• MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples.

      Asgari, Ehsaneddin; Garakani, Kiavash; McHardy, Alice C; Mofrad, Mohammad R K; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Oxford University Press, 2018-07-01)
      Microbial communities play important roles in the function and maintenance of various biosystems, ranging from the human body to the environment. A major challenge in microbiome research is the classification of microbial communities of different environments or host phenotypes. The most common and cost-effective approach for such studies to date is 16S rRNA gene sequencing. Recent falls in sequencing costs have increased the demand for simple, efficient and accurate methods for rapid detection or diagnosis with proved applications in medicine, agriculture and forensic science. We describe a reference- and alignment-free approach for predicting environments and host phenotypes from 16S rRNA gene sequencing based on k-mer representations that benefits from a bootstrapping framework for investigating the sufficiency of shallow sub-samples. Deep learning methods as well as classical approaches were explored for predicting environments and host phenotypes. A k-mer distribution of shallow sub-samples outperformed Operational Taxonomic Unit (OTU) features in the tasks of body-site identification and Crohn's disease prediction. Aside from being more accurate, using k-mer features in shallow sub-samples allows (i) skipping computationally costly sequence alignments required in OTU-picking and (ii) provided a proof of concept for the sufficiency of shallow and short-length 16S rRNA sequencing for phenotype prediction. In addition, k-mer features predicted representative 16S rRNA gene sequences of 18 ecological environments, and 5 organismal environments with high macro-F1 scores of 0.88 and 0.87. For large datasets, deep learning outperformed classical methods such as Random Forest and Support Vector Machine. The software and datasets are available at https://llp.berkeley.edu/micropheno. Supplementary data are available at Bioinformatics online.
    • Modular Traits of the Rhizobiales Root Microbiota and Their Evolutionary Relationship with Symbiotic Rhizobia.

      Garrido-Oter, Ruben; Nakano, Ryohei Thomas; Dombrowski, Nina; Ma, Ka-Wai; McHardy, Alice C; Schulze-Lefert, Paul; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Elsevier, 2018-07-11)
      Animal-microbe facultative symbioses play a fundamental role in ecosystem and organismal health. Yet, due to the flexible nature of their association, the selection pressures that act on animals and their facultative symbionts remain elusive. Here we apply experimental evolution to Drosophila melanogaster associated with its growth-promoting symbiont Lactobacillus plantarum, representing a well-established model of facultative symbiosis. We find that the diet of the host, rather than the host itself, is a predominant driving force in the evolution of this symbiosis. Furthermore, we identify a mechanism resulting from the bacterium's adaptation to the diet, which confers growth benefits to the colonized host. Our study reveals that bacterial adaptation to the host's diet may be the foremost step in determining the evolutionary course of a facultative animal-microbe symbiosis.
    • Novel Syntrophic Populations Dominate an Ammonia-Tolerant Methanogenic Microbiome.

      Frank, J A; Arntzen, M Ø; Sun, L; Hagen, L H; McHardy, A C; Horn, S J; Eijsink, V G H; Schnürer, A; Pope, P B; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2017-05-10)
      Biogas reactors operating with protein-rich substrates have high methane potential and industrial value; however, they are highly susceptible to process failure because of the accumulation of ammonia. High ammonia levels cause a decline in acetate-utilizing methanogens and instead promote the conversion of acetate via a two-step mechanism involving syntrophic acetate oxidation (SAO) to H2 and CO2, followed by hydrogenotrophic methanogenesis. Despite the key role of syntrophic acetate-oxidizing bacteria (SAOB), only a few culturable representatives have been characterized. Here we show that the microbiome of a commercial, ammonia-tolerant biogas reactor harbors a deeply branched, uncultured phylotype (unFirm_1) accounting for approximately 5% of the 16S rRNA gene inventory and sharing 88% 16S rRNA gene identity with its closest characterized relative. Reconstructed genome and quantitative metaproteomic analyses imply unFirm_1's metabolic dominance and SAO capabilities, whereby the key enzymes required for acetate oxidation are among the most highly detected in the reactor microbiome. While culturable SAOB were identified in genomic analyses of the reactor, their limited proteomic representation suggests that unFirm_1 plays an important role in channeling acetate toward methane. Notably, unFirm_1-like populations were found in other high-ammonia biogas installations, conjecturing a broader importance for this novel clade of SAOB in anaerobic fermentations. IMPORTANCE The microbial production of methane or "biogas" is an attractive renewable energy technology that can recycle organic waste into biofuel. Biogas reactors operating with protein-rich substrates such as household municipal or agricultural wastes have significant industrial and societal value; however, they are highly unstable and frequently collapse due to the accumulation of ammonia. We report the discovery of a novel uncultured phylotype (unFirm_1) that is highly detectable in metaproteomic data generated from an ammonia-tolerant commercial reactor. Importantly, unFirm_1 is proposed to perform a key metabolic step in biogas microbiomes, whereby it syntrophically oxidizes acetate to hydrogen and carbon dioxide, which methanogens then covert to methane. Only very few culturable syntrophic acetate-oxidizing bacteria have been described, and all were detected at low in situ levels compared to unFirm_1. Broader comparisons produced the hypothesis that unFirm_1 is a key mediator toward the successful long-term stable operation of biogas production using protein-rich substrates.
    • The PARA-suite: PAR-CLIP specific sequence read simulation and processing.

