Single-Molecule Kinetics in Living Cells.

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize, and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods.

The Synchronization of Replication and Division Cycles in Individual E. coli Cells.

Isogenic E. coli cells growing in a constant environment display significant variability in growth rates, division sizes, and generation times. The guiding principle appears to be that each cell, during one generation, adds a size increment that is uncorrelated to its birth size. Here, we investigate the mechanisms underlying this "adder" behavior by mapping the chromosome replication cycle to the division cycle of individual cells using fluorescence microscopy. We have found that initiation of chromosome replication is triggered at a fixed volume per chromosome independent of a cell's birth volume and growth rate. Each initiation event is coupled to a division event after a growth-rate-dependent time. We formalize our findings in a model showing that cell-to-cell variation in division timing and cell size is mainly driven by variations in growth rate. The model also explains why fast-growing cells display adder behavior and correctly predict deviations from the adder behavior at slow growth.

RecA finds homologous DNA by reduced dimensionality search.

Homologous recombination is essential for the accurate repair of double-stranded DNA breaks (DSBs)1. Initially, the RecBCD complex2 resects the ends of the DSB into 3' single-stranded DNA on which a RecA filament assembles3. Next, the filament locates the homologous repair template on the sister chromosome4. Here we directly visualize the repair of DSBs in single cells, using high-throughput microfluidics and fluorescence microscopy. We find that, in Escherichia coli, repair of DSBs between segregated sister loci is completed in 15 ± 5 min (mean ± s.d.) with minimal fitness loss. We further show that the search takes less than 9 ± 3 min (mean ± s.d) and is mediated by a thin, highly dynamic RecA filament that stretches throughout the cell. We propose that the architecture of the RecA filament effectively reduces search dimensionality. This model predicts a search time that is consistent with our measurement and is corroborated by the observation that the search time does not depend on the length of the cell or the amount of DNA. Given the abundance of RecA homologues5, we believe this model to be widely conserved across living organisms.

DNA surface exploration and operator bypassing during target search.

Many proteins that bind specific DNA sequences search the genome by combining three-dimensional diffusion with one-dimensional sliding on nonspecific DNA1-5. Here we combine resonance energy transfer and fluorescence correlation measurements to characterize how individual lac repressor (LacI) molecules explore the DNA surface during the one-dimensional phase of target search. To track the rotation of sliding LacI molecules on the microsecond timescale, we use real-time single-molecule confocal laser tracking combined with fluorescence correlation spectroscopy (SMCT-FCS). The fluctuations in fluorescence signal are accurately described by rotation-coupled sliding, in which LacI traverses about 40 base pairs (bp) per revolution. This distance substantially exceeds the 10.5-bp helical pitch of DNA; this suggests that the sliding protein frequently hops out of the DNA groove, which would result in the frequent bypassing of target sequences. We directly observe such bypassing using single-molecule fluorescence resonance energy transfer (smFRET). A combined analysis of the smFRET and SMCT-FCS data shows that LacI hops one or two grooves (10-20 bp) every 200-700 µs. Our data suggest a trade-off between speed and accuracy during sliding: the weak nature of nonspecific protein-DNA interactions underlies operator bypassing, but also speeds up sliding. We anticipate that SMCT-FCS, which monitors rotational diffusion on the microsecond timescale while tracking individual molecules with millisecond resolution, will be applicable to the real-time investigation of many other biological interactions and will effectively extend the accessible time regime for observing these interactions by two orders of magnitude.

Antibiotic perseverance increases the risk of resistance development.

The rise of antibiotic-resistant bacterial infections poses a global threat. Antibiotic resistance development is generally studied in batch cultures which conceals the heterogeneity in cellular responses. Using single-cell imaging, we studied the growth response of Escherichia coli to sub-inhibitory and inhibitory concentrations of nine antibiotics. We found that the heterogeneity in growth increases more than what is expected from growth rate reduction for three out of the nine antibiotics tested. For two antibiotics (rifampicin and nitrofurantoin), we found that sub-populations were able to maintain growth at lethal antibiotic concentrations for up to 10 generations. This perseverance of growth increased the population size and led to an up to 40-fold increase in the frequency of antibiotic resistance mutations in gram-negative and gram-positive species. We conclude that antibiotic perseverance is a common phenomenon that has the potential to impact antibiotic resistance development across pathogenic bacteria.

Regulatory elements coordinating initiation of chromosome replication to the Escherichia coli cell cycle.

