Regulation of extracellular matrix components byAmrZ is mediated by c‑di‑GMP in Pseudomonas ogarae F113

The AmrZ/FleQ hub has been identified as a central node in the regulation of environmental adaption in the plant growth-promoting rhizobacterium and model for rhizosphere colonization Pseudomonas ogarae F113. AmrZ is involved in the regulation of motility, biofilm formation, and bis-(3′-5′)-cyclic dimeric guanosine monophosphate (c-di-GMP) turnover, among others, in this bacterium. The mutants in amrZ have a pleiotropic phenotype with distinguishable colony morphology, reduced biofilm formation, increased motility, and are severely impaired in competitive rhizosphere colonization. Here, RNA-Seq and qRT-PCR gene expression analyses revealed that AmrZ regulates many genes related to the production of extracellular matrix (ECM) components at the transcriptional level. Furthermore, overproduction of c-di-GMP in an amrZ mutant, by ectopic production of the Caulobacter crescentus constitutive diguanylate cyclase PleD*, resulted in increased expression of many genes implicated in the synthesis of ECM components. The overproduction of c-di-GMP in the amrZ mutant also suppressed the biofilm formation and motility phenotypes, but not the defect in competitive rhizosphere colonization. These results indicate that although biofilm formation and motility are mainly regulated indirectly by AmrZ, through the modulation of c-di-GMP levels, the implication of AmrZ in rhizosphere competitive colonization occurs in a c-di-GMP-independent manne

Adaption of Pseudomonas ogarae F113 to the rhizosphere environment—The AmrZ-FleQ Hub

Motility and biofilm formation are two crucial traits in the process of rhizosphere colonization by pseudomonads. The regulation of both traits requires a complex signaling network that is coordinated by the AmrZ-FleQ hub. In this review, we describe the role of this hub in the adaption to the rhizosphere. The study of the direct regulon of AmrZ and the phenotypic analyses of an amrZ mutant in Pseudomonas ogarae F113 has shown that this protein plays a crucial role in the regulation of several cellular functions, including motility, biofilm formation, iron homeostasis, and bis-(3′-5′)-cyclic dimeric guanosine monophosphate (c-di-GMP) turnover, controlling the synthesis of extracellular matrix components. On the other hand, FleQ is the master regulator of flagellar synthesis in P. ogarae F113 and other pseudomonads, but its implication in the regulation of multiple traits related with environmental adaption has been shown. Genomic scale studies (ChIP-Seq and RNA-Seq) have shown that in P. ogarae F113, AmrZ and FleQ are general transcription factors that regulate multiple traits. It has also been shown that there is a common regulon shared by the two transcription factors. Moreover, these studies have shown that AmrZ and FleQ form a regulatory hub that inversely regulate traits such as motility, extracellular matrix component production, and iron homeostasis. The messenger molecule c-di-GMP plays an essential role in this hub since its production is regulated by AmrZ and it is sensed by FleQ and required for its regulatory role. This regulatory hub is functional both in culture and in the rhizosphere, indicating that the AmrZ-FleQ hub is a main player of P. ogarae F113 adaption to the rhizosphere environmentWork related to environmental adaption of pseudomonads in the authors’ laboratory is currently funded by a Spanish Ministerio de Ciencia e Innovación FEDER/EU Grant PID2021-125070OB-I0

Transcriptomic analysis of pseudomonas ogarae F113 reveals the antagonistic roles of AmrZ and FleQ during rhizosphere adaption

