The Human-Bacterial Pathogen Protein Interaction Networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis

Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions

Ongoing studies on the bats of Danum Valley Borneo

Here we provide an update on the batting activities of the James Cook University's biannual undergraduate field trip to Danum Valley Field Centre in Borneo. The 2013 trip focussed on various bat surveying techniques, with an emphasis on the use and effectiveness of the EM3 full-spectrum and Anabat II ZCAM ultrasonic detectors. We captured a total of thirty-three individuals of 12 different species in harp traps and mist nets, three species of which had not been encountered on previous surveys. We collected an additional 16,500 call files and in total, we now have a call library of 43 microbat species (of which 28 can be allocated to individual species) along with high-quality photographs of 20 micro- and megabats. It will be no surprise that Terry Reardon also took dynamic photographs of individuals in flight upon release, and generously donated his flash-setup to the staff of Danum Valley. Future field trips will continue to build the call and photo library as well as collect tissue samples for collaborative studies with scientists in Malaysia and Australia. We plan to make the calls and photos available via an open-access WWW page

The US Program in Ground-Based Gravitational Wave Science: Contribution from the LIGO Laboratory

Recent gravitational-wave observations from the LIGO and Virgo observatories have brought a sense of great excitement to scientists and citizens the world over. Since September 2015,10 binary black hole coalescences and one binary neutron star coalescence have been observed. They have provided remarkable, revolutionary insight into the "gravitational Universe" and have greatly extended the field of multi-messenger astronomy. At present, Advanced LIGO can see binary black hole coalescences out to redshift 0.6 and binary neutron star coalescences to redshift 0.05. This probes only a very small fraction of the volume of the observable Universe. However, current technologies can be extended to construct "3rd Generation" (3G) gravitational-wave observatories that would extend our reach to the very edge of the observable Universe. The event rates over such a large volume would be in the hundreds of thousands per year (i.e. tens per hour). Such 3G detectors would have a 10-fold improvement in strain sensitivity over the current generation of instruments, yielding signal-to-noise ratios of 1000 for events like those already seen. Several concepts are being studied for which engineering studies and reliable cost estimates will be developed in the next 5 years

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Interactions with host innate immune response.

<p>Interactions of human proteins involved in the innate immune response. We divided the human protein into subsets based on whether they induce or prevent apoptosis, or whether they regulate apoptosis. Proteins in the group labeled “Non-specific” do not have an annotation more specific than “Apoptosis” in the Gene Ontology <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012089#pone.0012089-Ashburner1" target="_blank">[20]</a>. For clarity this image shows only interactions involving virulence factors and uncharacterized pathogen proteins. As a result, some human proteins in the figure may appear to have no interacting partners.</p

Network properties of interacting proteins.

<p>Cumulative log-log plots of (A) node centralities and (B) degrees for six subsets of nodes in the whole human protein-protein interaction network: the red curve is for the set of proteins in the human PPI network that do not interact with any pathogen in our dataset; the green line is for the set interacting with <i>B. anthracis</i>; the dark blue line is the for set interacting with <i>F. tularensis</i>; the purple line is for the set interacting with <i>Y. pestis</i>; the light blue line is for the set interacting with at least two pathogens; and the orange line is for the set interacting with all three pathogens. The fraction of proteins at a particular value of degree or centrality is the number of proteins having that value or greater divided by the number of proteins in the set. (Counts in parentheses represent the number of proteins in each set.)</p

Conserved interactions.

<p>Summary of bacterial interologs. each row is a pair of bacteria, column 1 is the number orthologous pairs of proteins that both interact with a human protein, column 2 is number of these pairs that interact with the same protein, column 3 is number of these pairs that interact with human proteins that interact themselves, column 4 is number of these pairs that interact with paralogous human proteins.</p

Summary of human-pathogen interactions.

<p>Counts in columns marked with an “*” correspond to pathogen proteins labeled as “putative”, “uncharacterized”, or “hypothetical”.</p