Plasmodium falciparum parasite population structure and gene flow associated to anti-malarial drugs resistance in Cambodia

Background: Western Cambodia is recognized as the epicentre of emergence of Plasmodium falciparum multi-drug resistance. The emergence of artemisinin resistance has been observed in this area since 2008–2009 and molecular signatures associated to artemisinin resistance have been characterized in k13 gene. At present, one of the major threats faced, is the possible spread of Asian artemisinin resistant parasites over the world threatening millions of people and jeopardizing malaria elimination programme efforts. To anticipate the diffusion of artemisinin resistance, the identification of the P. falciparum population structure and the gene flow among the parasite population in Cambodia are essential. Methods: To this end, a mid-throughput PCR-LDR-FMA approach based on LUMINEX technology was developed to screen for genetic barcode in 533 blood samples collected in 2010–2011 from 16 health centres in malaria endemics areas in Cambodia. Results: Based on successful typing of 282 samples, subpopulations were characterized along the borders of the country. Each 11-loci barcode provides evidence supporting allele distribution gradient related to subpopulations and gene flow. The 11-loci barcode successfully identifies recently emerging parasite subpopulations in western Cambodia that are associated with the C580Y dominant allele for artemisinin resistance in k13 gene. A subpopulation was identified in northern Cambodia that was associated to artemisinin (R539T resistant allele of k13 gene) and mefloquine resistance. Conclusions: The gene flow between these subpopulations might have driven the spread of artemisinin resistance over Cambodia

A 60-million-year Cenozoic history of western Amazonian ecosystems in Contamana, eastern Peru

Weprovide a synopsis of ~60million years of life history in Neotropical lowlands, based on a comprehensive survey of the Cenozoic deposits along the Quebrada Cachiyacu near Contamana in PeruvianAmazonia. The 34 fossilbearing localities identified have yielded a diversity of fossil remains, including vertebrates,mollusks, arthropods, plant fossils, and microorganisms, ranging from the early Paleocene to the lateMiocene–?Pliocene (N20 successive levels). This Cenozoic series includes the base of the Huchpayacu Formation (Fm.; early Paleocene; lacustrine/ fluvial environments; charophyte-dominated assemblage), the Pozo Fm. (middle + ?late Eocene; marine then freshwater environments; most diversified biomes), and complete sections for the Chambira Fm. (late Oligocene–late early Miocene; freshwater environments; vertebrate-dominated faunas), the Pebas Fm. (late early to early late Miocene; freshwater environments with an increasing marine influence; excellent fossil record), and Ipururo Fm. (late Miocene–?Pliocene; fully fluvial environments; virtually no fossils preserved). At least 485 fossil species are recognized in the Contamana area (~250 ‘plants’, ~212 animals, and 23 foraminifera). Based on taxonomic lists from each stratigraphic interval, high-level taxonomic diversity remained fairly constant throughout themiddle Eocene–Miocene interval (8-12 classes), ordinal diversity fluctuated to a greater degree, and family/species diversity generally declined, with a drastic drop in the early Miocene. The Paleocene–?Pliocene fossil assemblages from Contamana attest at least to four biogeographic histories inherited from (i) Mesozoic Gondwanan times, (ii) the Panamerican realm prior to (iii) the time of South America’s Cenozoic “splendid isolation”, and (iv) Neotropical ecosystems in the Americas. No direct evidence of any North American terrestrial immigrant has yet been recognized in the Miocene record at Contamana.Facultad de Ciencias Naturales y Muse

Observatoire Scientifique en Appui à la GEstion de la Santé sur un territoire (OSAGE-S)

Dans le contexte « environnement-santé », l’équipe interdisciplinaire (biologistes, médecins, épidémiologistes, modélisateurs, écologues, géographes, informaticiens) qui travaille sur la dynamique de maladies infectieuses dans le Sud-Est asiatique, propose de mettre en commun la connaissance qu’elle a des agents biologiques pathogènes et des processus qui interviennent dans les milieux et les sociétés et de partager expériences de terrain, de laboratoire, clinique pour aborder les questions de recherche, de suivi des maladies et de gestion de la santé. Pour ce faire, l’idée d’une plateforme intégrative a été avancée et nous a permis de décliner la proposition de mise en œuvre d’un Observatoire Scientifique en Appui à la GEstion de la Santé sur un territoire (OSAGE-S). Les prémices de ce travail sont d’une part d’ordre générique et épistémologique : ils explicitent formellement la formule « environnement-santé » pour y positionner le pathosystème, l’environnement et l’observatoire ; d’autre part d’ordre opérationnel par explicitation du concept d’observatoire en appui à la gestion de la Santé. Par la suite nous illustrerons nos propos autour d’OSAGE-S, à partir d’une étude de cas, la maladie du Chikungunya en Indonésie.Within the “Health and Environment” framework, a group of scientists in disciplinary fields as diverse as biology, medical sciences, modelling, ecology, geography, computer sciences, are collaborating to study the dynamics of infectious diseases in Southeast Asia. In this paper they propose to pool their knowledge on biological pathogens, environment and societies and to share their field, laboratory and clinical expertise to address questions on research, disease monitoring and health management. An integrative platform has been suggested and organised in order to implement a Scientific Observatory (OSAGE-S), dedicated to supporting Health Management in a Territory. The first part of this work addresses generic and epistemological questions, formally explicits the formula “Health and Environment” in order to relate it to concepts such as « pathological system », « environment » and « observatory » ; the second part relates to further operational issues for the observatory concept dedicated to the support of Health management. Thereafter we illustrate our proposition with a case study, the Chikungunya disease in Indonesia