      Kloetgen, Andreas; Borkhardt, Arndt; Hoell, Jessica I; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2016 (Sour)
      Next-generation sequencing technologies have profoundly impacted biology over recent years. Experimental protocols, such as photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), which identifies protein-RNA interactions on a genome-wide scale, commonly employ deep sequencing. With PAR-CLIP, the incorporation of photoactivatable nucleosides into nascent transcripts leads to high rates of specific nucleotide conversions during reverse transcription. So far, the specific properties of PAR-CLIP-derived sequencing reads have not been assessed in depth. [Source code of the PARA-suite toolkit and the PARA-suite aligner (BWA PARA) are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner , respectively, under the GNU GPLv3 license.]
    • Pediatric ALL relapses after allo-SCT show high individuality, clonal dynamics, selective pressure, and druggable targets.

      Hoell, Jessica I; Ginzel, Sebastian; Kuhlen, Michaela; Kloetgen, Andreas; Gombert, Michael; Fischer, Ute; Hein, Daniel; Demir, Salih; Stanulla, Martin; Schrappe, Martin; et al. (American Society of Haematology, 2019-10-22)
      Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post-allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post-allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients' first relapses, which disappeared in the post-allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children's post-allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post-allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.
    • Phylogeographic reconstruction using air transportation data and its application to the 2009 H1N1 influenza A pandemic.

      Reimering, Susanne; Muñoz, Sebastian; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (PLOS, 2020-02-01)
      Influenza A viruses cause seasonal epidemics and occasional pandemics in the human population. While the worldwide circulation of seasonal influenza is at least partly understood, the exact migration patterns between countries, states or cities are not well studied. Here, we use the Sankoff algorithm for parsimonious phylogeographic reconstruction together with effective distances based on a worldwide air transportation network. By first simulating geographic spread and then phylogenetic trees and genetic sequences, we confirmed that reconstructions with effective distances inferred phylogeographic spread more accurately than reconstructions with geographic distances and Bayesian reconstructions with BEAST that do not use any distance information, and led to comparable results to the Bayesian reconstruction using distance information via a generalized linear model. Our method extends Bayesian methods that estimate rates from the data by using fine-grained locations like airports and inferring intermediate locations not observed among sampled isolates. When applied to sequence data of the pandemic H1N1 influenza A virus in 2009, our approach correctly inferred the origin and proposed airports mainly involved in the spread of the virus. In case of a novel outbreak, this approach allows to rapidly analyze sequence data and infer origin and spread routes to improve disease surveillance and control.
    • PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.

      Gregor, Ivan; Dröge, Johannes; Schirmer, Melanie; Quince, Christopher; McHardy, Alice C; Helmholtz Centre for infection research, Inhoffenstr. 7, D-38124 Braunschweig, Germany. (2016)
      Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into 'bins' representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies 'training' sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.
    • Probabilistic variable-length segmentation of protein sequences for discriminative motif discovery (DiMotif) and sequence embedding (ProtVecX).

