The role of auxin during early berry development in grapevine as revealed by transcript profiling from pollination to fruit set

Auxin is a key phytohormone that modulates fruit formation in many fleshy fruits through the regulation of cell division and expansion. Auxin content rapidly increases after pollination and the manipulation in its levels may lead to the parthenocarpic development. ln Vitis vinifera L., little is known about the early fruit development that encompasses from pollination to fruit set. Pollination/fertilization events trigger fruit formation, and auxin treatment mimics their effect in grape berry set. However, the role of auxin in this process at the molecular level is not well understood. To elucidate the participation of auxin in grapevine fruit formation, morphological, reproductive, and molecular events from anthesis to fruit set were described in sequential days after pollination. Exploratory RNA-seq analysis at four time points from anthesis to fruit set revealed that the highest percentage of genes induced/repressed within the hormone-related gene category were auxin-related genes. Transcript profiling showed significant transcript variations in auxin signaling and homeostasis-related genes during the early fruit development. Indole acetic acid and several auxin metabolites were present during this period. Finally, application of an inhibitor of auxin action reduced cell number and the mesocarp diameter, similarly to unpollinated berries, further confirming the key role of auxin during early berry development. This work sheds light into the molecular features of the initial fruit development and highlights the auxin participation during this stage in grapevine

Fault interactions in a complex fault system: insight from the 1936-1997 NE Lut earthquake sequence

International audienceCalculations of Coulomb stress changes have shown that moderate to large earthquakes mayincrease stress at the location of future earthquakes. Coulomb stress transfers have thus beenwidely accepted to explain earthquake sequences, especially for sequences occurring withinparallel or collinear fault systems. Relating, under this framework, successive earthquakes occurringwithin more complex fault systems (i.e. conjugate fault system) is more challenging.In this study, we assess which ingredients of the Coulomb stress change theory are decisive forexplaining the succession of three large (Mw7+) earthquakes that occurred on a conjugate faultsystem in the NE Lut, East Iran, during a 30-year period. These earthquakes belong to a largerseismic sequence made up of 11 earthquakes (Mw5.9+) from 1936 to 1997. To reach our goal,we calculate, at each earthquake date, the stress changes generated by the static deformationof the preceding earthquakes, the following postseismic deformation due to the viscoelasticrelaxation of the lithosphere, and the interseismic deformation since 1936. We first show thataccurately modelling the source and receiver fault geometry is crucial to precisely estimatingCoulomb stress changes. Then we show that 7 out of 10 earthquakes of the NE Lut sequence,considering the uncertainties, are favoured by the previous earthquakes. Furthermore, the lasttwo M7+ earthquakes of the sequence (1979 and 1997) have mainly been favoured by the moderate Mw 6 earthquakes. Finally, we investigate the link between the Coulomb stresschanges due to previous earthquakes and the rupture extension of the next earthquake and showthat a correlation does exist for some earthquakes but is not systematic

Earthquake sequence in the NE Lut, Iran: observations from multiple space geodetic techniques

International audienceAn increasing number of observations supports temporal clustering behaviour of earthquakes within fault systems. As earthquake occurrence is mainly controlled by the crustal stresses, it is crucial to determine their spatio-temporal evolution to understand the generation of catastrophic seismic sequences. A possible way to constrain these variations is to measure the surface displacement field induced by seismic sequences. However, the observation time of modern satellite geodesy (InSAR/GPS) is short compared to the duration of an earthquake sequence. Thus, the goal of this paper is to extend the temporal range of observations of a seismic sequence. We focus on the largest earthquakes of the 1936–1997, Northeast Lut, Iran, sequence that is composed of 11  Mw ≧ ∼ 6 earthquakes. Using subpixel correlation of historic (KH9) and recent (Sentinel-2) optical satellite images, we measure for the first time the surface displacement field of the 1979 Mw  7.1 Khuli-Boniabad earthquake, which broke the eastern part of the Dasht-e-Bayaz fault. Using subpixel correlation of optical (SPOT2-4) and SAR (JERS-2) images, we also measure the surface displacement field of the Mw 7.2 Zirkuh earthquake, which ruptured the Abiz fault. We found that both earthquakes have a mean slip of 2.5  m but the Khuli-Boniabad earthquake broke two main segments (total rupture ∼ 60  km), whereas the Zirkuh earthquake broke three main segments (total rupture ∼ 125 km). We suggest that the differences are controlled by the maturity of the faults, the Dasht-e-Bayaz fault being less mature than the Abiz fault. Furthermore, we succeed to measure offsets up to 2.60  m for the 1979 Mw 6.6 Korizan earthquake that broke the northern part of the Abiz fault. It is the first time that the surface displacement field for such a small historic earthquake has been measured using optical correlation. Finally, our study confirms the potential of historical optical imagery for retrieving surface displacements for past earthquakes (pre-modern geodesy era)

A new multilayered visco-elasto-plastic experimental model to study strike-slip fault seismic cycle

International audienceNowadays, technological advances in satellite imagery measurements as well as the development of dense geodetic and seismologic networks allow for a detailed analysis of surface deformation associated with active fault seismic cycle. However, the study of earthquake dynamics faces several limiting factors related to the difficulty to access the deep source of earthquake and to integrate the characteristic time scales of deformation processes that extend from seconds to thousands of years. To overcome part of these limitations and better constrain the role and couplings between kinematic and mechanical parameters, we have developed a new experimental approach allowing for the simulation of strike-slip fault earthquakes and analyze in detail hundreds of successive seismic cycle. Model rheology is made of multilayered visco-elasto-plastic analog materials to account for the mechanical behavior of the upper and lower crust and to allow simulating brittle/ductile coupling, postseismic deformation phase and far-field stress transfers. The kinematic evolution of the model surface is monitored using an optical system, based on subpixel spectral correlation of high-resolution digital images. First, results show that the model succeed in reproducing the deformation mechanisms and surface kinematics associated to the main phases of the seismic cycle indicating that model scaling is satisfactory. These results are comforted by using numerical algorithms to study the strain and stress distribution at the surface and at depth, along the fault plane. Our analog modeling approach appears, then, as an efficient complementary approach to investigate earthquake dynamics

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.