Escherichia coli coordinates replication and division cycles by initiating replication at a narrow range of cell sizes. By tracking replisomes in individual cells through thousands of division cycles in wild-type and mutant strains, we were able to compare the relative importance of previously described control systems. We found that accurate triggering of initiation does not require synthesis of new DnaA. The initiation size increased only marginally as DnaA was diluted by growth after dnaA expression had been turned off. This suggests that the conversion of DnaA between its active ATP- and inactive ADP-bound states is more important for initiation size control than the total free concentration of DnaA. In addition, we found that the known ATP/ADP converters DARS and datA compensate for each other, although the removal of them makes the initiation size more sensitive to the concentration of DnaA. Only disruption of the regulatory inactivation of DnaA mechanism had a radical impact on replication initiation. This result was corroborated by the finding that termination of one round of replication correlates with the next initiation at intermediate growth rates, as would be the case if RIDA-mediated conversion from DnaA-ATP to DnaA-ADP abruptly stops at termination and DnaA-ATP starts accumulating.

More Than Just Letters and Chemistry: Genomics Goes Mechanics.

Although ubiquitously thought of as a simple string of letters, DNA exhibits complex physicochemical properties. As a result, DNA can store information beyond the extensively studied explicit genetic message. The mechanical code of DNA has not been studied systematically in a genome-wide context until recent groundbreaking work by Basu et al.

Imaging-based screens of pool-synthesized cell libraries.

Mapping a genetic perturbation to a change in phenotype is at the core of biological research. Advances in microscopy have transformed these studies, but they have largely been confined to examining a few strains or cell lines at a time. In parallel, there has been a revolution in creating synthetic libraries of genetically altered cells with relative ease. Here we describe methods that combine these powerful tools to perform live-cell imaging of pool-generated strain libraries for improved biological discovery.

Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy.

Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safeguarding public health. For instance, identifying the species and its antibiotic susceptibility is vital for effective bacterial infection treatment. Here we show that phase contrast time-lapse microscopy combined with deep learning is sufficient to classify four species of bacteria relevant to human health. The classification is performed on living bacteria and does not require fixation or staining, meaning that the bacterial species can be determined as the bacteria reproduce in a microfluidic device, enabling parallel determination of susceptibility to antibiotics. We assess the performance of convolutional neural networks and vision transformers, where the best model attained a class-average accuracy exceeding 98%. Our successful proof-of-principle results suggest that the methods should be challenged with data covering more species and clinically relevant isolates for future clinical use.

Association between changed self-rated health and the risk of venous thromboembolism in Malmö Preventive Program: a cohort study.

Poor self-rated health (SRH) is associated with incident arterial cardiovascular disease in both sexes. Studies on the association between SRH and incident venous thromboembolism (VTE) show divergent results in women and no association in men. This study focuses on the association between change in SRH and incident VTE in a cohort of 11,558 men and 6682 women who underwent a baseline examination and assessment of SRH between 1974 and 1992 and a re-examination in 2002-2006. To investigate if changes in SRH over time affect the risk of incident VTE in men and women. During a follow-up time from the re-examination of more than 16 years, there was a lower risk for incident VTE among women if SRH changed from poor at baseline to very good/excellent (HR 0.46, 95% CI 0.28; 0.74) at the re-examination. Stable good SRH (good to very good/excellent at the re-examination, HR 0.60, 95% CI 0.42; 0.89), or change from good SRH at baseline into poor/fair at the re-examination (HR 0.68, 95% CI 0.51; 0.90) were all significantly associated with a reduced risk for VTE. All comparisons were done with the group with stable poor SRH. This pattern was not found among men. Regardless of a decreased or increased SRH during life, having an SRH of very good/excellent at any time point seems to be associated with a decreased risk of VTE among women.

Time-resolved imaging-based CRISPRi screening.

Our ability to connect genotypic variation to biologically important phenotypes has been seriously limited by the gap between live-cell microscopy and library-scale genomic engineering. Here, we show how in situ genotyping of a library of strains after time-lapse imaging in a microfluidic device overcomes this problem. We determine how 235 different CRISPR interference knockdowns impact the coordination of the replication and division cycles of Escherichia coli by monitoring the location of replication forks throughout on average >500 cell cycles per knockdown. Subsequent in situ genotyping allows us to map each phenotype distribution to a specific genetic perturbation to determine which genes are important for cell cycle control. The single-cell time-resolved assay allows us to determine the distribution of single-cell growth rates, cell division sizes and replication initiation volumes. The technology presented in this study enables genome-scale screens of most live-cell microscopy assays.

