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1. Deciphering transcript architectural complexity in bacteria and archaea

   https://doi.org/10.1128/mbio.02359-24  

   Mattick, John_S A; Bromley, Robin E; Watson, Kaylee J; Adkins, Ricky S; Holt, Christopher I; Lebov, Jarrett F; Sparklin, Benjamin C; Tyson, Tyonna S; Rasko, David A; Dunning_Hotopp, Julie C (October 2024, mBio)

   Parkhill, Julian (Ed.)

   ABSTRACT RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) inEscherichia coliK12 and E2348/69 strains (Bacteria:gamma-Proteobacteria),Listeria monocytogenesstrains Scott A and RO15 (Bacteria:Firmicute),Pseudomonas aeruginosastrains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), andHaloferax volcanii(Archaea:Halobacteria). From >5 millionE. coliK12 and >3 millionE. coliE2348/69 newly generated Oxford Nanopore Technologies direct RNA sequencing reads, 2,487 K12 mRNAs and 1,844 E2348/69 mRNAs were predicted, with the K12 mRNAs containing more than half of the predictedE. coliK12 proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used, across all strains examined, the predicted average size of the mRNAs was 1.6–1.7 kbp, while the median size of the 5′- and 3′-untranslated regions (UTRs) were 30–90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions were of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in theE. coliE2348/69LEEpathogenicity islands. We predicted small transcripts in the 100–200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being thenuooperon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, and reproducible method will facilitate the presentation of transcripts, and UTR predictions alongside coding sequences and protein predictions in bacterial genome annotation as important resources for the research community.IMPORTANCEOur understanding of bacterial and archaeal genes and genomes is largely focused on proteins since there have only been limited efforts to describe bacterial/archaeal RNA diversity. This contrasts with studies on the human genome, where transcripts were sequenced prior to the release of the human genome over two decades ago. We developed software for the quick, easy, and reproducible prediction of bacterial and archaeal transcripts from Oxford Nanopore Technologies direct RNA sequencing data. These predictions are urgently needed for more accurate studies examining bacterial/archaeal gene regulation, including regulation of virulence factors, and for the development of novel RNA-based therapeutics and diagnostics to combat bacterial pathogens, like those with extreme antimicrobial resistance. 

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2. Designing efficient genetic code expansion in Bacillus subtilis to gain biological insights

   https://doi.org/10.1038/s41467-021-25691-4  

   Stork, Devon A.; Squyres, Georgia R.; Kuru, Erkin; Gromek, Katarzyna A.; Rittichier, Jonathan; Jog, Aditya; Burton, Briana M.; Church, George M.; Garner, Ethan C.; Kunjapur, Aditya M. (September 2021, Nature Communications)

   Abstract Bacillus subtilisis a model gram-positive bacterium, commonly used to explore questions across bacterial cell biology and for industrial uses. To enable greater understanding and control of proteins inB. subtilis, here we report broad and efficient genetic code expansion inB. subtilisby incorporating 20 distinct non-standard amino acids within proteins using 3 different families of genetic code expansion systems and two choices of codons. We use these systems to achieve click-labelling, photo-crosslinking, and translational titration. These tools allow us to demonstrate differences betweenE. coliandB. subtilisstop codon suppression, validate a predicted protein-protein binding interface, and begin to interrogate properties underlying bacterial cytokinesis by precisely modulating cell division dynamics in vivo. We expect that the establishment of this simple and easily accessible chemical biology system inB. subtiliswill help uncover an abundance of biological insights and aid genetic code expansion in other organisms. 

