tRNA-mediated codon-biased translation in mycobacterial hypoxic persistence

Microbial pathogens adapt to the stress of infection by regulating transcription, translation and protein modification. We report that changes in gene expression in hypoxia-induced non-replicating persistence in mycobacteria—which models tuberculous granulomas—are partly determined by a mechanism of tRNA reprogramming and codon-biased translation. Mycobacterium bovis BCG responded to each stage of hypoxia and aerobic resuscitation by uniquely reprogramming 40 modified ribonucleosides in tRNA, which correlate with selective translation of mRNAs from families of codon-biased persistence genes. For example, early hypoxia increases wobble cmo[superscript 5]U in tRNA[superscript Thr(UGU)], which parallels translation of transcripts enriched in its cognate codon, ACG, including the DosR master regulator of hypoxic bacteriostasis. Codon re-engineering of dosR exaggerates hypoxia-induced changes in codon-biased DosR translation, with altered dosR expression revealing unanticipated effects on bacterial survival during hypoxia. These results reveal a coordinated system of tRNA modifications and translation of codon-biased transcripts that enhance expression of stress response proteins in mycobacteria.Singapore-MIT Alliance for Research and Technology (SMART)National Institute of Environmental Health Sciences (grants ES017010 and ES002109)National Science Foundation (U.S.) (grant CHE-1308839)Singapore-MIT Alliance for Research and Technology (SMART) (SMA3 Graduate Fellowship

Investigating the Impacts of Urbanization on Vegetation Net Primary Productivity: A Case Study of Chengdu–Chongqing Urban Agglomeration from the Perspective of Townships

As an emerging national strategic urban agglomeration in China, the changing trend of vegetation net primary productivity (NPP) and the impact of the urbanization level (UL) on carbon cycle functions in the Chengdu–Chongqing urban agglomeration (CUA) have received increasing attention. Previous studies have largely overlooked externalities and the heterogeneity of urbanization effects, and urbanization has also been analyzed in isolation (with focus being on land and population urbanization). In this study, the spatial evolution of NPP was evaluated from 2000 to 2020 at the township level (3859) using multivariate remote sensing data and a comprehensive index (UL) that included population urbanization, land urbanization, and economic urbanization. Bivariate spatial autocorrelation, spatial Durbin models, and geographically weighted regression models were used to analyze the spatial externalities of urbanization impacts and assess the global and local effects. The results show that the region’s mean NPP increased by 177.25 g*c/m2 (annual growth of 1.59%), exhibiting a distribution of “low in the middle and high in the periphery” and low-value clustering along major traffic arteries and rivers. Low-value-NPP areas were mainly located in urban centers, while the high-level areas were in the mountainous region (in the southwest and southeast) and significantly expanded over time. Negative correlation clusters were the main clustering types between the UL and NPP; the “High-Low” negative correlation clusters accelerated outward from the urban centers of Chengdu and Chongqing. Overall, urbanization had negative direct and spillover effects on NPP, exhibiting spatial non-stationarity of the negative driving effect within the urban agglomeration. The results indicate the need to strengthen regional ecological joint governance and adopt more place-based urbanization optimization strategies. This study offers new insights to help to reduce the constraining effects of urbanization on vegetation productivity and ecological functions from the perspectives of population agglomeration, land expansion, and industrial construction

Computational synchronization of microarray data with application to Plasmodium falciparum

From IEEE International Conference on Bioinformatics and Biomedicine 2011 Atlanta, GA, USA. 12-15 November 2011Background Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. Methods We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. Results By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. Conclusions This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.United States. Dept. of Defense (ARO (Grant Number W911NF-09-1-0480)Singapore-MIT Alliance for Research and Technology (Graduate Fellowship