The displacement of the σ70 finger in initial transcription is highly heterogeneous and promoter-dependent
Nucleic Acids Research Oxford University Press (OUP) 53:17 (2025) gkaf857
Abstract:
Most bacterial sigma factors (σ) contain a highly conserved structural module, the 'σ-finger', which forms a loop that protrudes towards the RNA polymerase active centre in the open complex and has been implicated in pre-organization of template DNA, abortive initiation of short RNAs, initiation pausing, and promoter escape. Here, we introduce a novel single-molecule FRET (smFRET) assay to monitor σ-finger motions during transcription initiation and promoter escape. By performing real-time smFRET measurements, we determine that for all promoters studied, displacement occurs before promoter escape and can occur either before or after a clash with the extending RNA. We show that the kinetics of σ-finger displacement are highly dependent on the promoter, with implications for transcription kinetics and regulation. Analogous mechanisms may operate in the similar modules present across all kingdoms of life.Pointwise prediction of protein diffusive properties using machine learning
JPhys: Photonics IOP Publishing 7:3 (2025) 035025
Abstract:
The understanding of cellular mechanisms benefits substantially from accurate determination of protein diffusive properties. Prior work in this field primarily focuses on traditional methods, such as mean square displacements, for calculation of protein diffusion coefficients and biological states. This proves difficult and error-prone for proteins undergoing heterogeneous behaviour, particularly in complex environments, limiting the exploration of new biological behaviours. The importance of determining protein diffusion coefficients, anomalous exponents, and biological behaviours led to the Anomalous Diffusion Challenge 2024, exploring machine learning methods to infer these variables in heterogeneous trajectories with time-dependent changepoints. In response to the challenge, we present M3, a machine learning method for pointwise inference of diffusive coefficients, anomalous exponents, and states along noisy heterogenous protein trajectories. M3 makes use of long short-term memory cells to achieve small mean absolute errors for the diffusion coefficient and anomalous exponent alongside high state accuracies (>90%). Subsequently, we implement changepoint detection to determine timepoints at which protein behaviour changes. M3 removes the need for expert fine-tuning required in most conventional statistical methods while being computationally inexpensive to train. The model finished in the Top 5 of the Anomalous Diffusive Challenge 2024, with small improvements made since challenge closure.Tunable fluorogenic DNA probes drive fast and high-resolution single-molecule fluorescence imaging
Nucleic Acids Research Oxford University Press 53:13 (2025) gkaf593
Abstract:
A main limitation of single-molecule fluorescence (SMF) measurements is the 'high concentration barrier', describing the maximum concentration of fluorescent species tolerable for sufficient signal-to-noise ratio. To address this barrier in several SMF applications, we design fluorogenic probes based on short single-stranded DNAs, fluorescing only upon hybridizing to their complementary target sequence. We engineer the quenching efficiency and fluorescence enhancement upon duplex formation through screening several fluorophore-quencher combinations, label lengths, and sequence motifs, which we utilize as tuning screws to adapt our labels to different experimental designs. Using these fluorogenic probes, we can perform SMF experiments at concentrations of 10 μM fluorescent labels; this concentration is 100-fold higher than the operational limit for standard TIRF experiments. We demonstrate the ease of implementing these probes into existing protocols by performing super-resolution imaging with DNA-PAINT, employing a fluorogenic 6-nt-long imager; through the faster acquisition of binding events, the imaging of viral genome segments could be sped up significantly to achieve extraction of 20-nm structural features with only ∼150 s of imaging. The exceptional tunability of our probe design will overcome concentration barriers in SMF experiments and unlock new possibilities in super-resolution imaging, molecular tracking, and single-molecule fluorescence energy transfer (smFRET).Single-molecule imaging for unraveling the functional diversity of 10–23 DNAzymes
Analytical Chemistry American Chemical Society 97:25 (2025) 13300-13309
Abstract:
DNA-based enzymes, also known as DNAzymes, have opened new opportunities for signal generation and amplification in several fields including biosensing. However, biosensor performance can be hampered by heterogeneity in the catalytic activity of such DNAzymes, especially when relying on a limited number of molecules to generate signal. In this regard, single-molecule studies are essential to discern the behavior among such heterogeneous molecules otherwise masked by ensemble measurements. This work presents a novel methodology to study the 10–23 RNA-cleaving DNAzyme at the single-molecule level. By means of measuring the distance-sensitive efficiency of Förster Resonance Energy Transfer using alternating-laser excitation on a superresolution microscope, we determined the kinetics of individual DNAzymes in terms of substrate turnover, rates of different reaction steps, and changes in performance over time. Our results revealed that, despite high concentrations of the reaction cofactor (i.e., Mg2+), a maximum of only 70% of the DNAzymes are actively cleaving multiple substrate sequences; the DNAzyme molecules also showed a wide range of substrate turnover rates. Our findings shed new light on the functional diversity of DNAzymes and the importance of exploring sequence modifications to improve their catalytic performance. Ultimately, this work presents a technique to obtain time-dependent information, which could be easily implemented to study other types of enzymes or biomolecular interactions.In vivo single-molecule imaging of RecB reveals efficient repair of DNA damage in Escherichia coli
Nucleic Acids Research Oxford University Press 53:10 (2025) gkaf454