Comparison of the effects of co-transplantation of bone marrow hematopoietic stem cells and thymic multipotent stromal cells on the immune system of mice depending on methods

Physical interaction of multipotent stromal cells (MSCs) and hematopoietic stem cells (HSCs) is a modern approach to effective and focused changes in the properties of HSCs. Resulting of those contact interaction is significant activation of cells with following immune system restoration. The purpose of the study is to investigate the effect of co-transplantation of bone marrow hematopoietic stem cells (HSCs) and thymic multipotent stromal cells (MSCs) separately and as a union of cells on regeneration of the murine immune system, damaged by cyclophosphamide. MSCs were obtained from thymuses of C57BL mice using explant technique. Bone marrow cells (BMCs) were obtained by flushing out the femur with a nutrient medium. BMCs were cocultivated for 2 hours on the monolayer of thymus-derived MSCs. The immune deficiency of mice was modelled by the treatment with cyclophosphamide (CP). After that, the cells were co-transplanted in two methods (separately into different the retroorbital sinus and as a union after co-cultivation) and the parameters of the immune system were evaluated. It was shown, that separate co-transplantation of BMCs and thymus-derived MSCs is associated with the restoration of the number of bone marrow cells, thymus, spleen and lymph nodes with an increase in the proliferation index of lymph node cells by 1.4 times compared to control. It normalized the previous reduced concentration of hemoglobin and hematocrit in the blood. Co-transplantation had a suppressive effect on the blast transformation reaction, induced by phytohemagglutinin, by 4.3 times, but showed a stimulating effect on DTHR response by 1.6 times compared to control. Co-transplantation of the union of BMCs and MSCs is associated with the restoration of the number of bone marrow cells, spleen and lymph nodes. The level of spontaneous apoptosis of lymph node cells significantly increased by 3.3 times compared to control. It had not effect on hematological parameters, but is activated to impact the immune system. Thus, as a result of cells union administration showed normalization of the bactericidal activity of peritoneal macrophages, unlike the separate co-transplantation. This cells graft had a suppressive effect on the number of antibody-producing cells in the spleen by 4.2 times compared to control. Previous co-cultivation and contact interaction of cells change the properties of cell graft. The effect of co-transplantation of BMCs and thymic MSCs is not a simple additive effect of cells. It is acquiring the features typical to certain cell types, and the expression of new characteristics. We assume this phenomenon as a result development of complex cells cooperative processes in vivo and in vitr

Bar coding MS2 spectra for metabolite identification

[Image: see text] Metabolite identifications are most frequently achieved in untargeted metabolomics by matching precursor mass and full, high-resolution MS(2) spectra to metabolite databases and standards. Here we considered an alternative approach for establishing metabolite identifications that does not rely on full, high-resolution MS(2) spectra. First, we select mass-to-charge regions containing the most informative metabolite fragments and designate them as bins. We then translate each metabolite fragmentation pattern into a binary code by assigning 1’s to bins containing fragments and 0’s to bins without fragments. With 20 bins, this binary-code system is capable of distinguishing 96% of the compounds in the METLIN MS(2) library. A major advantage of the approach is that it extends untargeted metabolomics to low-resolution triple quadrupole (QqQ) instruments, which are typically less expensive and more robust than other types of mass spectrometers. We demonstrate a method of acquiring MS(2) data in which the third quadrupole of a QqQ instrument cycles over 20 wide isolation windows (coinciding with the location and width of our bins) for each precursor mass selected by the first quadrupole. Operating the QqQ instrument in this mode yields diagnostic bar codes for each precursor mass that can be matched to the bar codes of metabolite standards. Furthermore, our data suggest that using low-resolution bar codes enables QqQ instruments to make MS(2)-based identifications in untargeted metabolomics with a specificity and sensitivity that is competitive to high-resolution time-of-flight technologies

Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides

Background The laboratory mouse is the most commonly used model for studying variation in complex traits relevant to human disease. Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity. Results We identified small nucleotide variants (SNVs) and structural variants (SVs) in the LG/J and SM/J strains relative to the reference genome and discovered novel variants in these two strains by comparing their sequences to other mouse genomes. We find that 39% of the LG/J and SM/J genomes are identical-by-descent (IBD). We characterized amino-acid changing mutations using three algorithms: LRT, PolyPhen-2 and SIFT. We also identified polymorphisms between LG/J and SM/J that fall in regulatory regions and highly informative transcription factor binding sites (TFBS). We intersected these functional predictions with quantitative trait loci (QTL) mapped in advanced intercrosses of these two strains. We find that QTL are both over-represented in non-IBD regions and highly enriched for variants predicted to have a functional impact. Variants in QTL associated with metabolic (231 QTL identified in an F16 generation) and developmental (41 QTL identified in an F34generation) traits were interrogated and we highlight candidate quantitative trait genes (QTG) and nucleotides (QTN) in a QTL on chr13 associated with variation in basal glucose levels and in a QTL on chr6 associated with variation in tibia length. Conclusions We show how integrating genomic sequence with QTL reduces the QTL search space and helps researchers prioritize candidate genes and nucleotides for experimental follow-up. Additionally, given the LG/J and SM/J phylogenetic context among inbred strains, these data contribute important information to the genomic landscape of the laboratory mouse

