Inferring the immune response from repertoire sequencing

High-throughput sequencing of B- and T-cell receptors makes it possible to track immune repertoires across time, in different tissues, and in acute and chronic diseases or in healthy individuals. However, quantitative comparison between repertoires is confounded by variability in the read count of each receptor clonotype due to sampling, library preparation, and expression noise. Here, we present a general Bayesian approach to disentangle repertoire variations from these stochastic effects. Using replicate experiments, we first show how to learn the natural variability of read counts by inferring the distributions of clone sizes as well as an explicit noise model relating true frequencies of clones to their read count. We then use that null model as a baseline to infer a model of clonal expansion from two repertoire time points taken before and after an immune challenge. Applying our approach to yellow fever vaccination as a model of acute infection in humans, we identify candidate clones participating in the response

Function-Based Rhizosphere Assembly along a Gradient of Desiccation in the Former Aral Sea

The desiccation of the Aral Sea represents one of the largest human-made environmental regional disasters. The salt- and toxin-enriched dried-out basin provides a natural laboratory for studying ecosystem functioning and rhizosphere assembly under extreme anthropogenic conditions. Here, we investigated the prokaryotic rhizosphere communities of the native pioneer plant Suaeda acuminata (C.A.Mey.) Moq. in comparison to bulk soil across a gradient of desiccation (5, 10, and 40 years) by metagenome and amplicon sequencing combined with quantitative PCR (qPCR) analyses. The rhizosphere effect was evident due to significantly higher bacterial abundances but less diversity in the rhizosphere compared to bulk soil. Interestingly, in the highest salinity (5 years of desiccation), rhizosphere functions were mainly provided by archaeal communities. Along the desiccation gradient, we observed a significant change in the rhizosphere microbiota, which was reflected by (i) a decreasing archaeon-bacterium ratio, (ii) replacement of halophilic archaea by specific plant-associated bacteria, i.e., Alphaproteobacteria and Actinobacteria, and (iii) an adaptation of specific, potentially plant-beneficial biosynthetic pathways. In general, both bacteria and archaea were found to be involved in carbon cycling and fixation, as well as methane and nitrogen metabolism. Analysis of metagenome-assembled genomes (MAGs) showed specific signatures for production of osmoprotectants, assimilatory nitrate reduction, and transport system induction. Our results provide evidence that rhizosphere assembly by cofiltering specific taxa with distinct traits is a mechanism which allows plants to thrive under extreme conditions. Overall, our findings highlight a function-based rhizosphere assembly, the importance of plant-microbe interactions in salinated soils, and their exploitation potential for ecosystem restoration approaches

Molecularly defined diffuse leptomeningeal glioneuronal tumor (DLGNT) comprises two subgroups with distinct clinical and genetic features

Diffuse leptomeningeal glioneuronal tumors (DLGNT) represent rare CNS neoplasms which have been included in the 2016 update of the WHO classification. The wide spectrum of histopathological and radiological features can make this enigmatic tumor entity difficult to diagnose. In recent years, large-scale genomic and epigenomic analyses have afforded insight into key genetic alterations occurring in multiple types of brain tumors and provide unbiased, complementary tools to improve diagnostic accuracy. Through genome-wide DNA methylation screening of > 25,000 tumors, we discovered a molecularly distinct class comprising 30 tumors, mostly diagnosed histologically as DLGNTs. Copy-number profiles derived from the methylation arrays revealed unifying characteristics, including loss of chromosomal arm 1p in all cases. Furthermore, this molecular DLGNT class can be subdivided into two subgroups [DLGNT methylation class (MC)-1 and DLGNT methylation class (MC)-2], with all DLGNT-MC-2 additionally displaying a gain of chromosomal arm 1q. Co-deletion of 1p/19q, commonly seen in IDH-mutant oligodendroglioma, was frequently observed in DLGNT, especially in DLGNT-MC-1 cases. Both subgroups also had recurrent genetic alterations leading to an aberrant MAPK/ERK pathway, with KIAA1549:BRAF fusion being the most frequent event. Other alterations included fusions of NTRK1/2/3 and TRIM33:RAF1, adding up to an MAPK/ERK pathway activation identified in 80% of cases. In the DLGNT-MC-1 group, age at diagnosis was significantly lower (median 5 vs 14 years, p < 0.01) and clinical course less aggressive (5-year OS 100, vs 43% in DLGNT-MC-2). Our study proposes an additional molecular layer to the current histopathological classification of DLGNT, of particular use for cases without typical morphological or radiological characteristics, such as diffuse growth and radiologic leptomeningeal dissemination. Recurrent 1p deletion and MAPK/ERK pathway activation represent diagnostic biomarkers and therapeutic targets, respectively—laying the foundation for future clinical trials with, e.g., MEK inhibitors that may improve the clinical outcome of patients with DLGNT

Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins

T-cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remains a major challenge. Here we developed a statistical framework to detect TCR clone proliferation and contraction from longitudinal repertoire data. We applied this framework to data from three pairs of identical twins immunized with the yellow fever vaccine. We identified 500-1500 responding TCRs in each donor and validated them using three independent assays. While the responding TCRs were mostly private, albeit with higher overlap between twins, they could be well predicted using a classifier based on sequence similarity. Our method can also be applied to samples obtained post-infection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations

Studies of the mass composition of cosmic rays and proton-proton interaction cross-sections at ultra-high energies with the Pierre Auger Observatory

In this work, we present an estimate of the cosmic-ray mass composition from the distributions of the depth of the shower maximum (Xmax) measured by the fluorescence detector of the Pierre Auger Observatory. We discuss the sensitivity of the mass composition measurements to the uncertainties in the properties of the hadronic interactions, particularly in the predictions of the particle interaction cross-sections. For this purpose, we adjust the fractions of cosmic-ray mass groups to fit the data with Xmax distributions from air shower simulations. We modify the proton-proton cross-sections at ultra-high energies, and the corresponding air shower simulations with rescaled nucleus-air cross-sections are obtained via Glauber theory. We compare the energy-dependent composition of ultra-high-energy cosmic rays obtained for the different extrapolations of the proton-proton cross-sections from low-energy accelerator data

Study of downward Terrestrial Gamma-ray Flashes with the surface detector of the Pierre Auger Observatory

The surface detector (SD) of the Pierre Auger Observatory, consisting of 1660 water-Cherenkov detectors (WCDs), covers 3000 km2 in the Argentinian pampa. Thanks to the high efficiency of WCDs in detecting gamma rays, it represents a unique instrument for studying downward Terrestrial Gamma-ray Flashes (TGFs) over a large area. Peculiar events, likely related to downward TGFs, were detected at the Auger Observatory. Their experimental signature and time evolution are very different from those of a shower produced by an ultrahigh-energy cosmic ray. They happen in coincidence with low thunderclouds and lightning, and their large deposited energy at the ground is compatible with that of a standard downward TGF with the source a few kilometers above the ground. A new trigger algorithm to increase the TGF-like event statistics was installed in the whole array. The study of the performance of the new trigger system during the lightning season is ongoing and will provide a handle to develop improved algorithms to implement in the Auger upgraded electronic boards. The available data sample, even if small, can give important clues about the TGF production models, in particular, the shape of WCD signals. Moreover, the SD allows us to observe more than one point in the TGF beam, providing information on the emission angle

Radio Interferometry applied to air showers recorded by the Auger Engineering Radio Array

A new radio interferometric technique was recently developed that takes into account time lags caused by the three-dimensional dependency of the refractive index in the atmosphere. It enables us to track the extensive air shower while it propagates through the atmosphere. Using this technique, properties of the air shower can be estimated, like the depth of maximum and the axis of propagation. In order to apply this method, strict constraints on the time-synchronisation between radio antennas in an array must be satisfied. In this contribution, we show that the Auger Engineering Radio Array can meet these timing criteria by operating a time reference beacon. We will show how this enables us to reconstruct air shower properties using the radio interferometric technique