Single Nitrogen-Vacancy Imaging in Nanodiamonds for Multimodal Sensing

BIOPHYSICAL JOURNAL 116:3 (2019) 174A-174A

Authors:

Maabur Sow, Horst Steuer, Barak Gilboa, Laia Gines, Soumen Mandal, Sanmi Adekanye, Jason M Smith, Oliver A Williams, Achillefs N Kapanidis

Pausing controls branching between productive and non-productive pathways during initial transcription in bacteria

Nature Communications Nature Publishing Group 9 (2018) Article number 1478

Authors:

David Dulin, David Bauer, Anssi Malinen, Jacob Bakermans, Martin Kaller, Z Morichaud, I Petushkov, M Depken, K Brodolin, A Kulbachinskiy, Achillefs Kapanidis

Abstract:

Transcription in bacteria is controlled by multiple molecular mechanisms that precisely regulate gene expression. It has been recently shown that initial RNA synthesis by the bacterial RNA polymerase (RNAP) is interrupted by pauses; however, the pausing determinants and the relationship of pausing with productive and abortive RNA synthesis remain poorly understood. Using single-molecule FRET and biochemical analysis, here we show that the pause encountered by RNAP after the synthesis of a 6-nt RNA (ITC6) renders the promoter escape strongly dependent on the NTP concentration. Mechanistically, the paused ITC6 acts as a checkpoint that directs RNAP to one of three competing pathways: productive transcription, abortive RNA release, or a new unscrunching/scrunching pathway. The cyclic unscrunching/scrunching of the promoter generates a long-lived, RNA-bound paused state; the abortive RNA release and DNA unscrunching are thus not as tightly linked as previously thought. Finally, our new model couples the pausing with the abortive and productive outcomes of initial transcription.

Single-molecule tracking reveals the functional allocation, in vivo interactions, and spatial organization of universal transcription factor NusG.

Molecular cell 84:5 (2024) 926-937.e4

Authors:

Hafez El Sayyed, Oliver J Pambos, Mathew Stracy, Max E Gottesman, Achillefs N Kapanidis

Abstract:

During transcription elongation, NusG aids RNA polymerase by inhibiting pausing, promoting anti-termination on rRNA operons, coupling transcription with translation on mRNA genes, and facilitating Rho-dependent termination. Despite extensive work, the in vivo functional allocation and spatial distribution of NusG remain unknown. Using single-molecule tracking and super-resolution imaging in live E. coli cells, we found NusG predominantly in a chromosome-associated population (binding to RNA polymerase in elongation complexes) and a slowly diffusing population complexed with the 30S ribosomal subunit; the latter provides a "30S-guided" path for NusG into transcription elongation. Only ∼10% of NusG is fast diffusing, with its mobility suggesting non-specific interactions with DNA for >50% of the time. Antibiotic treatments and deletion mutants revealed that chromosome-associated NusG participates mainly in rrn anti-termination within phase-separated transcriptional condensates and in transcription-translation coupling. This study illuminates the multiple roles of NusG and offers a guide on dissecting multi-functional machines via in vivo imaging.

Aberrant topologies of bacterial membrane proteins revealed by high sensitivity fluorescence labelling

Journal of Molecular Biology Elsevier 436:2 (2023) 168368

Authors:

Helen Miller, Alfredas Bukys, Achillefs Kapanidis, Benjamin Berks

Deep learning and single-cell phenotyping for rapid antimicrobial susceptibility detection in Escherichia coli.

Communications biology 6:1 (2023) 1164

Authors:

Alexander Zagajewski, Piers Turner, Conor Feehily, Hafez El Sayyed, Monique Andersson, Lucinda Barrett, Sarah Oakley, Mathew Stracy, Derrick Crook, Christoffer Nellåker, Nicole Stoesser, Achillefs N Kapanidis

Abstract:

The rise of antimicrobial resistance (AMR) is one of the greatest public health challenges, already causing up to 1.2 million deaths annually and rising. Current culture-based turnaround times for bacterial identification in clinical samples and antimicrobial susceptibility testing (AST) are typically 18-24 h. We present a novel proof-of-concept methodological advance in susceptibility testing based on the deep-learning of single-cell specific morphological phenotypes directly associated with antimicrobial susceptibility in Escherichia coli. Our models can reliably (80% single-cell accuracy) classify untreated and treated susceptible cells for a lab-reference fully susceptible E. coli strain, across four antibiotics (ciprofloxacin, gentamicin, rifampicin and co-amoxiclav). For ciprofloxacin, we demonstrate our models reveal significant (p < 0.001) differences between bacterial cell populations affected and unaffected by antibiotic treatment, and show that given treatment with a fixed concentration of 10 mg/L over 30 min these phenotypic effects correlate with clinical susceptibility defined by established clinical breakpoints. Deploying our approach on cell populations from six E. coli strains obtained from human bloodstream infections with varying degrees of ciprofloxacin resistance and treated with a range of ciprofloxacin concentrations, we show single-cell phenotyping has the potential to provide equivalent information to growth-based AST assays, but in as little as 30 min.