Transcription factors (TFs) efficiently locate their target DNA sequences by combining three-dimensional diffusion and one-dimensional sliding on nonspecific DNA. To balance rapid sliding with strong specific binding, TFs were proposed to switch between search and recognition conformations. For Escherichia coli lac repressor (LacI), the folding of the hinge helices has been implicated in the conformational switch. Here, we tested how mutations in the hinge region impact the search speed and binding stability. Based on molecular dynamics simulations, we selected two LacI mutants favoring either search or recognition conformation. We measured the binding kinetics of the mutants both in vitro on DNA microarrays with 2479 different Lac operators and in vivo via single-molecule experiments. We identified a mutation that enhances the specificity but reduces binding strength globally, and another mutation that makes the operator binding stronger but also reduces the specificity. However, the altered specificity impacts the search time less than expected. Instead, the major effect was impaired dissociation in response to Isopropyl β-D-1-thiogalactopyranoside (IPTG) induction for the strongly binding mutant. Together with earlier reports of affinity-inducibility trade-offs in LacI, our data support the model in which the trade-off is between binding stability and inducibility rather than between speed and binding stability.

Optical pooled screening is an important tool to study dynamic phenotypes for libraries of genetically engineered cells. However, the desired engineering often requires that the barcodes used for in situ genotyping are expressed from the chromosome. This has not previously been achieved in bacteria. Here we describe a method for in situ genotyping of libraries with genomic barcodes in Escherichia coli. The method is applied to measure the intracellular maturation time of 84 red fluorescent proteins.

The blood of a septic patient contains only a few bacteria per milliliter. Recently, various techniques have been developed for extracting these few bacteria from a blood sample. Independent of how these bacteria are separated from the blood cells, we want to learn from them how to treat the infection. Here, we describe how a phenotypic Antibiotic Susceptibility Test can be executed with a single bacterial cell by making averages over time instead of populations, if we account for the experimental noise and cell-to-cell variability. We use the method to make preliminary estimates for how long it takes to distinguish a single susceptible from a resistant cell with statistical confidence. We also exemplify how it is possible to sequentially test different antibiotics, or different concentrations of the same antibiotic, on one cell lineage until a susceptible phenotype is detected. The assay can be followed by single-cell species identification using FISH probes. ### Competing Interest Statement A patent has been filed for the method.

Transcription factors (TFs) efficiently locate their target DNA sequences by combining three-dimensional diffusion and one-dimensional sliding on nonspecific DNA. To balance rapid sliding with strong specific binding, TFs were proposed to switch between search and recognition conformations. For E. coli lac repressor (LacI), the folding of the hinge helices has been implicated in the conformational switch. Here, we tested how mutations in the hinge region impact the search speed and binding stability. Based on molecular dynamics simulations, we selected two LacI mutants favoring either search or recognition conformation. We measured the binding kinetics of the mutants both in vitro on DNA microarrays with 2,479 different Lac operators and in vivo via single-molecule experiments. We conclude that a hinge region mutation causing less helix propensity enhances the specificity but reduces binding strength globally, while a hinge region mutation causing higher helix propensity has opposite effects. However, altered specificity impacts the search time less than expected. Instead, the major effect was impaired dissociation in response to IPTG induction for the strongly binding mutant. Together with earlier reports of affinity-inducibility trade-offs in LacI, our data support the model in which the hinge region governs a trade-off between binding stability and inducibility rather than between speed and binding stability.

Approximately 50 million people suffer from sepsis yearly, and 13 million die from it. For every hour a patient with septic shock is untreated, their survival rate decreases by 8%. Therefore, rapid detection and antibiotic susceptibility profiling of bacterial agents in the blood of sepsis patients are crucial for determining appropriate treatment. Here, we introduce a method to isolate bacteria from whole blood with high separation efficiency through Smart centrifugation, followed by microfluidic trapping and subsequent detection using deep learning applied to microscopy images. We detected, within 2 h, E. coli, K. pneumoniae, or E. faecalis from spiked samples of healthy human donor blood at clinically relevant concentrations as low as 9, 7 and 32 colony-forming units per ml of blood, respectively. However, the detection of S. aureus remains a challenge. This rapid isolation and detection represents a significant advancement towards culture-free detection of bloodstream infections.