South Green bioinformatics platform : Plateforme collaborative de bioinformatique verte héraultaise

Drivers and other road users often encounter situations where priority is unclear or ambiguous, but must be resolved, for example, after arriving at an intersection nearly simultaneously. The participants in such scenarios reach agreement by communicating; while instinctive to humans, this is a significant challenge for autonomous vehicles. Currently, the nature of interaction for resolving ambiguous road situations between pedestrians and autonomous vehicles remains mostly in the realm of speculation, for which no direct means for expressing intent and acknowledgment has yet been established. This thesis approaches the challenge by contributing a model and approach for planning that can produce actions that are expressive and encode certain aspects of intent; the result is communicative in that vehicle-pedestrian coordination arises via a negotiation of intent in a prototypical unsignalized intersection crossing scenario. We deliberately construct a prototypical crossing setting with a vehicle and one pedestrian at an unsignalized intersection such that there is substantial ambiguity in crossing order. A decision-theoretic model is then used for capturing this scenario along with its ambiguity as uncertainty arising from non-determinism and partial observability. We solve the problem by first proposing a Markov decision process to express the interaction at the intersection. Next, we focus on the partial-observability and include it in the model to generate a sequence of vehicle actions by solving via a state-of-the-art online solver. We implement the approach on a self-driving Ford Lincoln MKZ platform and examine an experimental setting involving real-time interaction. The experiment shows that the method achieves safe and efficient navigation. We analyze the resulting policy in detail in simulation and examine the coupled behavior of the vehicle and pedestrian, interpreting evidence for implicit communication that emerges as the two resolve ambiguity to achieve safe and efficient navigation

HLA-DPB1 and HLA Class I Confer Risk of and Protection from Narcolepsy

Correction: AMERICAN JOURNAL OF HUMAN GENETICS Volume: 96 Issue: 5 Pages: 852-852 DOI: 10.1016/j.ajhg.2015.04.001 Published:MAY 7 2015Peer reviewe

Design and selection of optimal ErbB-targeting bispecific antibodies in pancreatic cancer

The ErbB family of receptor tyrosine kinases is a primary target for small molecules and antibodies for pancreatic cancer treatment. Nonetheless, the current treatments for this tumor are not optimal due to lack of efficacy, resistance, or toxicity. Here, using the novel BiXAb™ tetravalent format platform, we generated bispecific antibodies against EGFR, HER2, or HER3 by considering rational epitope combinations. We then screened these bispecific antibodies and compared them with the parental single antibodies and antibody pair combinations. The screen readouts included measuring binding to the cognate receptors (mono and bispecificity), intracellular phosphorylation signaling, cell proliferation, apoptosis and receptor expression, and also immune system engagement assays (antibody-dependent cell-mediated cytotoxicity and complement-dependent cytotoxicity). Among the 30 BiXAbs™ tested, we selected 3Patri-1Cetu-Fc, 3Patri-1Matu-Fc and 3Patri-2Trastu-Fc as lead candidates. The in vivo testing of these three highly efficient bispecific antibodies against EGFR and HER2 or HER3 in pre-clinical mouse models of pancreatic cancer showed deep antibody penetration in these dense tumors and robust tumor growth reduction. Application of such semi-rational/semi-empirical approach, which includes various immunological assays to compare pre-selected antibodies and their combinations with bispecific antibodies, represents the first attempt to identify potent bispecific antibodies against ErbB family members in pancreatic cancer

American Gut: an Open Platform for Citizen Science Microbiome Research

McDonald D, Hyde E, Debelius JW, et al. American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems. 2018;3(3):e00031-18

Application of modular response analysis to medium- to large-size biological systems

International audienceThe development of high-throughput genomic technologies associated with recent genetic perturbation techniques such as short hairpin RNA (shRNA), gene trapping, or gene editing (CRISPR/Cas9) has made it possible to obtain large perturbation data sets. These data sets are invaluable sources of information regarding the function of genes, and they offer unique opportunities to reverse engineer gene regulatory networks in specific cell types. Modular response analysis (MRA) is a well-accepted mathematical modeling method that is precisely aimed at such network inference tasks, but its use has been limited to rather small biological systems so far. In this study, we show that MRA can be employed on large systems with almost 1,000 network components. In particular, we show that MRA performance surpasses general-purpose mutual information-based algorithms. Part of these competitive results was obtained by the application of a novel heuristic that pruned MRA-inferred interactions a posteriori . We also exploited a block structure in MRA linear algebra to parallelize large system resolutions

An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk

International audienceAbstract Modular response analysis (MRA) is a widely used inference technique developed to uncover directions and strengths of connections in molecular networks under a steady-state condition by means of perturbation experiments. We devised several extensions of this methodology to search genomic data for new associations with a biological network inferred by MRA, to improve the predictive accuracy of MRA-inferred networks, and to estimate confidence intervals of MRA parameters from datasets with low numbers of replicates. The classical MRA computations and their extensions were implemented in a freely available R package called aiMeRA ( https://github.com/bioinfo-ircm/aiMeRA/ ) . We illustrated the application of our package by assessing the crosstalk between estrogen and retinoic acid receptors, two nuclear receptors implicated in several hormone-driven cancers, such as breast cancer. Based on new data generated for this study, our analysis revealed potential cross-inhibition mediated by the shared corepressors NRIP1 and LCoR. We designed aiMeRA for non-specialists and to allow biologists to perform their own analyses