes, and locations relative to the transcription factor binding sites; the presence of riboswitches in the 5'UTR, and for other transcription factors. We applied our approach to characterize network motifs controlled by the PhoP/PhoQ regulatory system of Escherichia coli and Salmonella enterica serovar Typhimurium. We identified key features that enable the PhoP protein to control its target genes, and distinct features may produce different expression patterns even within the same network motif., Conclusion: Global transcriptional regulators control multiple promoters by a variety of network motifs. This is clearly the case for the regulatory protein PhoP. In this work, we studied this regulatory protein and demonstrated that understanding gene expression does not only require identifying a set of connexions or network motif, but also the cis-acting elements participating in each of these connexions.

Background: The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern., Results: We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation., Conclusion: Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods.

Intramembrane proteases, which cleave transmembrane (TM) helices, participate in numerous biological processes encompassing all branches of life. Several crystallographic structures of Escherichia coli GlpG rhomboid protease have been determined. In order to understand GlpG dynamics and lipid interactions in a native-like environment, we have examined the molecular dynamics of wild-type and mutant GlpG in different membrane environments. The irregular shape and small hydrophobic thickness of the protein cause significant bilayer deformations that may be important for substrate entry into the active site. Hydrogen-bond interactions with lipids are paramount in protein orientation and dynamics. Mutations in the unusual L1 loop cause changes in protein dynamics and protein orientation that are relayed to the His-Ser catalytic dyad. Similarly, mutations in TM5 change the dynamics and structure of the L1 loop. These results imply that the L1 loop has an important regulatory role in proteolysis.

The aim of this study was to characterize soils contaminated by different levels of heavy metals and hydrocarbons (Madonna Dell'Acqua, Pisa, Italy). The soils were chemically and biochemically analysed by measuring the standard chemical properties and some enzyme activities related to microbial activity (dehydrogenase activity) and the soil carbon cycle (total and extracellular beta-glucosidase activities). The metabolic capacities of soil microorganisms to degrade hydrocarbons through catechol 2,3-dioxygenase were also described. The microbial diversity of contaminated and uncontaminated soils was estimated by denaturing gradient gel electrophoresis (DGGE) of amplified 16S rDNA sequences. The PCR/single-strand conformation polymorphism (PCR/SSCP) method was used to estimate the genetic diversity of PAH-degrading genes in both contaminated and uncontaminated soils. A greater bacterial diversity and lower catechol 2,3-dioxygenase activity was detected in unpolluted soils. The complexity of the microbial community (Shannon and Simpson indices) as well as the dehydrogenase soil activity negatively correlated with contamination levels. The greatest PAH-degrading gene diversity and the most intense catechol 2,3-dioxygenase activity were found in the soils with the highest levels of hydrocarbons. Heavy metals and hydrocarbon pollution has caused a genetic and metabolic alteration in microbial communities, corresponding to a reduction in microbial activity. A multi-technique approach combining traditional biochemical methods with molecular-based techniques, along with some methodological improvements, may represent an important tool to expand our knowledge of the role of microbial diversity in contaminated soil.

Bacterial small non-coding RNAs (sRNAs) are being recognized as novel widespread regulators of gene expression in response to environmental signals. Here, we present the first search for sRNA-encoding genes in the nitrogen-fixing endosymbiont Sinorhizobium meliloti, performed by a genome-wide computational analysis of its intergenic regions. Comparative sequence data from eight related alpha-proteobacteria were obtained, and the interspecies pairwise alignments were scored with the programs eQRNA and RNAz as complementary predictive tools to identify conserved and stable secondary structures corresponding to putative non-coding RNAs. Northern experiments confirmed that eight of the predicted loci, selected among the original 32 candidates as most probable sRNA genes, expressed small transcripts. This result supports the combined use of eQRNA and RNAz as a robust strategy to identify novel sRNAs in bacteria. Furthermore, seven of the transcripts accumulated differentially in free-living and symbiotic conditions. Experimental mapping of the 5'-ends of the detected transcripts revealed that their encoding genes are organized in autonomous transcription units with recognizable promoter and, in most cases, termination signatures. These findings suggest novel regulatory functions for sRNAs related to the interactions of alpha-proteobacteria with their eukaryotic hosts.

Background: The German cDNA Consortium has been cloning full length cDNAs and continued with their exploitation in protein localization experiments and cellular assays. However, the efficient use of large cDNA resources requires the development of strategies that are capable of a speedy selection of truly useful cDNAs from biological and experimental noise. To this end we have developed a new high-throughput analysis tool, CAFTAN, which simplifies these efforts and thus fills the gap between large-scale cDNA collections and their systematic annotation and application in functional genomics., Results: CAFTAN is built around the mapping of cDNAs to the genome assembly, and the subsequent analysis of their genomic context. It uses sequence features like the presence and type of PolyA signals, inner and flanking repeats, the GC-content, splice site types, etc. All these features are evaluated in individual tests and classify cDNAs according to their sequence quality and likelihood to have been generated from fully processed mRNAs. Additionally, CAFTAN compares the coordinates of mapped cDNAs with the genomic coordinates of reference sets from public available resources (e.g., VEGA, ENSEMBL). This provides detailed information about overlapping exons and the structural classification of cDNAs with respect to the reference set of splice variants. The evaluation of CAFTAN showed that is able to correctly classify more than 85% of 5950 selected "known protein-coding" VEGA cDNAs as high quality multi- or single-exon. It identified as good 80.6 % of the single exon cDNAs and 85 % of the multiple exon cDNAs. The program is written in Perl and in a modular way, allowing the adoption of this strategy to other tasks like EST-annotation, or to extend it by adding new classification rules and new organism databases as they become available. We think that it is a very useful program for the annotation and research of unfinished genomes., Conclusion: CAFTAN is a high-throughput sequence analysis tool, which performs a fast and reliable quality prediction of cDNAs. Several thousands of cDNAs can be analyzed in a short time, giving the curator/scientist a first quick overview about the quality and the already existing annotation of a set of cDNAs. It supports the rejection of low quality cDNAs and helps in the selection of likely novel splice variants, and/or completely novel transcripts for new experiments.

