Additional file 6. Comparison of D. discoideum genes regulated in response to pathogenic bacteria and food bacteria. Regulation and description of genes included in Fig. 6.
Abstract Recent advances in long-read sequencing technology enable its use in potentially life-saving applications for rapid clinical diagnostics and epidemiological monitoring. To take advantage of these enabling characteristics, we present Voyager , a novel algorithm that complements real-time sequencing by rapidly and efficiently mapping long sequencing reads with insertion- and deletion errors to a large set of reference genomes. The concept of Sorted Motif Distance Space ( SMDS ), i.e., distances between exact matches of short motifs sorted by rank, represents sequences and sequence complementarity in a highly compressed form and is thus computationally efficient while enabling strain-level discrimination. In addition, Voyager applies a deconvolution algorithm rather than reducing taxonomic resolution if sequences of closely related organisms cannot be discerned by SMDS alone. Using relevant real-world data, we evaluated Voyager against the current best taxonomic classification methods (Kraken 2 and Centrifuge). Voyager was on average more than twice as fast as the current fastest method and obtained on average over 40% higher species level accuracy while maintaining lower memory usage than both other methods.
Vishvanath Nene,* Jennifer R. Wortman, Daniel Lawson, Brian Haas, Chinnappa Kodira, Zhijian (Jake) Tu, Brendan Loftus, Zhiyong Xi, Karyn Megy, Manfred Grabherr, Quinghu Ren, Evgeny M. Zdobnov, Neil F. Lobo, Kathryn S. Campbell, Susan E. Brown, Maria F. Bonaldo, Jingsong Zhu, Steven P. Sinkins, David G. Hogenkamp, Paolo Amedo, Peter Arensburger, Peter W. Atkinson, Shelby Bidwell, Jim Biedler, Ewan Birney, Robert V. Bruggner, Javier Costas, Monique R. Coy, Jonathan Crabtree, Matt Crawford, Becky deBruyn, David DeCaprio, Karin Eiglmeier, Eric Eisenstadt, Hamza El-Dorry, William M. Gelbart, Suely L. Gomes, Martin Hammond, Linda I. Hannick, James R. Hogan, Michael H. Holmes, David Jaffe, J. Spencer Johnston, Ryan C. Kennedy, Hean Koo, Saul Kravitz, Evgenia V. Kriventseva, David Kulp, Kurt LaButti, Eduardo Lee, Song Li, Diane D. Lovin, Chunhong Mao, Evan Mauceli, Carlos F. M. Menck, Jason R. Miller, Philip Montgomery, Akio Mori, Ana L. Nascimento, Horacio F. Naveira, Chad Nusbaum, Sinead O’Leary, Joshua Orvis, Mihaela Pertea, Hadi Quesneville, Kyanne R. Reidenbach, Yu-Hui Rogers, Charles W. Roth, Jennifer R. Schneider, Michael Schatz, Martin Shumway, Mario Stanke, Eric O. Stinson, Jose M. C. Tubio, Janice P. VanZee, Sergio VerjovskiAlmeida, Doreen Werner, Owen White, Stefan Wyder, Qiandong Zeng, Qi Zhao, Yongmei Zhao, Catherine A. Hill, Alexander S. Raikhel, Marcelo B. Soares, Dennis L. Knudson, Norman H. Lee, James Galagan, Steven L. Salzberg, Ian T. Paulsen, George Dimopoulos, Frank H. Collins, Bruce Birren, Claire M. Fraser-Liggett, David W. Severson*
Whole genome sequencing (WGS) is a very valuable resource to understand the evolutionary history of poorly known species. However, in organisms with large genomes, as most amphibians, WGS is still excessively challenging and transcriptome sequencing (RNA-seq) represents a cost-effective tool to explore genome-wide variability. Non-model organisms do not usually have a reference genome and the transcriptome must be assembled de-novo. We used RNA-seq to obtain the transcriptomic profile for Oreobates cruralis, a poorly known South American direct-developing frog. In total, 550,871 transcripts were assembled, corresponding to 422,999 putative genes. Of those, we identified 23,500, 37,349, 38,120 and 45,885 genes present in the Pfam, EggNOG, KEGG and GO databases, respectively. Interestingly, our results suggested that genes related to immune system and defense mechanisms are abundant in the transcriptome of O. cruralis. We also present a pipeline to assist with pre-processing, assembling, evaluating and functionally annotating a de-novo transcriptome from RNA-seq data of non-model organisms. Our pipeline guides the inexperienced user in an intuitive way through all the necessary steps to build de-novo transcriptome assemblies using readily available software and is freely available at: https://github.com/biomendi/TRANSCRIPTOME-ASSEMBLY-PIPELINE/wiki.
A deeper understanding of microbial communities associated with plants is revealing their importance for plant health and productivity. RNA extracted from plant field samples represents the host and other organisms present.