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3. Lipid bilayer induces contraction of the denatured state ensemble of a helical-bundle membrane protein

   https://doi.org/10.1073/pnas.2109169119  

   Gaffney, Kristen_A; Guo, Ruiqiong; Bridges, Michael_D; Muhammednazaar, Shaima; Chen, Daoyang; Kim, Miyeon; Yang, Zhongyu; Schilmiller, Anthony_L; Faruk, Nabil_F; Peng, Xiangda; et al (December 2021, Proceedings of the National Academy of Sciences)

   Defining the denatured state ensemble (DSE) and disordered proteins is essential to understanding folding, chaperone action, degradation, and translocation. As compared with water-soluble proteins, the DSE of membrane proteins is much less characterized. Here, we measure the DSE of the helical membrane protein GlpG ofEscherichia coli(E. coli) in native-like lipid bilayers. The DSE was obtained using our steric trapping method, which couples denaturation of doubly biotinylated GlpG to binding of two streptavidin molecules. The helices and loops are probed using limited proteolysis and mass spectrometry, while the dimensions are determined using our paramagnetic biotin derivative and double electron–electron resonance spectroscopy. These data, along with ourUpsidesimulations, identify the DSE as being highly dynamic, involving the topology changes and unfolding of some of the transmembrane (TM) helices. The DSE is expanded relative to the native state but only to 15 to 75% of the fully expanded condition. The degree of expansion depends on the local protein packing and the lipid composition.E. coli’s lipid bilayer promotes the association of TM helices in the DSE and, probably in general, facilitates interhelical interactions. This tendency may be the outcome of a general lipophobic effect of proteins within the cell membranes. 

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4. Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

   https://doi.org/10.1038/s41467-024-49920-8  

   Gupta, Meera; Johnson, Alex_N_T; Cruz, Edward_R; Costa, Eli_J; Guest, Randi_L; Li, Sophia_Hsin-Jung; Hart, Elizabeth_M; Nguyen, Thao; Stadlmeier, Michael; Bratton, Benjamin_P; et al (July 2024, Nature Communications)

   Abstract Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studiedE. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200E. coliproteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway inE. coliremains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates inE. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis. 

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5. Promoter Architecture Differences among Alphaproteobacteria and Other Bacterial Taxa

   https://doi.org/10.1128/mSystems.00526-21  

   Myers, Kevin S.; Noguera, Daniel R.; Donohue, Timothy J. (August 2021, mSystems)

   Faust, Karoline (Ed.)

   ABSTRACT Much of our knowledge of bacterial transcription initiation has been derived from studying the promoters of Escherichia coli and Bacillus subtilis . Given the expansive diversity across the bacterial phylogeny, it is unclear how much of this knowledge can be applied to other organisms. Here, we report on bioinformatic analyses of promoter sequences of the primary σ factor (σ 70 ) by leveraging publicly available transcription start site (TSS) sequencing data sets for nine bacterial species spanning five phyla. This analysis identifies previously unreported differences in the −35 and −10 elements of σ 70 -dependent promoters in several groups of bacteria. We found that Actinobacteria and Betaproteobacteria σ 70 -dependent promoters lack the TTG triad in their −35 element, which is predicted to be conserved across the bacterial phyla. In addition, the majority of the Alphaproteobacteria σ 70 -dependent promoters analyzed lacked the thymine at position −7 that is highly conserved in other phyla. Bioinformatic examination of the Alphaproteobacteria σ 70 -dependent promoters identifies a significant overrepresentation of essential genes and ones encoding proteins with common cellular functions downstream of promoters containing an A, C, or G at position −7. We propose that transcription of many σ 70 -dependent promoters in Alphaproteobacteria depends on the transcription factor CarD, which is an essential protein in several members of this phylum. Our analysis expands the knowledge of promoter architecture across the bacterial phylogeny and provides new information that can be used to engineer bacteria for use in medical, environmental, agricultural, and biotechnological processes. IMPORTANCE Transcription of DNA to RNA by RNA polymerase is essential for cells to grow, develop, and respond to stress. Understanding the process and control of transcription is important for health, disease, the environment, and biotechnology. Decades of research on a few bacteria have identified promoter DNA sequences that are recognized by the σ subunit of RNA polymerase. We used bioinformatic analyses to reveal previously unreported differences in promoter DNA sequences across the bacterial phylogeny. We found that many Actinobacteria and Betaproteobacteria promoters lack a sequence in their −35 DNA recognition element that was previously assumed to be conserved and that Alphaproteobacteria lack a thymine residue at position −7, also previously assumed to be conserved. Our work reports important new information about bacterial transcription, illustrates the benefits of studying bacteria across the phylogenetic tree, and proposes new lines of future investigation. 

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