Association of Circulating Long Noncoding 7S RNA with Deep Vein Thrombosis.

Mitochondrial dysfunction is a recognized factor in the pathogenesis of deep vein thrombosis (DVT). The role of 7S RNA, a long noncoding RNA that plays an important role in mitochondrial function, in DVT remains unclear. In this study, we aimed to investigate the potential use of 7S RNA as a biomarker in DVT. Plasma samples were obtained from 237 patients (aged 16-95 years) with suspected DVT recruited in a prospective multicenter management study (SCORE) where 53 patients were objectively confirmed with a diagnosis of DVT and the rest were diagnosed as non-DVT. 7S RNA was measured using quantitative real-time polymerase chain reaction in plasma samples. The plasma expression of 7S RNA was significantly lower in DVT compared with non-DVT (0.50 vs. 0.95, p = 0.043). With the linear regression analysis, we showed that the association between the plasma expression of 7S RNA and DVT (ß = -0.72, p = 0.007) was independent of potential confounders. Receiver-operating characteristic curve analysis showed the area under the curve values of 0.60 for 7S RNA. The findings of the present study showed a notable association between 7S RNA and DVT. However, further investigations are needed to fully elucidate the exact role of 7S RNA in the pathophysiology of DVT and its diagnostic value.

Incidental pulmonary embolism in patients with cancer: prevalence, underdiagnosis and evaluation of an AI algorithm for automatic detection of pulmonary embolism.

OBJECTIVES: To assess the prevalence of reported and unreported incidental pulmonary embolism (iPE) in patients with cancer, and to evaluate an artificial intelligence (AI) algorithm for automatic detection of iPE. METHODS: Retrospective cohort study on patients with cancer with an elective CT study including the chest between 2018-07-01 and 2019-06-30. All study reports and images were reviewed to identify reported and unreported iPE and were processed by the AI algorithm. RESULTS: One thousand sixty-nine patients (1892 studies) were included. Per study, iPE was present in 75 studies (4.0%), of which 16 (21.3%) were reported. Unreported iPE had a significantly lower number of involved vessels compared to reported iPE, with a median of 2 (interquartile range, IQR, 1-4) versus 5 (IQR 3-9.75), p < 0.001. There were no significant differences in age, cancer type, or attenuation of the main pulmonary artery. The AI algorithm correctly identified 68 of 75 iPE, with 3 false positives (sensitivity 90.7%, specificity 99.8%, PPV 95.6%, NPV 99.6%). False negatives occurred in cases with 1-3 involved vessels. Of the unreported iPE, 32/59 (54.2%) were proximal to the subsegmental arteries. CONCLUSION: In patients with cancer, the prevalence of iPE was 4.0%, of which only 21% were reported. Greater than 50% of unreported iPE were proximal to the subsegmental arteries. The AI algorithm had a very high sensitivity and specificity with only three false positives, with the potential to increase the detection rate of iPE. KEY POINTS: • In a retrospective single-center study on patients with cancer, unreported iPE were common, with the majority lying proximal to the subsegmental arteries. • The evaluated AI algorithm had a very high sensitivity and specificity, so has the potential to increase the detection rate of iPE.

Can molecular dynamics be used to simulate biomolecular recognition?

There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challenged by the size of systems and the time scales needed to describe relevant motions. In theory, enhanced sampling algorithms can help to overcome some of the limitations of molecular simulations. Here, we discuss a problem in biochemistry that offers a significant challenge for enhanced sampling methods and that could, therefore, serve as a benchmark for comparing approaches that use machine learning to find suitable collective variables. In particular, we study the transitions LacI undergoes upon moving between being non-specifically and specifically bound to DNA. Many degrees of freedom change during this transition and that the transition does not occur reversibly in simulations if only a subset of these degrees of freedom are biased. We also explain why this problem is so important to biologists and the transformative impact that a simulation of it would have on the understanding of DNA regulation.

Contact-dependent growth inhibition induces high levels of antibiotic-tolerant persister cells in clonal bacterial populations.