      Asgari, Ehsaneddin; McHardy, Alice C; Mofrad, Mohammad R K; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Springer Nature, 2019-03-05)
    • Reconstructing metabolic pathways of a member of the genus Pelotomaculum suggesting its potential to oxidize benzene to carbon dioxide with direct reduction of sulfate.

      Dong, Xiyang; Dröge, Johannes; von Toerne, Christine; Marozava, Sviatlana; McHardy, Alice C; Meckenstock, Rainer U; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2017)
      The enrichment culture BPL is able to degrade benzene with sulfate as electron acceptor and is dominated by an organism of the genus Pelotomaculum. Members of Pelotomaculum are usually known to be fermenters, undergoing syntrophy with anaerobic respiring microorganisms or methanogens. By using a metagenomic approach, we reconstructed a high-quality genome (∼2.97 Mbp, 99% completeness) for Pelotomaculum candidate BPL. The proteogenomic data suggested that (1) anaerobic benzene degradation was activated by a yet unknown mechanism for conversion of benzene to benzoyl-CoA; (2) the central benzoyl-CoA degradation pathway involved reductive dearomatization by a class II benzoyl-CoA reductase followed by hydrolytic ring cleavage and modified β-oxidation; (3) the oxidative acetyl-CoA pathway was utilized for complete oxidation to CO2. Interestingly, the genome of Pelotomaculum candidate BPL has all the genes for a complete sulfate reduction pathway including a similar electron transfer mechanism for dissimilatory sulfate reduction as in other Gram-positive sulfate-reducing bacteria. The proteome analysis revealed that the essential enzymes for sulfate reduction were all formed during growth with benzene. Thus, our data indicated that, besides its potential to anaerobically degrade benzene, Pelotomaculum candidate BPL is the first member of the genus that can perform sulfate reduction.
    • Reproducible Colonization of Germ-Free Mice With the Oligo-Mouse-Microbiota in Different Animal Facilities.

      Eberl, Claudia; Ring, Diana; Münch, Philipp C; Beutler, Markus; Basic, Marijana; Slack, Emma Caroline; Schwarzer, Martin; Srutkova, Dagmar; Lange, Anna; Frick, Julia S; et al. (Frontiers, 2019-01-01)
      The Oligo-Mouse-Microbiota (OMM12) is a recently developed synthetic bacterial community for functional microbiome research in mouse models (Brugiroux et al., 2016). To date, the OMM12 model has been established in several germ-free mouse facilities world-wide and is employed to address a growing variety of research questions related to infection biology, mucosal immunology, microbial ecology and host-microbiome metabolic cross-talk. The OMM12 consists of 12 sequenced and publically available strains isolated from mice, representing five bacterial phyla that are naturally abundant in the murine gastrointestinal tract (Lagkouvardos et al., 2016). Under germ-free conditions, the OMM12 colonizes mice stably over multiple generations. Here, we investigated whether stably colonized OMM12 mouse lines could be reproducibly established in different animal facilities. Germ-free C57Bl/6J mice were inoculated with a frozen mixture of the OMM12 strains. Within 2 weeks after application, the OMM12 community reached the same stable composition in all facilities, as determined by fecal microbiome analysis. We show that a second application of the OMM12 strains after 72 h leads to a more stable community composition than a single application. The availability of such protocols for reliable de novo generation of gnotobiotic rodents will certainly contribute to increasing experimental reproducibility in biomedical research.
    • Seqenv: Linking sequences to environments through text mining

      BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
      Understanding the distribution of taxa and associated traits across different environments is one of the central questions in microbial ecology. High-throughput sequencing (HTS) studies are presently generating huge volumes of data to address this biogeographical topic. However, these studies are often focused on specific environment types or processes leading to the production of individual, unconnected datasets. The large amounts of legacy sequence data with associated metadata that exist can be harnessed to better place the genetic information found in these surveys into a wider environmental context. Here we introduce a software program, seqenv, to carry out precisely such a task. It automatically performs similarity searches of short sequences against the ``nt'' nucleotide database provided by NCBI and, out of every hit, extracts-if it is available-the textual metadata field. After collecting all the isolation sources from all the search results, we run a text mining algorithm to identify and parse words that are associated with the Environmental Ontology (EnvO) controlled vocabulary. This, in turn, enables us to determine both in which environments individual sequences or taxa have previously been observed and, by weighted summation of those results, to summarize complete samples. We present two demonstrative applications of seqenv to a survey of ammonia oxidizing archaea as well as to a plankton paleome dataset from the Black Sea. These demonstrate the ability of the tool to reveal novel patterns in HTS and its utility in the fields of environmental source tracking, paleontology, and studies of microbial biogeography. To install seqenv, go to: https://github.com/xapple/seqenv. (c) 2016 Sinclair et al
    • Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment.

