High-Quality Library Preparation for NGS-Based Immunoglobulin Germline Gene Inference and Repertoire Expression Analysis

Next generation sequencing (NGS) of immunoglobulin (Ig) repertoires (Rep-seq) enables examination of the adaptive immune system at an unprecedented level. Applications include studies of expressed repertoires, gene usage, somatic hypermutation levels, Ig lineage tracing and identification of genetic variation within the Ig loci through inference methods. All these applications require starting libraries that allow the generation of sequence data with low error rate and optimal representation of the expressed repertoire. Here, we provide detailed protocols for the production of libraries suitable for human Ig germline gene inference and Ig repertoire studies. Various parameters used in the process were tested in order to demonstrate factors that are critical to obtain high quality libraries. We demonstrate an improved 5′RACE technique that reduces the length constraints of Illumina MiSeq based Rep-seq analysis but allows for the acquisition of sequences upstream of Ig V genes, useful for primer design. We then describe a 5′ multiplex method for library preparation, which yields full length V(D)J sequences suitable for genotype identification and novel gene inference. We provide comprehensive sets of primers targeting IGHV, IGKV, and IGLV genes. Using the optimized protocol, we produced IgM, IgG, IgK, and IgL libraries and analyzed them using the germline inference tool IgDiscover to identify expressed germline V alleles. This process additionally uncovered three IGHV, one IGKV, and six IGLV novel alleles in a single individual, which are absent from the IMGT reference database, highlighting the need for further study of Ig genetic variation. The library generation protocols presented here enable a robust means of analyzing expressed Ig repertoires, identifying novel alleles and producing individualized germline gene databases from humans

The effects of long-term saturated fat enriched diets on the brain lipidome

The brain is highly enriched in lipids, where they influence neurotransmission, synaptic plasticity and inflammation. Non-pathological modulation of the brain lipidome has not been previously reported and few studies have investigated the interplay between plasma lipid homeostasis relative to cerebral lipids. This study explored whether changes in plasma lipids induced by chronic consumption of a well-tolerated diet enriched in saturated fatty acids (SFA) was associated with parallel changes in cerebral lipid homeostasis. Male C57Bl/6 mice were fed regular chow or the SFA diet for six months. Plasma, hippocampus (HPF) and cerebral cortex (CTX) lipids were analysed by LC-ESI-MS/MS. A total of 348 lipid species were determined, comprising 25 lipid classes. The general abundance of HPF and CTX lipids was comparable in SFA fed mice versus controls, despite substantial differences in plasma lipid-class abundance. However, significant differences in 50 specific lipid species were identified as a consequence of SFA treatment, restricted to phosphatidylcholine (PC), phosphatidylethanolamine (PE), alkyl-PC, alkenyl-PC, alkyl-PE, alkenyl-PE, cholesterol ester (CE), diacylglycerol (DG), phosphatidylinositol (PI) and phosphatidylserine (PS) classes. Partial least squares regression of the HPF/CTX lipidome versus plasma lipidome revealed the plasma lipidome could account for a substantial proportion of variation. The findings demonstrate that cerebral abundance of specific lipid species is strongly associated with plasma lipid homeostasis

Normative productivity of the global vegetation

<p>Abstract</p> <p>Background</p> <p>The biosphere models of terrestrial productivity are essential for projecting climate change and assessing mitigation and adaptation options. Many of them have been developed in connection to the International Geosphere-Biosphere Program (IGBP) that backs the work of the Intergovernmental Panel on Climate Change (IPCC). In the end of 1990s, IGBP sponsored release of a data set summarizing the model outputs and setting certain norms for estimates of terrestrial productivity. Since a number of new models and new versions of old models were developed during the past decade, these normative data require updating.</p> <p>Results</p> <p>Here, we provide the series of updates that reflects evolution of biosphere models and demonstrates evolutional stability of the global and regional estimates of terrestrial productivity. Most of them fit well the long-living Miami model. At the same time we call attention to the emerging alternative: the global potential for net primary production of biomass may be as high as 70 PgC y^-1, the productivity of larch forest zone may be comparable to the productivity of taiga zone, and the productivity of rain-green forest zone may be comparable to the productivity of tropical rainforest zone.</p> <p>Conclusion</p> <p>The departure from Miami model's worldview mentioned above cannot be simply ignored. It requires thorough examination using modern observational tools and techniques for model-data fusion. Stability of normative knowledge is not its ultimate goal – the norms for estimates of terrestrial productivity must be evidence-based.</p

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

The carbon balance of an old-growth forest: building across approaches. Ecosystems 7:525–3345 .

ABSTRACT The carbon budget of the Wind River old-growth forest is being addressed from a variety of perspectives and with a range of approaches. The goal of this comprehensive analysis is developing a thorough, general, and validated understanding of the carbon balance, as well as the processes controlling it. The initial results from studies addressing annual carbon (C) balance with ground-based methods, eddy flux, leaf-based models, and ecosystem models are consistent in some, but not all, respects. Net primary production is 500-600 g C m )2 y )1 (5-6 Mg C ha )1 y )1 ), consistent with estimates based on climate alone. The site appears to be close to carbon equilibrium, as a multiyear average, using ground-based methods but a sink of approximately 150-190 g C m )2 y )1 from eddy flux for a single year. An overview of the mechanisms that can drive forest carbon sinks illustrates why methods emphasizing different temporal and spatial scales, as well as different processes, can come to different conclusions, and it highlights opportunities in moving toward a truly integrated approach

Radiative transfer modeling of direct and diffuse sunlight in a Siberian pine forest

We have expanded the Monte Carlo, ray-tracing model FLIGHT in order to simulate photosynthesis within three-dimensional, heterogeneous tree canopies. In contrast to the simple radiative transfer schemes adopted in many land-surface models (e.g., the Big Leaf approximation), our simulation calculates explicitly the leaf irradiance at different heights within the canopy and thus produces an accurate scale-up in photosynthesis from leaf to canopy level. We also account for both diffuse and direct sunlight. For a Siberian stand of Scots pine Pinus sylvestris, FLIGHT predicts observed carbon assimilation, across the full range of sky radiance, with an r.m.s. error of 12%. Our main findings for this sparse canopy, using both measurements and model, are as follows: (1) Observationally, we detect a light-use efficiency (LUE) increase of only ≤10% for the canopy when the proportion of diffuse sky radiance is 75% rather than 25%. The corresponding enhancement predicted by our simulations is 10–20%. With such small increases in LUE, our site will not assimilate more carbon on overcast days compared to seasonally equivalent sunny days; (2) the scale-up in photosynthesis from top-leaf to canopy is less than unity. The Big Leaf approximation, based on Beer's law and light-acclimated leaf nitrogen, overpredicts this scale-up by ≥60% for low sky radiance (≤500 μmolPAR m−2 s−1); (3) when leaf nitrogen is distributed so as to maximize canopy photosynthesis, the increase in the canopy carbon assimilation, compared with a uniform nitrogen distribution, is small (≅4%). Maximum assimilation occurs when the vertical gradient of leaf nitrogen is slightly shallower than that of the light profile

Immunoglobulin M libraries for two donors

D19 and D46 human Immunoglobulin M (IgM) libraries, sequenced by Illumina Miseq and publised in the paper titled Adaptive immune receptor genotyping using the corecount program. The D19 and D46 datasets consists of bulk sequencing data from IgM libraries obtained by IgM specific cDNA synthesis and sequencing in forward and reverse directions using the Illumina MiSeq platform (2 x 300 bp kit).  Further details will be available in Narang et al., 2023 (doi: 10.3389/fimmu.2023.1125884) </p