Rhizosphere colonization by bacteria involves molecular and cellular mechanisms, such as motility and chemotaxis, biofilm formation, metabolic versatility, or biosynthesis of secondary metabolites, among others. Nonetheless, there is limited knowledge concerning the main regulatory factors that drive the rhizosphere colonization process. Here we show the importance of the AmrZ and FleQ transcription factors for adaption in the plant growth-promoting rhizobacterium (PGPR) and rhizosphere colonization model Pseudomonas ogarae F113. RNA-Seq analyses of P. ogarae F113 grown in liquid cultures either in exponential and stationary growth phase, and rhizosphere conditions, revealed that rhizosphere is a key driver of global changes in gene expression in this bacterium. Regarding the genetic background, this work has revealed that a mutation in fleQ causes considerably more alterations in the gene expression profile of this bacterium than a mutation in amrZ under rhizosphere conditions. The functional analysis has revealed that in P. ogarae F113, the transcription factors AmrZ and FleQ regulate genes involved in diverse bacterial functions. Notably, in the rhizosphere, these transcription factors antagonistically regulate genes related to motility, biofilm formation, nitrogen, sulfur, and amino acid metabolism, transport, signalling, and secretion, especially the type VI secretion systems. These results define the regulon of two important bifunctional transcriptional regulators in pseudomonads during the process of rhizosphere colonization

The diguanylate cyclase AdrA regulates flagellar biosynthesis in Pseudomonas fluorescens F113 through SadB

Flagellum mediated motility is an essential trait for rhizosphere colonization by pseudomonads. Flagella synthesis is a complex and energetically expensive process that is tightly regulated. In Pseudomonas fluorescens, the regulatory cascade starts with the master regulatory protein FleQ that is in turn regulated by environmental signals through the Gac/Rsm and SadB pathways, which converge in the sigma factor AlgU. AlgU is required for the expression of amrZ, encoding a FleQ repressor. AmrZ itself has been shown to modulate c-di-GMP levels through the control of many genes encoding enzymes implicated in c-di-GMP turnover. This cyclic nucleotide regulates flagellar function and besides, the master regulator of the flagellar synthesis signaling pathway, FleQ, has been shown to bind c-di-GMP. Here we show that AdrA, a diguanylate cyclase regulated by AmrZ participates in this signaling pathway. Epistasis analysis has shown that AdrA acts upstream of SadB, linking SadB with environmental signaling. We also show that SadB binds c-di-GMP with higher affinity than FleQ and propose that c-di-GMP produced by AdrA modulates flagella synthesis through SadBThis work was supported by funding from MINECO/FEDER EU Grant RTI2018 093991-BI00 to R.R. and M.M. C.M. was funded by a FPI fellowship from MINECO. EB-R was the recipient of fellowships from Fundación Tatiana Pérez de Guzmán el Bueno (Medioambiente 2016) and the FPU program from MECD (FPU16/05513). Short stays of R.R. and C.M. at John Innes Centre were funded by MECD (Salvador de Madariaga and FPU, respectively

Field scale biodegradation of total petroleum hydrocarbons and soil restoration by Ecopiles: microbiological analysis of the process

Ecopiling is a method for biodegradation of hydrocarbons in soils. It derives from Biopiles, but phytoremediation is added to biostimulation with nitrogen fertilization and bioaugmentation with local bacteria. We have constructed seven Ecopiles with soil heavily polluted with hydrocarbons in Carlow (Ireland). The aim of the study was to analyze changes in the microbial community during ecopiling. In the course of 18 months of remediation, total petroleum hydrocarbons values decreased in 99 and 88% on average for aliphatics and aromatics, respectively, indicating a successful biodegradation. Community analysis showed that bacterial alfa diversity (Shannon Index), increased with the degradation of hydrocarbons, starting at an average value of 7.59 and ending at an average value of 9.38. Beta-diversity analysis, was performed using Bray-Curtis distances and PCoA ordination, where the two first principal components (PCs) explain the 17 and 14% of the observed variance, respectively. The results show that samples tend to cluster by sampling time instead of by Ecopile. This pattern is supported by the hierarchical clustering analysis, where most samples from the same timepoint clustered together. We used DSeq2 to determine the differential abundance of bacterial populations in Ecopiles at the beginning and the end of the treatment. While TPHs degraders are more abundant at the start of the experiment, these populations are substituted by bacterial populations typical of clean soils by the end of the biodegradation process. Similar results are found for the fungal community, indicating that the microbial community follows a succession along the process. This succession starts with a TPH degraders or tolerant enriched community, and finish with a microbial community typical of clean soil

Role of extracellular matrix components in biofilm formation and adaptation of Pseudomonas ogarae F113 to the rhizosphere environment