Generating polygenic risk scores for diseases and complex traits requires high quality GWAS summary statistic files. Often, these files can be difficult to acquire either as a result of unshared or incomplete data. To date, bioinformatics tools which focus on restoring missing columns containing identification and association data are limited, which has the potential to increase the number of usable GWAS summary statistics files.SumStatsRehab was able to restore rsID, effect/other alleles, chromosome, base pair position, effect allele frequencies, beta, standard error, and p-values to a better extent than any other currently available tool, with minimal loss.SumStatsRehab offers a unique tool utilizing both functional programming and pipeline-like architecture, allowing users to generate accurate data restorations for incomplete summary statistics files. This in turn, increases the number of usable GWAS summary statistics files, which may be invaluable for less researched health traits.
Candida species are the most common cause of opportunistic fungal infection worldwide. Here we report the genome sequences of six Candida species and compare these and related pathogens and non-pathogens. There are significant expansions of cell wall, secreted and transporter gene families in pathogenic species, suggesting adaptations associated with virulence. Large genomic tracts are homozygous in three diploid species, possibly resulting from recent recombination events. Surprisingly, key components of the mating and meiosis pathways are missing from several species. These include major differences at the mating-type loci (MTL); Lodderomyces elongisporus lacks MTL, and components of the a1/α2 cell identity determinant were lost in other species, raising questions about how mating and cell types are controlled. Analysis of the CUG leucine-to-serine genetic-code change reveals that 99% of ancestral CUG codons were erased and new ones arose elsewhere. Lastly, we revise the Candida albicans gene catalogue, identifying many new genes. The genome sequences of six Candida species have been determined, and compared with those of Candida albicans, a marine yeast and baker's yeast. Candida species are the most common cause of opportunistic fungal infection in humans. The genomic comparisons reveal striking gene family expansions associated with pathogenic species. Other aspects of Candida biology, including evolution of the genetic code, and the architecture of mating and meiotic processes, can also be addressed in the interspecies comparisons. Candida species are the most common cause of opportunistic fungal infection worldwide. Here, the genomes of six Candida species are sequenced and compared with each other and with related pathogens and non-pathogens; providing insight into the genetic features that underlie the diversity of Candida biology, including pathogenesis and the architecture of mating and meiotic processes.
ABSTRACT Type-2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from a cohort of 43 multi-organ donors. The intra-individual analysis was assessed across five key-metabolic tissues (serum, adipose tissue, liver, pancreatic islets and muscle), and the inter-individual across three different groups reflecting T2D progression. We identified 92 metabolites differing significantly between non-diabetes and T2D subjects. Carnitines were significantly higher in liver, while lysophosphatidylcholines significantly lower in muscle and serum. An investigation of the progression to overt T2D showed that deoxycholic acid glycine conjugate was significantly higher in liver of pre-diabetes samples while additional increase in T2D was insignificant. A subset of lysophosphatidylcholines were significantly lower in the muscle of pre-diabetes subjects. Overall, the analysis of this unique dataset can increase the understanding of the metabolic interplay between organs in the development of T2D.
Background Giardia intestinalis is a non-invasive protozoan parasite that causes giardiasis in humans, the most common form of parasite-induced diarrhea. Disease mechanisms are not completely defined and very few virulence factors are known. Methodology To identify putative virulence factors and elucidate mechanistic pathways leading to disease, we have used proteomics to identify the major excretory-secretory products (ESPs) when Giardia trophozoites of WB and GS isolates (assemblages A and B, respectively) interact with intestinal epithelial cells (IECs) in vitro. Findings The main parts of the IEC and parasite secretomes are constitutively released proteins, the majority of which are associated with metabolism but several proteins are released in response to their interaction (87 and 41 WB and GS proteins, respectively, 76 and 45 human proteins in response to the respective isolates). In parasitized IECs, the secretome profile indicated effects on the cell actin cytoskeleton and the induction of immune responses whereas that of Giardia showed anti-oxidation, proteolysis (protease-associated) and induction of encystation responses. The Giardia secretome also contained immunodominant and glycosylated proteins as well as new candidate virulence factors and assemblage-specific differences were identified. A minor part of Giardia ESPs had signal peptides (29% for both isolates) and extracellular vesicles were detected in the ESPs fractions, suggesting alternative secretory pathways. Microscopic analyses showed ESPs binding to IECs and partial internalization. Parasite ESPs reduced ERK1/2 and P38 phosphorylation and NF-κB nuclear translocation. Giardia ESPs altered gene expression in IECs, with a transcriptional profile indicating recruitment of immune cells via chemokines, disturbances in glucose homeostasis, cholesterol and lipid metabolism, cell cycle and induction of apoptosis. Conclusions This is the first study identifying Giardia ESPs and evaluating their effects on IECs. It highlights the importance of host and parasite ESPs during interactions and reveals the intricate cellular responses that can explain disease mechanisms and attenuated inflammatory responses during giardiasis.
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