The microbiota-gut-brain axis:Neurobehavioral correlates, health and sociality

Recent data suggest that the human body is not such a neatly self-sufficient island after all. It is more like a super-complex ecosystem containing trillions of bacteria and other microorganisms that inhabit all our surfaces; skin, mouth, sexual organs, and specially intestines. It has recently become evident that such microbiota, specifically within the gut, can greatly influence many physiological parameters, including cognitive functions, such as learning, memory and decision making processes. Human microbiota is a diverse and dynamic ecosystem, which has evolved in a mutualistic relationship with its host. Ontogenetically, it is vertically inoculated from the mother during birth, established during the first year of life and during lifespan, horizontally transferred among relatives, mates or close community members. This micro-ecosystem serves the host by protecting it against pathogens, metabolizing complex lipids and polysaccharides that otherwise would be inaccessible nutrients, neutralizing drugs and carcinogens, modulating intestinal motility, and making visceral perception possible. It is now evident that the bidirectional signaling between the gastrointestinal tract and the brain, mainly through the vagus nerve, the so called “microbiota–gut–vagus–brain axis,” is vital for maintaining homeostasis and it may be also involved in the etiology of several metabolic and mental dysfunctions/disorders. Here we review evidence on the ability of the gut microbiota to communicate with the brain and thus modulate behavior, and also elaborate on the ethological and cultural strategies of human and non-human primates to select, transfer and eliminate microorganisms for selecting the commensal profile

CD32 is expressed on cells with transcriptionally active HIV but does not enrich for HIV DNA in resting T cells

The persistence of HIV reservoirs, including latently infected, resting CD4+ T cells, is the major obstacle to cure HIV infection. CD32a expression was recently reported to mark CD4+ T cells harboring a replication-competent HIV reservoir during antiretroviral therapy (ART) suppression. We aimed to determine whether CD32 expression marks HIV latently or transcriptionally active infected CD4+ T cells. Using peripheral blood and lymphoid tissue of ART-treated HIV+ or SIV+ subjects, we found that most of the circulating memory CD32+ CD4+ T cells expressed markers of activation, including CD69, HLA-DR, CD25, CD38, and Ki67, and bore a TH2 phenotype as defined by CXCR3, CCR4, and CCR6. CD32 expression did not selectively enrich for HIV- or SIV-infected CD4+ T cells in peripheral blood or lymphoid tissue; isolated CD32+ resting CD4+ T cells accounted for less than 3% of the total HIV DNA in CD4+ T cells. Cell-associated HIV DNA and RNA loads in CD4+ T cells positively correlated with the frequency of CD32+ CD69+ CD4+ T cells but not with CD32 expression on resting CD4+ T cells. Using RNA fluorescence in situ hybridization, CD32 coexpression with HIV RNA or p24 was detected after in vitro HIV infection (peripheral blood mononuclear cell and tissue) and in vivo within lymph node tissue from HIV-infected individuals. Together, these results indicate that CD32 is not a marker of resting CD4+ T cells or of enriched HIV DNA–positive cells after ART; rather, CD32 is predominately expressed on a subset of activated CD4+ T cells enriched for transcriptionally active HIV after long-term ART

The EphB4 Receptor Tyrosine Kinase Promotes Lung Cancer Growth: A Potential Novel Therapeutic Target

Despite progress in locoregional and systemic therapies, patient survival from lung cancer remains a challenge. Receptor tyrosine kinases are frequently implicated in lung cancer pathogenesis, and some tyrosine kinase inhibition strategies have been effective clinically. The EphB4 receptor tyrosine kinase has recently emerged as a potential target in several other cancers. We sought to systematically study the role of EphB4 in lung cancer. Here, we demonstrate that EphB4 is overexpressed 3-fold in lung tumors compared to paired normal tissues and frequently exhibits gene copy number increases in lung cancer. We also show that overexpression of EphB4 promotes cellular proliferation, colony formation, and motility, while EphB4 inhibition reduces cellular viability in vitro, halts the growth of established tumors in mouse xenograft models when used as a single-target strategy, and causes near-complete regression of established tumors when used in combination with paclitaxel. Taken together, these data suggest an important role for EphB4 as a potential novel therapeutic target in lung cancer. Clinical trials investigating the efficacy of anti-EphB4 therapies as well as combination therapy involving EphB4 inhibition may be warranted.</p