The rate at which transcription factors (TFs) bind their cognate sites has long been assumed to be limited by diffusion, and thus independent of binding site sequence. Here, we systematically test this assumption using cell-to-cell variability in gene expression as a window into the in vivo association and dissociation kinetics of the model transcription factor LacI. Using a stochastic model of the relationship between gene expression variability and binding kinetics, we performed single-cell gene expression measurements to infer association and dissociation rates for a set of 35 different LacI binding sites. We found that both association and dissociation rates differed significantly between binding sites, and moreover observed a clear anticorrelation between these rates across varying binding site strengths. These results contradict the long-standing hypothesis that TF binding site strength is primarily dictated by the dissociation rate, but may confer the evolutionary advantage that TFs do not get stuck in near-operator sequences while searching.

Drug-resistant tuberculosis (DR-TB) kills ~200,000 people every year. A contributing factor is the slow turnaround time (TAT) associated with drug susceptibility diagnostics. The prevailing gold standard for phenotypic drug susceptibility testing (pDST) takes at least two weeks. Here we show that growth-based pDST for slow-growing mycobacteria can be conducted in 12 h. We use Mycobacterium tuberculosis variant bovis Bacillus Calmette-Guérin (BCG) and Mycobacterium smegmatis as the mycobacterial pathogen models and expose them to antibiotics used in (multidrug-resistant) tuberculosis (TB) treatment regimens - i.e ., rifampicin (RIF), isoniazid (INH), ethambutol (EMB), linezolid (LZD), streptomycin (STR), bedaquiline (BDQ), and levofloxacin (LFX). The bacterial growth in a microfluidic chip is tracked by time-lapse phase-contrast microscopy. A deep neural network-based segmentation algorithm is used to quantify the growth rate and to determine how the strains responded to drug treatments. Most importantly, a panel of susceptible and resistant M. bovis BCG are tested at critical concentrations for INH, RIF, STR, and LFX. The susceptible strains could be identified in less than 12 h. These findings are comparable to what we expect for pathogenic M. tuberculosis as they share 99.96% genetic identity.

Background: As patients undergoing cancer surgery are at a higher risk of developing venous thromboembolism (VTE), guidelines recommend anticoagulant prophylaxis with low-molecular-weight heparins (LMWH). Information about prophylaxis patterns of LMWH and outcomes in patients after cancer surgery in Swedish clinical practice is scarce. Knowledge about to what extent treatment guidelines are followed is also lacking. Swedish health care registers provide a unique opportunity to investigate treatment patterns and outcomes in the total Swedish population. An overall objective of this research program is to explore the extent of LMWH use as prophylaxis among Swedish cancer surgery patients. Specifically, the objective is to analyse the prophylaxis patterns and outcomes in terms of major bleedings, VTE and mortality in use of LMWHs in different patient populations (e.g. cancer surgery patients with urogenital, gastrointestinal, and gynecological cancers)

In Escherichia coli, it is debated whether the two replisomes move independently along the two chromosome arms during replication or if they remain spatially confined. Here, we use high-throughput fluorescence microscopy to simultaneously determine the location and short-time-scale (1 s) movement of the replisome and a chromosomal locus throughout the cell cycle. The assay is performed for several loci. We find that (i) the two replisomes are confined to a region of ~250 nm and ~120 nm along the cell’s long and short axis, respectively, (ii) the chromosomal loci move to and through this region sequentially based on their distance from the origin of replication, and (iii) when a locus is being replicated, its short time-scale movement slows down. This behavior is the same at different growth rates. In conclusion, our data supports a model with DNA moving towards spatially confined replisomes at replication.

Drug-resistant tuberculosis (TB) kills approximately 200,000 people every year. A contributing factor is the slow turnaround time associated with anti-tuberculosis drug susceptibility diagnostics. The prevailing gold standard for phenotypic drug susceptibility testing (pDST) takes at least two weeks. In this study, we used Mycobacterium tuberculosis variant bovis BCG (M. bovis BCG) and Mycobacterium smegmatis as models for tuberculous and nontuberculous pathogens. The bacteria were loaded into a microfluidic chip, trapping them in microchambers, and allowing simultaneous tracking of single-cell growth with and without antibiotic exposure. A deep neural network image-segmentation algorithm was employed to quantify the growth rate over time and determine how the strains responded to the drugs compared to the untreated reference. We determined that the response time of the susceptible strains to isoniazid (INH), ethambutol (EMB), and linezolid (LZD) at MIC was within 3 hours and 1.5 hours for M. bovis BCG and M. smegmatis, respectively. Resistant strains of M. smegmatis were identifiable within 3 hours, suggesting that growth-based pDST can be conducted in less than 12 hours for slow-growing M. bovis BCG. The results obtained for M. bovis BCG are most likely comparable to what we expect for M. tuberculosis as these strains share 99.96% genetic identity.### Competing Interest StatementJ.E. has patented the method (US10,041,104) and founded Astrego Diagnostics, but he has no current association with the company. All other authors declare no competing interests.

