A Multiparameter Network Reveals Extensive Divergence Between \u3cem\u3eC. elegans\u3c/em\u3e bHLH Transcription Factors: A Dissertation

It has become increasingly clear that transcription factors (TFs) play crucial roles in the development and day-to-day homeostasis that all biological systems experience. TFs target particular genes in a genome, at the appropriate place and time, to regulate their expression so as to elicit the most appropriate biological response from a cell or multicellular organism. TFs can often be grouped into families based on the presence of similar DNA binding domains, and these families are believed to have expanded and diverged throughout evolution by several rounds of gene duplication and mutation. The extent to which TFs within a family have functionally diverged, however, has remained unclear. We propose that systematic analysis of multiple aspects, or parameters, of TF functionality for entire families of TFs could provide clues as to how divergent paralogous TFs really are. We present here a multiparameter integrated network of the activity of the basic helix-loop-helix (bHLH) TFs from the nematode Caenorhabditis elegans. Our data, and the resulting network, indicate that several parameters of bHLH function contribute to their divergence and that many bHLH TFs and their associated parameters exhibit a wide range of connectivity in the network, some being uniquely associated to one another, whereas others are highly connected to multiple parameter associations. We find that 34 bHLH proteins dimerize to form 30 bHLH dimers, which are expressed in a wide range of tissues and cell types, particularly during the development of the nematode. These dimers bind to E-Box DNA sequences and E-Box-like sequences with specificity for nucleotides central to and flanking those E-Boxes and related sequences. Our integrated network is the first such network for a multicellular organism, describing the dimerization specificity, spatiotemporal expression patterns, and DNA binding specificities of an entire family of TFs. The network elucidates the state of bHLH TF divergence in C. elegans with respect to multiple functional parameters and suggests that each bHLH TF, despite many molecular similarities, is distinct from its family members. This functional distinction may indeed explain how TFs from a single family can acquire different biological functions despite descending from common genetic ancestry

Transcription factor functionality and transcription regulatory networks

Now that numerous high-quality complete genome sequences are available, many efforts are focusing on the second genomic code , namely the code that determines how the precise temporal and spatial expression of each gene in the genome is achieved. In this regard, the elucidation of transcription regulatory networks that describe combined transcriptional circuits for an organism of interest has become valuable to our understanding of gene expression at a systems level. Such networks describe physical and regulatory interactions between transcription factors (TFs) and the target genes they regulate under different developmental, physiological, or pathological conditions. The mapping of high-quality transcription regulatory networks depends not only on the accuracy of the experimental or computational method chosen, but also relies on the quality of TF predictions. Moreover, the total repertoire of TFs is not only determined by the protein-coding capacity of the genome, but also by different protein properties, including dimerization, co-factor interactions and post-translational modifications. Here, we discuss the factors that influence TF functionality and, hence, the functionality of the networks in which they operate

Initial results from the Caltech/DRSI balloon-borne isotope experiment

The Caltech/DSRI balloonborne High Energy Isotope Spectrometer Telescope (HEIST) was flown successfully from Palestine, Texas on 14 May, 1984. The experiment was designed to measure cosmic ray isotopic abundances from neon through iron, with incident particle energies from approx. 1.5 to 2.2 GeV/nucleon depending on the element. During approximately 38 hours at float altitude, 100,000 events were recorded with Z or = 6 and incident energies approx. 1.5 GeV/nucleon. We present results from the ongoing data analysis associated with both the preflight Bevalac calibration and the flight data