Background: Recent observations of insertional mutagenesis in preclinical and clinical settings emphasize the relevance of investigating comprehensively the spectrum of integration sites targeted by specific vectors., Methods: We followed the engraftment of lentivirally transduced human cord blood (CB) progenitor cells after transplantation into NOD/SCID mice using a self-inactivating HIV-1-derived vector expressing the enhanced green fluorescent protein (EGFP)., Results: The mean of transduction of CD34(+) CB cells was 41%, as deduced from the percentage of EGFP(+) cells before transplantation. At 3 weeks post-transplantation, the average of EGFP(+) cells in the human cell population was 65 +/- 8%, and increased to 75 +/- 10% at 12 weeks post-transplantation. In order to determine the proviral integration sites in human NOD/SCID repopulating cells (SRCs) we used the ligation-mediated polymerase chain reaction (LM-PCR) technique. Sixty-eight percent of the integrations were found to be located in RefSeq genes, most of them in intron regions. Twenty percent of these integrations occurred within a distance of 10 kb from the transcription start site; a percentage that is significantly lower compared to that observed in cells transduced by gammaretroviral vectors. Sixty-two percent of integrations occurred in genes with a biological function in cell metabolism, and four integrations were located in genes with a role in tumorigenesis., Conclusions: These investigations indicate that integration of lentiviral vectors in human repopulating cells capable of engrafting NOD/SCID mice preferentially occur in coding regions of the human genome. Nevertheless, the clustering of integrations at the transcriptional start is not as high as that observed for gammaretroviral vectors., (Copyright (c) 2006 John Wiley & Sons, Ltd.)

Background: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions., Description: We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar, Conclusion: Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

The wealth of transcript information that has been made publicly available in recent years requires the development of high-throughput functional genomics and proteomics approaches for its analysis. Such approaches need suitable data integration procedures and a high level of automation in order to gain maximum benefit from the results generated. We have designed an automatic pipeline to analyse annotated open reading frames (ORFs) stemming from full-length cDNAs produced mainly by the German cDNA Consortium. The ORFs are cloned into expression vectors for use in large-scale assays such as the determination of subcellular protein localization or kinase reaction specificity. Additionally, all identified ORFs undergo exhaustive bioinformatic analysis such as similarity searches, protein domain architecture determination and prediction of physicochemical characteristics and secondary structure, using a wide variety of bioinformatic methods in combination with the most up-to-date public databases (e.g. PRINTS, BLOCKS, INTERPRO, PROSITE SWISSPROT). Data from experimental results and from the bioinformatic analysis are integrated and stored in a relational database (MS SQL-Server), which makes it possible for researchers to find answers to biological questions easily, thereby speeding up the selection of targets for further analysis. The designed pipeline constitutes a new automatic approach to obtaining and administrating relevant biological data from high-throughput investigations of cDNAs in order to systematically identify and characterize novel genes, as well as to comprehensively describe the function of the encoded proteins.

Background: In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process., Results: cDNA2Genome is an application for the automatic high-throughput mapping and characterization of cDNAs. It utilizes current annotation data and the most up to date databases, especially in the case of ESTs and mRNAs in conjunction with a vast number of approaches to gene prediction in order to perform a comprehensive assessment of the cDNA exon-intron structure. The final result of cDNA2Genome is an XML file containing all relevant information obtained in the process. This XML output can easily be used for further analysis such us program pipelines, or the integration of results into databases. The web interface to cDNA2Genome also presents this data in HTML, where the annotation is additionally shown in a graphical form. cDNA2Genome has been implemented under the W3H task framework which allows the combination of bioinformatics tools in tailor-made analysis task flows as well as the sequential or parallel computation of many sequences for large-scale analysis., Conclusions: cDNA2Genome represents a new versatile and easily extensible approach to the automated mapping and annotation of human cDNAs. The underlying approach allows sequential or parallel computation of sequences for high-throughput analysis of cDNAs.

Unlabelled: Phylogenetic Analysis Task in Husar (PATH) is a task for the inference of phylogenies. It executes three phylogenetic methods and automatically chooses the evolutionary model for each set of data. The output of the tasks shows the consensus trees together with full results obtained from all executed methods., Availability: PATH is available at the German EMBnet node after registration via www at http://genome.dkfz-heidelberg.de