Regulating the transition of bacteria from motile to sessile lifestyles is crucial for their ability to compete effectively in the rhizosphere environment. Pseudomonas are known to rely on extracellular matrix (ECM) components for microcolony and biofilm formation, allowing them to adapt to a sessile lifestyle. Pseudomonas ogarae F113 possesses eight gene clusters responsible for the production of ECM components. These gene clusters are tightly regulated by AmrZ, a major transcriptional regulator that influences the cellular levels of c-di-GMP. The AmrZ-mediated transcriptional regulation of ECM components is primarily mediated by the signaling molecule c-di-GMP and the flagella master regulator FleQ. To investigate the functional role of these ECM components in P. ogarae F113, we performed phenotypic analyses using mutants in genes encoding these ECM components. These analyses included assessments of colony morphology, dye-staining, static attachment to abiotic surfaces, dynamic biofilm formation on abiotic surfaces, swimming motility, and competitive colonization assays of the rhizosphere. Our results revealed that alginate and PNAG polysaccharides, along with PsmE and the fimbrial low molecular weight protein/tight adherence (Flp/Tad) pilus, are the major ECM components contributing to biofilm formation. Additionally, we found that the majority of these components and MapA are needed for a competitive colonization of the rhizosphere in P. ogarae F113

Torque teno sus viruses : pathogenesis in co-infection with Porcine circovirus type 2 and humoral immune responses during natural infection of pigs