2018 Update on Protein-Protein Interaction Data in WormBase

Protein interaction is an important data type to understand the biological function of proteins involved in the interaction, and helps researchers to deduce the biological nature of unknown proteins from the well-characterized functions of their interaction partners. High-throughput studies, coupled with the aggregation of individual experiments, provides a global 'snapshot' of the protein interactions occurring at all levels of biological processes or circumstances. This snapshot of the interaction network, the interactome, is important to understand the overall events up to the level of comparison between species or pathway simulation, or to find new factors yet undefined in the processes, or to add details to the biological processes and pathways. As of September 2018, WormBase (www.wormbase.org) (Lee et al. 2018) contains 28,279 physical protein-protein interactions for the roundworm Caenorhabditis elegans. Among these, 1500 protein-protein interactions have been curated by BioGRID as a collaboration with WormBase. Within the data set, 17,990 protein-protein interactions are unique, and 6,079 unique genes are involved in these interactions. In order to visualize the overall interaction map, a network diagram for all the unique interactions was generated by using the ‘Cytoscape’ program, version 3.6.1 (Shannon et al. 2003) (Figure 1A). These numbers represent a 108% increase in the number of interaction annotations since last year, 2017. These interaction data were curated from 1,251 peer-reviewed papers, which were selected from the literature by ‘Textpresso Central’ using automatic SVM (Support Vector Machine)-based text mining approaches (Fang et al. 2012; Müller et al. 2018) and manual verification. Compared to other databases providing C. elegans protein-protein interaction, WormBase now presents the largest data set, which has 1.72-fold more interaction annotations than IMEx (Orchard et al. 2012) and 4.51-fold more than BioGRID (Chatr-Aryamontri et al. 2017) (Figure 1B). Most significantly, WormBase now houses the complete protein interaction data from almost all of the C. elegans literature published from 1993 to 2018. The data sets presented at IMEx and BioGRID are annotated from 253 and 174 papers, respectively. All the physical interaction data in WormBase are supported by experimental evidence from original research papers. The statistics of the detection methods used as experimental evidence are shown in Figure 1C. The majority of the interaction data came from high throughput analysis such as large-scale yeast two-hybrid assays or mass-spectrometry, however, a significant portion of the data (13.1%) are supported by more direct detection methods using small-scale, low throughput methods such as co-immunoprecipitation or co-crystallography (Figure 1C). In WormBase, protein-protein interaction data can be found as a subclass of physical interaction data in the ‘Interactions widget’ on the gene report page. The Interactions widget provides all types of interaction data related to the gene of interest, such as physical, genetic, regulatory, and predicted interactions. All the interaction data are represented together in a graph created with ‘Cytoscape.js’ and a table. In the table, the gene names of interaction partners (bait-target) in the interaction are displayed along with the publication. The interaction details including the detection method are also captured in the summary and the remark field in the Interactions page. Users can query the data by using the search bar on the WormBase front page or download all the available data files from the WormBase FTP site (ftp://ftp.wormbase.org/pub/wormbase/releases/current-production-release/species/c_elegans/PRJNA13758 /annotation/c_elegans.PRJNA13758.WSXXX.interactions.txt.gz, where WSXXX is the database version release, like “WS267”). All the interaction data in WormBase will be available soon at the new information resource for multiple model organisms, the Alliance of Genome Resources (https://www.alliancegenome.org/). This site will integrate all the interaction data from human and from model organisms C. elegans, budding yeast (Saccharomyces cerevisiae), fruit fly (Drosophila melanogaster), zebrafish (Danio rerio), mouse (Mus musculus) and rat (Rattus norvegicus). Integrated views of interaction data from diverse model organisms will be extremely helpful to build interaction databases for species-to-species comparison, and to establish a disease model quickly based on the database. For the most efficient analysis of the interaction data in WormBase, we are now working on developing a new ‘Venn diagram tool’ and integrating the ‘Gene Set Enrichment Analysis tool’ (https://wormbase.org/tools/enrichment/tea/tea.cgi) into the Interactions widget. We will continue to curate other types of macro-molecular interactions including protein-DNA, protein-RNA and RNA-RNA interactions, as well as newly reported protein-protein interaction data to serve our research community