Elite control of HIV is associated with distinct functional and transcriptional signatures in lymphoid tissue CD8+ T cells

The functional properties of circulating CD8+ T cells have been associated with immune control of HIV. However, viral replication occurs predominantly in secondary lymphoid tissues, such as lymph nodes (LNs). We used an integrated single-cell approach to characterize effective HIV-specific CD8+ T cell responses in the LNs of elite controllers (ECs), defined as individuals who suppress viral replication in the absence of antiretroviral therapy (ART). Higher frequencies of total memory and follicle-homing HIV-specific CD8+ T cells were detected in the LNs of ECs compared with the LNs of chronic progressors (CPs) who were not receiving ART. Moreover, HIV-specific CD8+ T cells potently suppressed viral replication without demonstrable cytolytic activity in the LNs of ECs, which harbored substantially lower amounts of CD4+ T cell–associated HIV DNA and RNA compared with the LNs of CPs. Single-cell RNA sequencing analyses further revealed a distinct transcriptional signature among HIV-specific CD8+ T cells from the LNs of ECs, typified by the down-regulation of inhibitory receptors and cytolytic molecules and the up-regulation of multiple cytokines, predicted secreted factors, and components of the protein translation machinery. Collectively, these results provide a mechanistic framework to expedite the identification of novel antiviral factors, highlighting a potential role for the localized deployment of noncytolytic functions as a determinant of immune efficacy against HIV

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers

A Single Argonaute Gene Participates in Exogenous and Endogenous RNAi and Controls Cellular Functions in the Basal Fungus Mucor circinelloides

The mechanism of RNAi is well described in metazoans where it plays a role in diverse cellular functions. However, although different classes of endogenous small RNAs (esRNAs) have been identified in fungi, their biological roles are poorly described due, in part, to the lack of phenotype of mutants affected in the biogenesis of these esRNAs. Argonaute proteins are one of the key components of the RNAi pathways, in which different members of this protein family participate in the biogenesis of a wide repertoire of esRNAs molecules. Here we identified three argonaute genes of the fungus Mucor circinelloides and investigated their participation in exogenous and endogenous RNAi. We found that only one of the ago genes, ago-1, is involved in RNAi during vegetative growth and is required for both transgene-induced RNA silencing and the accumulation of distinct classes of esRNAs derived from exons (ex-siRNAs). Classes I and II ex-siRNAs bind to Ago-1 to control mRNA accumulation of the target protein coding genes. Class III ex-siRNAs do not specifically bind to Ago-1, but requires this protein for their production, revealing the complexity of the biogenesis pathways of ex-siRNAs. We also show that ago-1 is involved in the response to environmental signals, since vegetative development and autolysis induced by nutritional stress are affected in ago-1(-) M. circinelloides mutants. Our results demonstrate that a single Ago protein participates in the production of different classes of esRNAs that are generated through different pathways. They also highlight the role of ex-siRNAs in the regulation of endogenous genes in fungi and expand the range of biological functions modulated by RNAi

Exploring low-energy neutrino physics with the Coherent Neutrino Nucleus Interaction Experiment