A la portada: IRTA, CReSALos Torque teno sus viruses pertenecen a la familia Anelloviridae, e infectan tanto a cerdos como a jabalíes. En la actualidad, los TTSuVs se dividen en dos géneros, Iotatorquevirus para los TTSuV1, que incluye las especies: TTSuV1a y TTSuV1b; y Kappatorquevirus para los TTSuV2, que incluye las especies: TTSuVk2a y TTSuVk2b. Ambos géneros se caracterizan por tener una organización similar del genoma y por una gran variabilidad genética. Las consecuencias de la infección de los TTSuVs sobre su hospedador no son del todo claras. Ambos géneros se detectan con una prevalencia muy alta, tanto en poblaciones de cerdos sanos como enfermos. El virus se transmite principalmente tanto por vía horizontal como vertical; sin embargo, la ruta parenteral también sería posible, ya que se ha detectado la presencia de TTSuVs contaminando productos vacunales veterinarios. Tras la infección, los TTSuVs se distribuyen por la mayoría de los tejidos y órganos del cerdo. Aunque en la actualidad el papel patogénico de los TTSuVs aún no está claro, se cree que estos virus pueden agravar el curso de la enfermedad en asociación con otros patógenos comunes de los cerdos domésticos. Entre los virus concomitantes con los que se asocian destaca el Circovirus porcino tipo 2 (PCV2), responsable de la circovirosis porcina (CP), una enfermedad con consecuencias devastadoras en la población porcina. La relación existente entre los TTSuV y el PCV2 se basa en la mayor prevalencia de los TTSuVs en cerdos afectados por CP comparada con la de cerdos sanos. Sin embargo, la alta prevalencia de los TTSuVs en la población porcina y su alta variabilidad genética, combinados con una alta prevalencia de otros virus que también infectan a los cerdos, constituyen varios obstáculos en la comprensión del papel patogénico asociado a la infección por los TTSuVs. Al mismo tiempo, la falta de herramientas de diagnóstico eficaces ha sido una barrera en el progreso del conocimiento de los TTSuVs. El diagnóstico de la infección de los TTSuV se ha basado principalmente en la detección mediante la técnica de la PCR. El objetivo de los estudios realizados en esta Tesis fue el de contribuir a la comprensión del papel que desempeñan los TTSuVs en la infección del cerdo. Para poder llevarlo a cabo fue necesario desarrollar técnicas de diagnóstico eficaces para estudiar la epidemiología de TTSuVs. En el primer estudio se investigó la dinámica de la infección y la carga viral en suero de los TTSuV1 y TTSuV2. Se seleccionaron sueros de cerdos afectados de CP y, se compararon los valores de carga viral y prevalencia en sueros de cerdos sanos criados en condiciones equivalentes. Para poder llevar a cabo el estudio, previamente se puso a punto una técnica de PCR cuantitativa a tiempo real (qPCR). Se observó que la prevalencia de los TTSuVs era alta en los dos grupos de cerdos estudiados y para los dos virus. En el caso del TTSuV2, la carga viral fue significativamente mayor en los cerdos afectados por la CP. Tal diferencia no se observó en el caso del TTSuV1. También cabe destacar que los cerdos infectados por el TTSuV2 a edades más tempranas (semanas 1 y 3 de vida) fueron más propensos a desarrollar la CP. Por el contrario, dicha correlación no se observó para TTSuV1. En conjunto, los resultados obtenidos refuerzan la hipótesis de la asociación entre la infección por los TTSuVs y el desarrollo de la CP. En el segundo estudio se investigaron las cargas virales tanto del TTSuV1 como del TTSuV2 en tejidos de 20 cerdos (divididos en dos grupos: 10 sanos y 10 afectados por CP). De cada cerdo se investigaron un total de 7 tejidos, incluyendo pulmón, riñón, hígado, íleon, médula ósea, y los nódulos linfáticos mesentéricos y mediastínicos. La determinación de las cargas de TTSuV1 y TTSuV2 en tejidos se llevó a cabo usando la qPCR descrita anteriormente. Las cargas del TTSuV2 fueron significativamente mayores en los tejidos procedentes de cerdos afectados por la CP que en sus homólogos sanos y que las cargas virales del TTSuV1 para ambos grupos de cerdos. Las mayores cargas del TTSuV2 se observaron en la médula ósea, los nódulos linfáticos mediastínicos y en el hígado. Las mayores cargas del TTSuV1 se detectaron en la médula ósea, pulmón e hígado. Independientemente del estado de salud, la médula ósea fue el tejido donde se observaron las cargas virales más altas. En este estudio se concluyó que las cargas de TTSuV2 fueron significativamente mayores que las cargas de TTSuV1 en los tejidos analizados. Además, las cargas de TTSuV2 en tejidos de cerdos afectados por la CP fueron significativamente mayor que las cargas de TTSuV2 en los mismos tejidos procedentes de cerdos sanos. Por último, los TTSuVs se hallaron en un gran número de tejidos diferentes, e incluso es muy probable que otros tejidos que no se incluyeron en este estudio también pudieran estar infectados por TTSuVs. En el tercer estudio se desarrolló una técnica serológica de ELISA basada en la detección de la proteína recombinante ORF1-A de los TTSuVs. Al mismo tiempo, la carga de los TTSuVs en suero se cuantificó usando la qPCR desarrollada previamente. El ensayo ELISA se usó para estudiar el desarrollo de la respuesta inmune humoral frente a TTSuV1 y TTSuV2. Para ello, se realizó un estudio longitudinal en cerdos clínicamente sanos y en sus madres. Se detectaron IgGs anti ORF1-A en las muestras de suero, tanto frente al TTSuV1 como al TTSuV2. En el caso de TTSuV1, se