2018 Update on Protein-Protein Interaction Data in WormBase

Protein interaction is an important data type to understand the biological function of proteins involved in the interaction, and helps researchers to deduce the biological nature of unknown proteins from the well-characterized functions of their interaction partners. High-throughput studies, coupled with the aggregation of individual experiments, provides a global 'snapshot' of the protein interactions occurring at all levels of biological processes or circumstances. This snapshot of the interaction network, the interactome, is important to understand the overall events up to the level of comparison between species or pathway simulation, or to find new factors yet undefined in the processes, or to add details to the biological processes and pathways. As of September 2018, WormBase (www.wormbase.org) (Lee et al. 2018) contains 28,279 physical protein-protein interactions for the roundworm Caenorhabditis elegans. Among these, 1500 protein-protein interactions have been curated by BioGRID as a collaboration with WormBase. Within the data set, 17,990 protein-protein interactions are unique, and 6,079 unique genes are involved in these interactions. In order to visualize the overall interaction map, a network diagram for all the unique interactions was generated by using the ‘Cytoscape’ program, version 3.6.1 (Shannon et al. 2003) (Figure 1A). These numbers represent a 108% increase in the number of interaction annotations since last year, 2017. These interaction data were curated from 1,251 peer-reviewed papers, which were selected from the literature by ‘Textpresso Central’ using automatic SVM (Support Vector Machine)-based text mining approaches (Fang et al. 2012; Müller et al. 2018) and manual verification. Compared to other databases providing C. elegans protein-protein interaction, WormBase now presents the largest data set, which has 1.72-fold more interaction annotations than IMEx (Orchard et al. 2012) and 4.51-fold more than BioGRID (Chatr-Aryamontri et al. 2017) (Figure 1B). Most significantly, WormBase now houses the complete protein interaction data from almost all of the C. elegans literature published from 1993 to 2018. The data sets presented at IMEx and BioGRID are annotated from 253 and 174 papers, respectively. All the physical interaction data in WormBase are supported by experimental evidence from original research papers. The statistics of the detection methods used as experimental evidence are shown in Figure 1C. The majority of the interaction data came from high throughput analysis such as large-scale yeast two-hybrid assays or mass-spectrometry, however, a significant portion of the data (13.1%) are supported by more direct detection methods using small-scale, low throughput methods such as co-immunoprecipitation or co-crystallography (Figure 1C). In WormBase, protein-protein interaction data can be found as a subclass of physical interaction data in the ‘Interactions widget’ on the gene report page. The Interactions widget provides all types of interaction data related to the gene of interest, such as physical, genetic, regulatory, and predicted interactions. All the interaction data are represented together in a graph created with ‘Cytoscape.js’ and a table. In the table, the gene names of interaction partners (bait-target) in the interaction are displayed along with the publication. The interaction details including the detection method are also captured in the summary and the remark field in the Interactions page. Users can query the data by using the search bar on the WormBase front page or download all the available data files from the WormBase FTP site (ftp://ftp.wormbase.org/pub/wormbase/releases/current-production-release/species/c_elegans/PRJNA13758 /annotation/c_elegans.PRJNA13758.WSXXX.interactions.txt.gz, where WSXXX is the database version release, like “WS267”). All the interaction data in WormBase will be available soon at the new information resource for multiple model organisms, the Alliance of Genome Resources (https://www.alliancegenome.org/). This site will integrate all the interaction data from human and from model organisms C. elegans, budding yeast (Saccharomyces cerevisiae), fruit fly (Drosophila melanogaster), zebrafish (Danio rerio), mouse (Mus musculus) and rat (Rattus norvegicus). Integrated views of interaction data from diverse model organisms will be extremely helpful to build interaction databases for species-to-species comparison, and to establish a disease model quickly based on the database. For the most efficient analysis of the interaction data in WormBase, we are now working on developing a new ‘Venn diagram tool’ and integrating the ‘Gene Set Enrichment Analysis tool’ (https://wormbase.org/tools/enrichment/tea/tea.cgi) into the Interactions widget. We will continue to curate other types of macro-molecular interactions including protein-DNA, protein-RNA and RNA-RNA interactions, as well as newly reported protein-protein interaction data to serve our research community