Bacterial populations can use bet-hedging strategies to cope with rapidly changing environments. One example is non-growing cells in clonal bacterial populations that are able to persist antibiotic treatment. Previous studies suggest that persisters arise in bacterial populations either stochastically through variation in levels of global signalling molecules between individual cells, or in response to various stresses. Here, we show that toxins used in contact-dependent growth inhibition (CDI) create persisters upon direct contact with cells lacking sufficient levels of CdiI immunity protein, which would otherwise bind to and neutralize toxin activity. CDI-mediated persisters form through a feedforward cycle where the toxic activity of the CdiA toxin increases cellular (p)ppGpp levels, which results in Lon-mediated degradation of the immunity protein and more free toxin. Thus, CDI systems mediate a population density-dependent bet-hedging strategy, where the fraction of non-growing cells is increased only when there are many cells of the same genotype. This may be one of the mechanisms of how CDI systems increase the fitness of their hosts.

Association between self-rated health and venous thromboembolism in Malmö Preventive Program: A cohort study.

INTRODUCTION: Venous thromboembolism (VTE) and cardiovascular disease (CVD) share some risk factors such as smoking, obesity, and dietary habits. Poor self-rated health (SRH) has been shown to be a predictor of arterial CVD and mortality for both men and women. The association between SRH and VTE has only been investigated in one previous Swedish study with a cohort that just contained women. This Swedish study did not show any significant associations between poor SRH and VTE in women. METHODS: A cohort of 22,444 men and 10,902 women in the Malmö Preventive Program was followed for a period of 44 years. All participants in the baseline screening with measurements including SRH were traced in national registers. Data on VTE events were collected from national hospital registries. Cox proportional regression analysis was used to calculate the association between SRH and time to VTE. RESULTS: During a follow-up time of 44.31 years, a total of 2612 individuals were affected by VTE. Good SRH was associated with a lower risk for VTE in women both in the univariate model (HR = 0.75, CI = 0.65-0.85) and after adjustments for age, smoking, BMI and varicose veins (HR = 0.81, CI 0.70-0.93). SRH was not a predictor for VTE in men, neither in the unadjusted (HR = 1.05, CI 0.90-1.13) nor in the fully adjusted model (HR = 1.00, CI = 0.88-1.14). CONCLUSION: In this cohort study, SRH was associated with VTE in women but not among men. The association was significant even when adjusting for well-known risk factors such as varicose veins, BMI and smoking.

Author Correction: tRNA tracking for direct measurements of protein synthesis kinetics in live cells.

In the version of this article originally published, the values on the y axis of Fig. 6d were incorrect. They should be 0.00, 0.02, 0.04, 0.06 and 0.08 instead of the previous 0.00, 0.04, 0.08 and 0.12. The error has been corrected in the HTML and PDF versions of this paper.

tRNA tracking for direct measurements of protein synthesis kinetics in live cells.

Our ability to directly relate results from test-tube biochemical experiments to the kinetics in living cells is very limited. Here we present experimental and analytical tools to directly study the kinetics of fast biochemical reactions in live cells. Dye-labeled molecules are electroporated into bacterial cells and tracked using super-resolved single-molecule microscopy. Trajectories are analyzed by machine-learning algorithms to directly monitor transitions between bound and free states. In particular, we measure the dwell time of tRNAs on ribosomes, and hence achieve direct measurements of translation rates inside living cells at codon resolution. We find elongation rates with tRNAPhe that are in perfect agreement with previous indirect estimates, and once fMet-tRNAfMet has bound to the 30S ribosomal subunit, initiation of translation is surprisingly fast and does not limit the overall rate of protein synthesis. The experimental and analytical tools for direct kinetics measurements in live cells have applications far beyond bacterial protein synthesis.

Antibiotic susceptibility testing in less than 30 min using direct single-cell imaging.

The emergence and spread of antibiotic-resistant bacteria are aggravated by incorrect prescription and use of antibiotics. A core problem is that there is no sufficiently fast diagnostic test to guide correct antibiotic prescription at the point of care. Here, we investigate if it is possible to develop a point-of-care susceptibility test for urinary tract infection, a disease that 100 million women suffer from annually and that exhibits widespread antibiotic resistance. We capture bacterial cells directly from samples with low bacterial counts (104 cfu/mL) using a custom-designed microfluidic chip and monitor their individual growth rates using microscopy. By averaging the growth rate response to an antibiotic over many individual cells, we can push the detection time to the biological response time of the bacteria. We find that it is possible to detect changes in growth rate in response to each of nine antibiotics that are used to treat urinary tract infections in minutes. In a test of 49 clinical uropathogenic Escherichia coli (UPEC) isolates, all were correctly classified as susceptible or resistant to ciprofloxacin in less than 10 min. The total time for antibiotic susceptibility testing, from loading of sample to diagnostic readout, is less than 30 min, which allows the development of a point-of-care test that can guide correct treatment of urinary tract infection.