      Schulte-Schrepping, Jonas; Reusch, Nico; Paclik, Daniela; Baßler, Kevin; Schlickeiser, Stephan; Zhang, Bowen; Krämer, Benjamin; Krammer, Tobias; Brumhard, Sophia; Bonaguro, Lorenzo; et al. (Elsevier /Cell Press), 2020-08-05)
      Coronavirus disease 2019 (COVID-19) is a mild to moderate respiratory tract infection, however, a subset of patients progress to severe disease and respiratory failure. The mechanism of protective immunity in mild forms and the pathogenesis of severe COVID-19 associated with increased neutrophil counts and dysregulated immune responses remain unclear. In a dual-center, two-cohort study, we combined single-cell RNA-sequencing and single-cell proteomics of whole-blood and peripheral-blood mononuclear cells to determine changes in immune cell composition and activation in mild versus severe COVID-19 (242 samples from 109 individuals) over time. HLA-DRhiCD11chi inflammatory monocytes with an interferon-stimulated gene signature were elevated in mild COVID-19. Severe COVID-19 was marked by occurrence of neutrophil precursors, as evidence of emergency myelopoiesis, dysfunctional mature neutrophils, and HLA-DRlo monocytes. Our study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.
    • Snowball: strain aware gene assembly of metagenomes.

      Gregor, I; Schönhuth, A; McHardy, A C; [BRICS] Braunschweiger Zentrum für Systembiology, Rebenring 56, 38106 Braunschweig, Germany. (2016-09-01)
      Gene assembly is an important step in functional analysis of shotgun metagenomic data. Nonetheless, strain aware assembly remains a challenging task, as current assembly tools often fail to distinguish among strain variants or require closely related reference genomes of the studied species to be available.
    • Structures and functions linked to genome-wide adaptation of human influenza A viruses.

      Klingen, Thorsten R; Loers, Jens; Stanelle-Bertram, Stephanie; Gabriel, Gülsah; McHardy, Alice C; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany. (Springer-Nature, 2019-04-18)
      Human influenza A viruses elicit short-term respiratory infections with considerable mortality and morbidity. While H3N2 viruses circulate for more than 50 years, the recent introduction of pH1N1 viruses presents an excellent opportunity for a comparative analysis of the genome-wide evolutionary forces acting on both subtypes. Here, we inferred patches of sites relevant for adaptation, i.e. being under positive selection, on eleven viral protein structures, from all available data since 1968 and correlated these with known functional properties. Overall, pH1N1 have more patches than H3N2 viruses, especially in the viral polymerase complex, while antigenic evolution is more apparent for H3N2 viruses. In both subtypes, NS1 has the highest patch and patch site frequency, indicating that NS1-mediated viral attenuation of host inflammatory responses is a continuously intensifying process, elevated even in the longtime-circulating subtype H3N2. We confirmed the resistance-causing effects of two pH1N1 changes against oseltamivir in NA activity assays, demonstrating the value of the resource for discovering functionally relevant changes. Our results represent an atlas of protein regions and sites with links to host adaptation, antiviral drug resistance and immune evasion for both subtypes for further study.
    • Survival trade-offs in plant roots during colonization by closely related beneficial and pathogenic fungi.

