Many essential biological processes are controlled by posttranslational protein modifications. The inability to synthetically attain the diversity enabled by these modifications limits functional studies of many proteins. We designed a three-step approach for installing authentic posttranslational modifications in recombinant proteins. We first use the established O-phosphoserine (Sep) orthogonal translation system to create a Sep-containing recombinant protein. The Sep residue is then dephosphorylated to dehydroalanine (Dha). Last, conjugate addition of alkyl iodides to Dha, promoted by zinc and copper, enables chemoselective carbon-carbon bond formation. To validate our approach, we produced histone H3, ubiquitin, and green fluorescent protein variants with site-specific modifications, including different methylations of H3K79. The methylated histones stimulate transcription through histone acetylation. This approach offers a powerful tool to engineer diverse designer proteins.
SUMMARY Upon DNA stimulation, cyclic GMP-AMP synthetase (cGAS) synthesizes the second messenger cyclic GMP-AMP (cGAMP) that binds to the STING, triggering antiviral interferon-β (IFN-β) production. However, it has remained undetermined how hosts regulate cGAS enzymatic activity after the resolution of DNA immunogen. Here, we show that Akt kinase plays a negative role in cGAS-mediated anti-viral immune response. Akt phosphorylated the S291 or S305 residue of the enzymatic domain of mouse or human cGAS, respectively, and this phosphorylation robustly suppressed its enzymatic activity. Consequently, expression of activated Akt led to the reduction of cGAMP and IFN-β production and the increase of herpes simplex virus 1 replication, whereas treatment with Akt inhibitor augmented cGAS-mediated IFN-β production. Furthermore, expression of the phosphorylation-resistant cGAS S291A mutant enhanced IFN-β production upon DNA stimulation, HSV-1 infection, and vaccinia virus infection. Our study identifies an Akt kinase-mediated checkpoint to fine-tune hosts’ immune responses to DNA stimulation.
This study introduces “Google Trends” as a social data source in monitoring and modeling the dynamics of drought awareness during the 2011–17 California drought. In this study, drought awareness is defined and operationalized as the relative search interest activities within California, using the search term “drought” from Google Trends. First, the 2011–17 California drought is characterized in the duration–intensity curve with other historical California droughts for comparative purposes, using the 12-month standard precipitation index data (1895–2017). Second, the potential triggers of the peaks of drought awareness during the 2011–17 California drought are investigated through Google Trends and Google Search. The Google Trends data show that the first peak of drought awareness occurred when the drought condition reached its peak and the governor declared the drought emergency (January 2014). The other peaks in August 2014, April 2015, and January 2017 are related to public interest in drought recovery driven by the forecast of the strong El Niño winter of 2014/15, the governor’s issue of water use rules, and California floods in early 2017, respectively. Last, a power-law decay model of drought awareness is fitted to the Google Trends data. According to the fitted power-law model, Californians remained interested in drought after the social trigger–related peaks longer than they did after the natural trigger–related peaks. The findings of this study suggest that it is necessary to develop a more realistic social dynamic modeling for communities that can respond to natural and human triggers and capture interactions with awareness of related disasters.
Drought is a creeping climatological phenomenon with persistent precipitation deficits. Unlike rapid onset natural hazards such as floods and wildfires, the intangible and gradual characteristics of drought cause a lack of social response during the onset. The level of awareness of a local drought increases rapidly through mass media reports and online information searching activities when the drought reaches its peak severity. This high level of local drought awareness drives concerns for water shortage and support for water policy. However, spatiotemporal patterns of national-scale drought awareness have never been studied due to constraints imposed by time-consuming and costly survey data collection and surveys' limited sample sizes. Here, we present the national-scale study to reveal the spatiotemporal patterns of drought awareness over the contiguous United States (CONUS) using Google Trends data and Principal Component Analysis (PCA). Results show that the first two PC modes can explain 48% (38% for PC1 and 10% for PC2) of the total variance of state-level drought awareness. We find that the PC1 mode relates to a national pattern of drought awareness across the CONUS. The spatiotemporal patterns further imply that residents in the Northeastern US region are the most aware of the emergence of drought, regardless of the geographic location of the occurrence. The results illustrate how big data, such as search query and social media data, can help develop an effective and efficient plan for drought mitigation in the future.
A new, high surface area, nanoporous polymer (COP-220) was synthesized using sustainable building blocks, namely, a food coloring dye (erythrosine B) and a commercial alkyne. During the Sonogashira coupling, it is observed that Pd and Cu ions and triphenylphosphine ligands of the catalyst get trapped inside the pores. The remnant synthesis catalyst components were characterized in detail and were tested as a new catalyst for Suzuki–Miyaura coupling reactions. COP-220 showed conversion yields comparable to the commercial homogeneous catalyst Pd(PPh3)2Cl2 with an additional advantage of size-dependent catalytic activity when bulkier substrates were used. COP-220 was highly stable under thermal and chemical treatments and recyclable with no loss of activity. These findings show a clear need for extensive characterization of nanoporous polymers made through cross-coupling reactions and the potential of the trapped catalysts for new catalytic activity without additional loading.
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