The origins and spread of domestic horses from the Western Eurasian steppes

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: All collapsed and paired-end sequence data for samples sequenced in this study are available in compressed fastq format through the European Nucleotide Archive under accession number PRJEB44430, together with rescaled and trimmed bam sequence alignments against both the nuclear and mitochondrial horse reference genomes. Previously published ancient data used in this study are available under accession numbers PRJEB7537, PRJEB10098, PRJEB10854, PRJEB22390 and PRJEB31613, and detailed in Supplementary Table 1. The genomes of ten modern horses, publicly available, were also accessed as indicated in their corresponding original publications57,61,85-87.NOTE: see the published version available via the DOI in this record for the full list of authorsDomestication of horses fundamentally transformed long-range mobility and warfare. However, modern domesticated breeds do not descend from the earliest domestic horse lineage associated with archaeological evidence of bridling, milking and corralling at Botai, Central Asia around 3500 BC. Other longstanding candidate regions for horse domestication, such as Iberia and Anatolia, have also recently been challenged. Thus, the genetic, geographic and temporal origins of modern domestic horses have remained unknown. Here we pinpoint the Western Eurasian steppes, especially the lower Volga-Don region, as the homeland of modern domestic horses. Furthermore, we map the population changes accompanying domestication from 273 ancient horse genomes. This reveals that modern domestic horses ultimately replaced almost all other local populations as they expanded rapidly across Eurasia from about 2000 BC, synchronously with equestrian material culture, including Sintashta spoke-wheeled chariots. We find that equestrianism involved strong selection for critical locomotor and behavioural adaptations at the GSDMC and ZFPM1 genes. Our results reject the commonly held association between horseback riding and the massive expansion of Yamnaya steppe pastoralists into Europe around 3000 BC driving the spread of Indo-European languages. This contrasts with the scenario in Asia where Indo-Iranian languages, chariots and horses spread together, following the early second millennium BC Sintashta culture

Computational Tools to Expand the Coverage of Metabolite Profiling via LC-MS/MS

Metabolite profiling is a recent addition to the suite of high-throughput phenotyping technologies. Unlike measuring gene and protein expression, it is often difficult to anticipate all of the metabolites that are likely to be present in a particular sample. Still, recent efforts to catalog all present metabolites have turned up fewer metabolites than expected. This thesis focuses on one of the common metabolite profiling technologies, LC-MS/MS, and takes two steps to expand the coverage of current metabolite profiling experiments. First, a method to enable collection of MS/MS data from a greater portion of the detected ions is presented. This is done by collecting fragmentation spectra with less stringent ion isolation settings, which provides greater sensitivity at the expense of obtaining fragments from contaminating ions. Those contaminated spectra are then computationally deconvolved, resulting in fragmentation data from ions that would have previously not been considered sufficiently abundant for fragmentation. Second, the design of large-scale triple quadrupole metabolite profiling experiments using the METLIN metabolite database is explored. Likelihoods of obtaining common fragmentation products from each structure in the database are estimated, and are then used to identify ensembles of the most informative fragmentation spectra. The results are encouraging and provide a basis for interpretation of precursor-ion and neutral-loss scanning experiments, as well as a foundation for designing large scale multiple reaction monitoring experiments. With these two additions to the arsenal of LC-MS/MS based metabolite profiling tools, we move closer to one day reaching the goal of global metabolite profiling. In turn, this may lead to exciting discoveries that uncover unknown pockets of human metabolism

GJ: Discriminating precursors of common fragments for large-scale metabolite profiling by triple quadrupole mass spectrometry. Bioinforma Oxf Engl

Abstract Motivation: The goal of large-scale metabolite profiling is to compare the relative concentrations of as many metabolites extracted from biological samples as possible. This is typically accomplished by measuring the abundances of thousands of ions with high-resolution and high mass accuracy mass spectrometers. Although the data from these instruments provide a comprehensive fingerprint of each sample, identifying the structures of the thousands of detected ions is still challenging and time intensive. An alternative, less-comprehensive approach is to use triple quadrupole (QqQ) mass spectrometry to analyze predetermined sets of metabolites (typically fewer than several hundred). This is done using authentic standards to develop QqQ experiments that specifically detect only the targeted metabolites, with the advantage that the need for ion identification after profiling is eliminated. Results: Here, we propose a framework to extend the application of QqQ mass spectrometers to large-scale metabolite profiling. We aim to provide a foundation for designing QqQ multiple reaction monitoring (MRM) experiments for each of the 82 696 metabolites in the METLIN metabolite database. First, we identify common fragmentation products from the experimental fragmentation data in METLIN. Then, we model the likelihoods of each precursor structure in METLIN producing each common fragmentation product. With these likelihood estimates, we select ensembles of common fragmentation products that minimize our uncertainty about metabolite identities. We demonstrate encouraging performance and, based on our results, we suggest how our method can be integrated with future work to develop large-scale MRM experiments. Availability and implementation: Our predictions, Supplementary results, and the code for estimating likelihoods and selecting ensembles of fragmentation reactions are made available on the lab website at http://pattilab.wustl.edu/FragPred