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) uses low-noise fully depleted charge-coupled devices (CCDs) with the goal of measuring low-energy recoils from coherent elastic scattering ( CE ν NS ) of reactor antineutrinos with silicon nuclei and testing nonstandard neutrino interactions (NSI). We report here the first results of the detector array deployed in 2016, considering an active mass 47.6 g (eight CCDs), which is operating at a distance of 30 m from the core of the Angra 2 nuclear reactor, with a thermal power of 3.8 GW. A search for neutrino events is performed by comparing data collected with the reactor on (2.1 kg-day) and reactor off (1.6 kg-day). The results show no excess in the reactor-on data, reaching the world record sensitivity down to recoil energies of about 1 keV (0.1 keV electron equivalent). A 95% confidence level limit for new physics is established at an event rate of 40 times the one expected from the standard model at this energy scale. The results presented here provide a new window to low-energy neutrino physics, allowing one to explore for the first time the energies accessible through the low threshold of CCDs. They will lead to new constraints on NSI from the CEνNS of antineutrinos from nuclear reactors.Fil: Aguilar Arevalo, Alexis. Universidad Nacional Autónoma de México; MéxicoFil: Bertou, Xavier Pierre Louis. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; ArgentinaFil: Bonifazi, Carla Brenda. Universidade Federal do Rio de Janeiro; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cancelo, Gustavo Indalecio. Fermi National Accelerator Laboratory; Estados UnidosFil: Castañeda, Alejandro. Universidad Nacional Autónoma de México; MéxicoFil: Cervantes Vergara, Brenda. Universidad Nacional Autónoma de México; MéxicoFil: Chavez, Claudio. Universidad Nacional de Asunción; ParaguayFil: D’Olivo, Juan C.. Universidad Nacional Autónoma de México; MéxicoFil: Dos Anjos, João C.. Centro Brasileiro de Pesquisas Físicas; BrasilFil: Estrada, Juan. Fermi National Accelerator Laboratory; Estados UnidosFil: Fernandes Neto, Aldo R.. Centro Federal de Educacão Tecnológica Celso Suckow Da Fonseca; BrasilFil: Fernández Moroni, Guillermo. Fermi National Accelerator Laboratory; Estados Unidos. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Foguel, Ana. Universidade Federal do Rio de Janeiro; BrasilFil: Ford, Richard. Fermi National Accelerator Laboratory; Estados UnidosFil: Gonzalez Cuevas, Juan. Universidad Nacional de Asunción; ParaguayFil: Hernández, Pamela. Universidad Nacional Autónoma de México; MéxicoFil: Hernandez, Susana. Fermi National Accelerator Laboratory; Estados UnidosFil: Izraelevitch, Federico Hernán. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de San Martín; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kavner, Alexander R.. University of Michigan; Estados UnidosFil: Kilminster, Ben. Universitat Zurich; SuizaFil: Kuk, Kevin. Fermi National Accelerator Laboratory; Estados UnidosFil: Lima, H.P.. Centro Brasileiro de Pesquisas Físicas; BrasilFil: Makler, Martín. Centro Brasileiro de Pesquisas Físicas; BrasilFil: Molina, Jorge. Universidad Nacional de Asunción; ParaguayFil: Mota, Philipe. Centro Brasileiro de Pesquisas Físicas; BrasilFil: Nasteva, Irina. Universidade Federal do Rio de Janeiro; BrasilFil: Paolini, Eduardo Emilio. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaFil: Romero, Carlos. Universidad Nacional de Asunción; ParaguayFil: Sarkis, Y.. Universidad Nacional Autónoma de México; MéxicoFil: Sofo Haro, Miguel Francisco. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Comisión Nacional de Energía Atómica; Argentina. Universidad Nacional de Cuyo; Argentina. Fermi National Accelerator Laboratory; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnol.conicet - Patagonia Norte. Unidad de Adm.territorial; ArgentinaFil: Souza, Iruatã M. S.. Centro Brasileiro de Pesquisas Físicas; BrasilFil: Tiffenberg, Javier Sebastian. Fermi National Accelerator Laboratory; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Wagner, Stefan. Centro Brasileiro de Pesquisas Físicas; Brasil. Pontifícia Universidade Católica do Rio de Janeiro; Brasi

Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study

Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = −0.14; 95% confidence interval [CI]: −0.24 to −0.03; p value = 0.010) and MDD (β = −0.16; 95% CI: −0.27 to −0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34–1.93; p value = 2e−7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD