Gene expression networks regulated by human personality.

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.

Pleiotropic Effects of PhaR Regulator in Bradyrhizobium diazoefficiens Microaerobic Metabolism.

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 fixK2 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.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study.

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.

Melanoma is a type of skin cancer that can be deadly if it is not detected at an early stage. Unfortunately, the early detection of melanoma is challenging. Our team has developed a model that could be used to predict whether a person has stage I malignant melanoma based on blood serum analysis. The model was trained on data from a group of people with melanoma and it was found to be accurate in predicting melanoma at an early stage. This means that the model could be used to identify people who have skin cancer before it progresses and becomes more complicated to treat. Although the researchers recommend that further studies are conducted to validate the model in a larger population of people, this research could help with the early diagnosis of melanoma and work toward improving survival rates.

Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis.

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).

Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods.

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.

Gene network downstream plant stress response modulated by peroxisomal H2O2.

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.

Identification of novel prostate cancer genes in patients stratified by Gleason classification: Role of antitumoral genes.

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.

Three genetic-environmental networks for human personality.

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.

A graph-based approach identifies dynamic H-bond communication networks in spike protein S of SARS-CoV-2.

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.

Diversity and sequence motifs of the bacterial SecA protein motor.

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.

Uncovering Tumour Heterogeneity through PKR and nc886 Analysis in Metastatic Colon Cancer Patients Treated with 5-FU-Based Chemotherapy.

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.

miRNAs as radio-response biomarkers for breast cancer stem cells.

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.

Uncovering the complex genetics of human temperament.

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.

Uncovering the complex genetics of human character.

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.

Low endogenous NO levels in roots and antioxidant systems are determinants for the resistance of Arabidopsis seedlings grown in Cd.

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.

Role of nitric oxide in plant responses to heavy metal stress: exogenous application versus endogenous production.

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.

Charged groups at binding interfaces of the PsbO subunit of photosystem II: A combined bioinformatics and simulation study.

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.

Identification, sequencing and comparative analysis of pBp15.S plasmid from the newly described entomopathogen Bacillus pumilus 15.1.

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.

Membrane Protein Structure, Function, and Dynamics: a Perspective from Experiments and Theory.

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.