      Hacquard, Stéphane; Kracher, Barbara; Hiruma, Kei; Münch, Philipp C; Garrido-Oter, Ruben; Thon, Michael R; Weimann, Aaron; Damm, Ulrike; Dallery, Jean-Félix; Hainaut, Matthieu; et al. (2016-05-06)
      The sessile nature of plants forced them to evolve mechanisms to prioritize their responses to simultaneous stresses, including colonization by microbes or nutrient starvation. Here, we compare the genomes of a beneficial root endophyte, Colletotrichum tofieldiae and its pathogenic relative C. incanum, and examine the transcriptomes of both fungi and their plant host Arabidopsis during phosphate starvation. Although the two species diverged only 8.8 million years ago and have similar gene arsenals, we identify genomic signatures indicative of an evolutionary transition from pathogenic to beneficial lifestyles, including a narrowed repertoire of secreted effector proteins, expanded families of chitin-binding and secondary metabolism-related proteins, and limited activation of pathogenicity-related genes in planta. We show that beneficial responses are prioritized in C. tofieldiae-colonized roots under phosphate-deficient conditions, whereas defense responses are activated under phosphate-sufficient conditions. These immune responses are retained in phosphate-starved roots colonized by pathogenic C. incanum, illustrating the ability of plants to maximize survival in response to conflicting stresses.
    • Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses.

      Klingen, Thorsten R; Reimering, Susanne; Loers, Jens; Mooren, Kyra; Klawonn, Frank; Krey, Thomas; Gabriel, Gülsah; McHardy, Alice Carolyn; BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany. (2018-01-10)
      Monitoring changes in influenza A virus genomes is crucial to understand its rapid evolution and adaptation to changing conditions e.g. establishment within novel host species. Selective sweeps represent a rapid mode of adaptation and are typically observed in human influenza A viruses. We describe Sweep Dynamics (SD) plots, a computational method combining phylogenetic algorithms with statistical techniques to characterize the molecular adaptation of rapidly evolving viruses from longitudinal sequence data. SD plots facilitate the identification of selective sweeps, the time periods in which these occurred and associated changes providing a selective advantage to the virus. We studied the past genome-wide adaptation of the 2009 pandemic H1N1 influenza A (pH1N1) and seasonal H3N2 influenza A (sH3N2) viruses. The pH1N1 influenza virus showed simultaneous amino acid changes in various proteins, particularly in seasons of high pH1N1 activity. Partially, these changes resulted in functional alterations facilitating sustained human-to-human transmission. In the evolution of sH3N2 influenza viruses, we detected changes characterizing vaccine strains, which were occasionally revealed in selective sweeps one season prior to the WHO recommendation. Taken together, SD plots allow monitoring and characterizing the adaptive evolution of influenza A viruses by identifying selective sweeps and their associated signatures. - - all data is published on GitHub: https://github.com/hzi-bifo/SDplots/tree/v1.0.0
    • Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods.

      Dröge, J; Gregor, I; McHardy, A C; Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany Department for Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany, Max-Planck Research Group for Computational Genomics and Epidemiology, Max-Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany and Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany. (2014-11-10)
      Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.
    • Temporally feathered intensity-modulated radiation therapy: A planning technique to reduce normal tissue toxicity.

      López Alfonso, Juan Carlos; Parsai, Shireen; Joshi, Nikhil; Godley, Andrew; Shah, Chirag; Koyfman, Shlomo A; Caudell, Jimmy J; Fuller, Clifton D; Enderling, Heiko; Scott, Jacob G; et al. (Wiley, 2018-06-08)
      Purpose: Intensity-modulated radiation therapy (IMRT) has allowed optimization of three-dimensional spatial radiation dose distributions permitting target coverage while reducing normal tissue toxicity. However, radiation-induced normal tissue toxicity is a major contributor to patients' quality of life and often a dose-limiting factor in the definitive treatment of cancer with radiation therapy. We propose the next logical step in the evolution of IMRT using canonical radiobiological principles, optimizing the temporal dimension through which radiation therapy is delivered to further reduce radiation-induced toxicity by increased time for normal tissue recovery. We term this novel treatment planning strategy "temporally feathered radiation therapy" (TFRT). Methods: Temporally feathered radiotherapy plans were generated as a composite of five simulated treatment plans each with altered constraints on particular hypothetical organs at risk (OARs) to be delivered sequentially. For each of these TFRT plans, OARs chosen for feathering receive higher doses while the remaining OARs receive lower doses than the standard fractional dose delivered in a conventional fractionated IMRT plan. Each TFRT plan is delivered a specific weekday, which in effect leads to a higher dose once weekly followed by four lower fractional doses to each temporally feathered OAR. We compared normal tissue toxicity between TFRT and conventional fractionated IMRT plans by using a dynamical mathematical model to describe radiation-induced tissue damage and repair over time. Results: Model-based simulations of TFRT demonstrated potential for reduced normal tissue toxicity compared to conventionally planned IMRT. The sequencing of high and low fractional doses delivered to OARs by TFRT plans suggested increased normal tissue recovery, and hence less overall radiation-induced toxicity, despite higher total doses delivered to OARs compared to conventional fractionated IMRT plans. The magnitude of toxicity reduction by TFRT planning was found to depend on the corresponding standard fractional dose of IMRT and organ-specific recovery rate of sublethal radiation-induced damage. Conclusions: TFRT is a novel technique for treatment planning and optimization of therapeutic radiotherapy that considers the nonlinear aspects of normal tissue repair to optimize toxicity profiles. Model-based simulations of TFRT to carefully conceptualized clinical cases have demonstrated potential for radiation-induced toxicity reduction in a previously described dynamical model of normal tissue complication probability (NTCP).
    • Toward unrestricted use of public genomic data.