observó una gran prevalencia de cerdos seropositivos en la semana 4 de vida; por el contrario, para el TTSuV2, el porcentaje de cerdos seropositivos en esa semana fue muy bajo. Se concluyó que los cerdos son capaces de desarrollar una respuesta inmune frente a la infección por los TTSuVs; sin embargo, la alta prevalencia de cerdos virémicos en presencia de IgGs anti ORF1-A sugiere que los anticuerpos no son capaces de eliminar los TTSuVs de la sangreTorque teno sus viruses (TTSuVs) belong to the family Anelloviridae and they infect swine and wild boar. Currently, TTSuVs infecting swine are divided into two separated genera, Iotatorquevirus for TTSuV1, including species: TTSuV1a and TTSuV1b, and Kappatorquevirus for TTSuV2, including species TTSuVk2a and TTSuVk2b. Both genera are characterized by similar genomic organization and high genomic variability. The impact of TTSuVs infection for the host is under discussion, since TTSuVs have been detected in high prevalence in healthy and diseased swine populations. Main described transmission routes are horizontal and vertical; nevertheless, the parenteral route is also possible due to the presence of TTSuVs contaminating veterinary vaccine products. In the infected host, TTSuVs are able to infect a variety of tissues and organs. However, the pathogenic role of TTSuVs is not yet clear. It is assumed they can be associated with other well-known swine pathogens, potentially worsening the prognosis of the disease. One of the most studied and harmful viruses in pig production is Porcine circovirus type 2 (PCV2), which is the essential cause of PCV2-systemic disease (PCV2-SD), a devastating disease for the swine industry. In fact, TTSuVs were linked to PCV2-SD triggering, based on the higher prevalence of TTSuVs observed in pigs suffering from PCV2-SD when compared with healthy counterparts. However, the high prevalence of TTSuVs in the swine population, the high genetic variability of TTSuVs, combined with high prevalence of other swine infecting viral pathogens constitute a hindrance in the understanding of the pathogenic role associated to TTSuVs infection. At the same time, the lack of effective diagnostic tools has been a barrier in the understanding of TTSuVs role or biology, as diagnosis of TTSuVs infection has been mainly based on polymerase chain reaction (PCR) detection. The studies carried out in this Thesis aimed to contribute to the understanding of the role played by TTSuVs in the pig. To go further into the study of TTSuVs, it was necessary to develop effective tools to study the epidemiology of TTSuVs. In the first study, the dynamics of TTSuV1 and TTSuV2 loads was studied. For this, serum TTSuV loads of pigs affected by PCV2-SD were compared with appropriate healthy control animals. Such study was carried out by means of a newly developed real-time quantitative PCR (qPCR) method. Results from this study showed that TTSuVs prevalence was high in all studied pigs. TTSuV2 viral load was significantly higher in PCV2-SD affected pigs. Such difference was not observed for TTSuV1. Importantly, it was observed that early TTSuV2 infected pigs were more prone to develop PCV2-SD; on the contrary, such correlation was not observed for TTSuV1. Altogether, obtained data reinforced the hypothesis of the association between TTSuVs infection and PCV2-SD development. In the second study, TTSuV1 and TTSuV2 loads were investigated in tissues of 20 pigs (10 healthy and 10 PCV2-SD affected pigs). For each pig a total of 7 different tissues were analysed, including lung, kidney, liver, ileum, bone marrow, and mesenteric and mediastinal lymph nodes. TTSuV1 and TTSuV2 tissue loads were quantified by the previously developed qPCR. TTSuV2 load was significantly higher in tissues of PCV2-SD affected pigs when compared with healthy counterparts and with TTSuV1 load. For TTSuV2, the highest viral load was observed in bone marrow, mediastinal lymph node and liver, while it was bone marrow, lung and liver for TTSuV1. Regardless of the health status, bone marrow contained the highest viral load. It was observed that TTSuV2 loads in tissues were significantly higher than TTSuV1 tissue loads. Moreover, TTSuV2 tissue load in PCV2-SD affected pigs was significantly higher than TTSuV2 load in tissues of healthy pigs. Finally, TTSuVs had a wide range of tissue distribution, so, it is very likely that other tissues not included in this study would also be infected by TTSuVs. In the third study, Enzyme-Linked ImmunoSorbent Assay (ELISA) assays to detect antibodies against TTSuVs were developed based on the open reading frame (ORF) 1-A recombinant protein of both viruses. Concomitantly, the viral loads in the same examined sera were quantified using the developed qPCR. The ELISA assay was used to study the development of the humoral immune response against TTSuV1 and TTSuV2 in longitudinally sampled clinically healthy pigs and their dams. Anti-ORF1-A IgGs were found in serum of pigs and sows for both TTSuVs. In case of TTSuV1, a high percentage of seropositive pigs were detected at 4 weeks of age; on the contrary, for TTSuV2, percentage of seropositive pigs at the same age was very low. It was concluded that, pigs are able to mount a humoral immune response against TTSuVs. However, based on the high prevalence of viremic pigs in the presence of anti ORF1-A IgGs, it was suggested that these antibodies are not able to remove TTSuVs from blood circulation

