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- Creators: Department of Chemistry and Biochemistry
- Member of: ASU Regents' Professors Open Access Works
Cell-sediment separation methods can potentially enable determination of the elemental composition of microbial communities by removing the sediment elemental contribution from bulk samples. We demonstrate that a separation method can be applied to determine the composition of prokaryotic cells. The method uses chemical and physical means to extract cells from benthic sediments and mats. Recovery yields were between 5% and 40%, as determined from cell counts. The method conserves cellular element contents to within 30% or better, as assessed by comparing C, N, P, Mg, Al, Ca, Ti, Mn, Fe, Ni, Cu, Zn, and Mo contents in Escherichia coli. Contamination by C, N, and P from chemicals used during the procedure was negligible. Na and K were not conserved, being likely exchanged through the cell membrane as cations during separation. V, Cr, and Co abundances could not be determined due to large (>100%) measurement uncertainties. We applied this method to measure elemental contents in extremophilic communities of Yellowstone National Park hot springs. The method was generally successful at separating cells from sediment, but does not discriminate between cells and detrital biological or noncellular material of similar density. This resulted in Al, Ti, Mn, and Fe contamination, which can be tracked using proxies such as metal:Al ratios. With these caveats, we present the first measurements, to our knowledge, of the elemental abundances of a chemosynthetic community. The communities have C:N ratios typical of aquatic microorganisms, are low in P, and their metal abundances vary between hot springs by orders of magnitude.
The membrane proximal region (MPR, residues 649–683) and transmembrane domain (TMD, residues 684–705) of the gp41 subunit of HIV-1’s envelope protein are highly conserved and are important in viral mucosal transmission, virus attachment and membrane fusion with target cells. Several structures of the trimeric membrane proximal external region (residues 662–683) of MPR have been reported at the atomic level; however, the atomic structure of the TMD still remains unknown. To elucidate the structure of both MPR and TMD, we expressed the region spanning both domains, MPR-TM (residues 649–705), in Escherichia coli as a fusion protein with maltose binding protein (MBP). MPR-TM was initially fused to the C-terminus of MBP via a 42 aa-long linker containing a TEV protease recognition site (MBP-linker-MPR-TM).
Biophysical characterization indicated that the purified MBP-linker-MPR-TM protein was a monodisperse and stable candidate for crystallization. However, crystals of the MBP-linker-MPR-TM protein could not be obtained in extensive crystallization screens. It is possible that the 42 residue-long linker between MBP and MPR-TM was interfering with crystal formation. To test this hypothesis, the 42 residue-long linker was replaced with three alanine residues. The fusion protein, MBP-AAA-MPR-TM, was similarly purified and characterized. Significantly, both the MBP-linker-MPR-TM and MBP-AAA-MPR-TM proteins strongly interacted with broadly neutralizing monoclonal antibodies 2F5 and 4E10. With epitopes accessible to the broadly neutralizing antibodies, these MBP/MPR-TM recombinant proteins may be in immunologically relevant conformations that mimic a pre-hairpin intermediate of gp41.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.