      Amann, Rudolf I; Baichoo, Shakuntala; Blencowe, Benjamin J; Bork, Peer; Borodovsky, Mark; Brooksbank, Cath; Chain, Patrick S G; Colwell, Rita R; Daffonchio, Daniele G; Danchin, Antoine; et al. (AAAS, 2019-01-25)
      Despite some notable progress in data sharing policies and practices, restrictions are still often placed on the open and unconditional use of various genomic data after they have received official approval for release to the public domain or to public databases. These restrictions, which often conflict with the terms and conditions of the funding bodies who supported the release of those data for the benefit of the scientific community and society, are perpetuated by the lack of clear guiding rules for data usage. Existing guidelines for data released to the public domain recognize but fail to resolve tensions between the importance of free and unconditional use of these data and the “right” of the data producers to the first publication. This self-contradiction has resulted in a loophole that allows different interpretations and a continuous debate between data producers and data users on the use of public data. We argue that the publicly available data should be treated as open data, a shared resource with unrestricted use for analysis, interpretation, and publication.
    • Transcriptome-wide analysis uncovers the targets of the RNA-binding protein MSI2 and effects of MSI2's RNA-binding activity on IL-6 signaling.

      Duggimpudi, Sujitha; Kloetgen, Andreas; Maney, Sathish Kumar; Münch, Philipp C; Hezaveh, Kebria; Shaykhalishahi, Hamed; Hoyer, Wolfgang; McHardy, Alice C; Lang, Philipp A; Borkhardt, Arndt; et al. (American Society for Biochemistry and Molecular Biology, 2018-08-20)
      The RNA-binding protein Musashi 2 (MSI2) has emerged as an important regulator in cancer initiation, progression, and drug resistance. Translocations and deregulation of the MSI2 gene are diagnostic of certain cancers, including chronic myeloid leukemia (CML) with translocation t(7;17), acute myeloid leukemia (AML) with translocation t(10;17), and some cases of B-precursor acute lymphoblastic leukemia (pB-ALL). To better understand the function of MSI2 in leukemia, the mRNA targets that are bound and regulated by MSI2 and their MSI2-binding motifs need to be identified. To this end, using photoactivatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) and the multiple EM for motif elicitation (MEME) analysis tool, here we identified MSI2's mRNA targets and the consensus RNA-recognition element (RRE) motif recognized by MSI2 (UUAG). Of note, MSI2 knockdown altered the expression of several genes with roles in eukaryotic initiation factor 2 (eIF2), hepatocyte growth factor (HGF), and epidermal growth factor (EGF) signaling pathways. We also show that MSI2 regulates classic interleukin-6 (IL-6) signaling by promoting the degradation of the mRNA of IL-6 signal transducer (IL6ST or GP130), which, in turn, affected the phosphorylation statuses of signal transducer and activator of transcription 3 (STAT3) and the mitogen-activated protein kinase ERK. In summary, we have identified multiple MSI2-regulated mRNAs and provided evidence that MSI2 controls IL6ST activity that control oncogenic signaling networks. Our findings may help inform strategies for unraveling the role of MSI2 in leukemia to pave the way for the development of targeted therapies.