Initial Results from the Caltech/DSRI Balloon-Borne Isotope Experiment

The Caltech/DSRI balloonborne High Energy Isotope Spectrometer Telescope (HEIST) was flown successfully from Palestine, Texas on 14 May, 1984. The experiment was designed to measure cosmic ray isotopic abundances from neon through iron, with incident particle energies from ~1.5 to 2.2 GeV/nucleon depending on the element. During ~38 hours at float altitude, > 10^5 events were recorded with Z ≥ 6 and incident energies ≳ 1.5 GeV/nucleon. We present results from the ongoing data analysis associated with both the preflight Bevalac calibration and the flight data

Technological and geometric morphometric analysis of ‘post-Howiesons Poort points’ from Border Cave, KwaZulu-Natal, South Africa

Lithic assemblages immediately following the Howiesons Poort, often loosely referred to as the ‘post-Howiesons Poort’ or MSA III, have attracted relatively little attention when compared to other well-known phases of the South African Middle Stone Age (MSA) sequence. Current evidence from sites occurring in widely-differing environments suggests that these assemblages are marked by temporal and technological variability, with few features in common other than the presence of unifacial points. Here we present a technological and geometric morphometric analysis of ‘points’ from the new excavations of Members 2 BS, 2 WA and the top of 3 BS members at Border Cave, KwaZulu-Natal, one of the key sites for studying modern human cultural evolution. Our complementary methodologies demonstrate that, at this site, hominins adopted a knapping strategy that primarily produced non-standardised unretouched points. Triangular morphologies were manufactured using a variety of reduction strategies, of which the discoidal and Levallois recurrent centripetal methods produced distinctive morphologies. We find technological and morphological variability increases throughout the post-Howiesons Poort sequence, with clear differences between and within chrono-stratigraphic groups. Finally, we assess the suitability of the ‘Sibudan’ cultural-technological typology proposed for post-Howiesons Poort assemblages at Sibhudu, another KwaZulu-Natal site, and find similarities in the morphological axes characterising the samples, despite differences in the shaping strategies adopted. Overall, our work contributes to the growing body of research that is helping to address historical research biases that have slanted our understanding of cultural evolution during the MSA of southern Africa towards the Still Bay and Howiesons Poort technocomplexes.publishedVersio

Using an A-10 Aircraft for Airborne measurements of TGFs

Plans are underway to convert an A-10 combat attack aircraft into a research aircraft for thunderstorm research. This aircraft would be configured and instrumented for flights into large, convective thunderstorms. It would have the capabilities of higher altitude performance and protection for thunderstorm conditions that exceed those of aircraft now in use for this research. One area of investigation for this aircraft would be terrestrial gamma ]ray flashes (TGFs), building on the pioneering observations made by the Airborne Detector for Energetic Lightning Emissions (ADELE) project several years ago. A new and important component of the planned investigations are the continuous, detailed correlations of TGFs with the electric fields near the aircraft, as well as detailed measurements of nearby lightning discharges. Together, the x-and gamma-radiation environments, the electric field measurements, and the lightning observations (all measured on microsecond timescales) should provide new insights into this TGF production mechanism. The A -10 aircraft is currently being modified for thunderstorm research. It is anticipated that the initial test flights for this role will begin next year

High Resolution Cherenkov Detectors for Use in a Cosmic Ray Isotope Spectrometer

We describe the development of new high-resolution Cerenkov detectors for use in an instrument designed to measure the isotopic composition of cosmic ray nuclei from Be to Ni (Z = 4 to 28). The latest version of this balloon-borne instrument contains two new large-area, (-0.5 m^2) Cerenkov detectors, one composed of Teflon and a second of Pilot- 425. Through the use of improved light-collection techniques, and a novel radiator design, the photoelectron yield of these counters has been upgraded significantly over that of earlier counters. In particular, the greatly improved Cerenkov light yield achieved with Teflon makes it an attractive alternative to available liquid counters of similar index of refraction. Laboratory tests of these and other Cerenkov radiators are described, along with estimates of the mass resolution that can be achieved