Tumor regression and resistance mechanisms upon CDK4 and RAF1 inactivation in KRAS/P53 mutant lung adenocarcinomas.

KRAS mutant lung adenocarcinomas remain intractable for targeted therapies. Genetic interrogation of KRAS downstream effectors, including the MAPK pathway and the interphase CDKs, identified CDK4 and RAF1 as the only targets whose genetic inactivation induces therapeutic responses without causing unacceptable toxicities. Concomitant CDK4 inactivation and RAF1 ablation prevented tumor progression and induced complete regression in 25% of KRAS/p53-driven advanced lung tumors, yet a significant percentage of those tumors that underwent partial regression retained a population of CDK4/RAF1-resistant cells. Characterization of these cells revealed two independent resistance mechanisms implicating hypermethylation of several tumor suppressors and increased PI3K activity. Importantly, these CDK4/RAF1-resistant cells can be pharmacologically controlled. These studies open the door to new therapeutic strategies to treat KRAS mutant lung cancer, including resistant tumors.We thank S. Ortega for the generation of the Cdk4FxKD mouse model; and M. San Roman, R. Villar, M. C. Gonzalez, A. Lopez, N. Cabrera, P. Villanueva, J. Condo, J. Klett, A. Cebria, A. Otero, O. Dominguez, G. Luengo, G. Garaulet, F. Mulero, and D. Megias for excellent technical support. This work was supported by European Research Council Grant ERC-2015-AdG/695566, THERACAN, Spanish Ministry of Science, Innovation, and Universities Grant RTC-2017-6576-1, and the Autonomous Community of Madrid Grant B2017/BMD-3884 iLUNG-CM (to M.B.); Spanish Ministry of Science, Innovation, and Universities Grant RTI2018-094664B-I00 (to M.B. and M.M.); and National Natural Science Foundation of China Grant 31771469 (to H.W.). M.B. is a recipient of an Endowed Chair from the AXA Research Fund. L.E.-B. is the recipient of an FPI fellowship from the Spanish Ministry of Economy and Competitiveness. F.F.-G., M.S., and P.N. were supported by an FPU fellowships from the Spanish Ministry of Education.S

LipoDDx: a mobile application for identification of rare lipodystrophy syndromes

BACKGROUND: Lipodystrophy syndromes are a group of disorders characterized by a loss of adipose tissue once other situations of nutritional deprivation or exacerbated catabolism have been ruled out. With the exception of the HIV-associated lipodystrophy, they have a very low prevalence, which together with their large phenotypic heterogeneity makes their identification difficult, even for endocrinologists and pediatricians. This leads to significant delays in diagnosis or even to misdiagnosis. Our group has developed an algorithm that identifies the more than 40 rare lipodystrophy subtypes described to date. This algorithm has been implemented in a free mobile application, LipoDDx(R). Our aim was to establish the effectiveness of LipoDDx(R). Forty clinical records of patients with a diagnosis of certainty of most lipodystrophy subtypes were analyzed, including subjects without lipodystrophy. The medical records, blinded for diagnosis, were evaluated by 13 physicians, 1 biochemist and 1 dentist. Each evaluator first gave his/her results based on his/her own criteria. Then, a second diagnosis was given using LipoDDx(R). The results were analysed based on a score table according to the complexity of each case and the prevalence of the disease. RESULTS: LipoDDx(R) provides a user-friendly environment, based on usually dichotomous questions or choice of clinical signs from drop-down menus. The final result provided by this app for a particular case can be a low/high probability of suffering a particular lipodystrophy subtype. Without using LipoDDx(R) the success rate was 17 +/- 20%, while with LipoDDx(R) the success rate was 79 +/- 20% (p < 0.01). CONCLUSIONS: LipoDDx(R) is a free app that enables the identification of subtypes of rare lipodystrophies, which in this small cohort has around 80% effectiveness, which will be of help to doctors who are not experts in this field. However, it will be necessary to analyze more cases in order to obtain a more accurate efficiency value

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data