The 3D point spread function of a fluorescence emitter in a living cell is often different from that of the z-stack of bead images typically used as a reference. Here we show that the location in z of a fluorescent emitter can be directly accessed in the latent space of an autoencoder trained on the sample images without z-reference data. The corresponding decoding network represents an accurate point spread function. ### Competing Interest Statement The authors have declared no competing interest.

Rapid detection and antibiotic susceptibility profiling of bacterial agents in the blood of sepsis patients are crucial for determining appropriate treatment. The low bacteria concentrations and high abundance of blood cells currently necessitate culture-based diagnostic methods, which can take several days. Here, we introduce a method to isolate bacteria from whole blood with high separation power by smart centrifugation, followed by detection through microscopy in microfluidic traps within 2 h without the need for blood culture. We detected E. coli, K. pneumonia , or E. faecalis from spiked samples of healthy human donor blood at clinically relevant concentrations as low as 9, 7 and 32 colony-forming units per ml of blood, respectively. This rapid isolation of living bacteria from blood at clinically relevant concentrations opens possibilities for rapid phenotypic antibiotic susceptibility testing for bloodstream infections without blood culture. ### Competing Interest Statement Yes there is potential Competing Interest. The authors aim to secure IP protection for at least parts of this manuscript. JE and WW have commercial interests in the diagnostics field including IP but not directly related to isolation of bacteria from blood

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.

AbstractThe intracellular position of genes may impact their expression, but it has not been possible to accurately measure the 3D position of chromosomal loci. In 2D, loci can be tracked using arrays of DNA-binding sites for transcription factors (TFs) fused with fluorescent proteins. However, the same 2D data can result from different 3D trajectories. Here, we have developed a deep learning method for super-resolved astigmatism-based 3D localization of chromosomal loci in live E. coli cells which enables a precision better than 61 nm at a signal-to-background ratio of ~4 on a heterogeneous cell background. Determining the spatial localization of chromosomal loci, we find that some loci are at the periphery of the nucleoid for large parts of the cell cycle. Analyses of individual trajectories reveal that these loci are subdiffusive both longitudinally (x) and radially (r), but that individual loci explore the full radial width on a minute time scale.

Background Tissue factor (TF), encoded by the F3 gene, is the main initiator of blood coagulation. The molecular epidemiology of the F3 gene and the relation to venous thromboembolism (VTE) remains to be determined. Objectives The aim was to determine the molecular epidemiology and the importance of F3 variants for incident VTE by analysis of the population-based MDC study (Malmö Diet and Cancer), consisting of unselected middle-aged and older individuals. Methods The exons of F3 were analyzed in a total of 28,794 individuals from the MDC cohort, and of these, 2584 (9 %) were affected by VTE during follow‐up (1991–2018). Qualifying variants used in gene-collapsing analysis were defined as loss-of-function or non-benign (PolyPhen-2) missense variants with minor allele frequency less than 0.1 %. Results Exon sequencing of the F3 gene identified 61 different variants, 3′ UTR variants (n = 5), 5′ UTR variants (n = 9) synonymous (n = 10), in frame insertion (n = 1), splice region variants (n = 2), missense (n = 33) or loss-of-function variants (n = 1). No associations between common F3 gene variants and incident VTE were found. Seventeen rare variants were classified as qualifying and included in collapsing analysis (16 non-benign missense and 1 loss-of-function variants). The prevalence of F3 qualifying variants was 0.14 %. Seven individuals with F3 qualifying variants had VTE, while 34 individuals had no VTE. The adjusted VTE model was significant (hazard ratio = 2.1 [95 % confidence interval, 1.02–4.48], P-value = 0.045). Conclusions Qualifying F3 gene variants are very rare, indicating a constrained gene. Rare but not common variation in the F3 gene may be involved in VTE.

The DNA of bacterial cells is organized in a highly dynamic chromosome structure. To guarantee its propagation, the chromosome must replicate, segregate, and accommodate other biological processes like gene expression. Therefore, to understand the causal relationship between chromosome organization and biological function, it is essential to follow chromosome dynamics. Live-cell imaging of fluorescent labels allows the tracking of specific genomic locations, but the current imaging-based approaches to study bacterial chromosome organization over the cell cycle are limited in their throughput. Even with multicolor fluorescent locus labeling, the genomic resolution is insufficient to gain insights about the whole chromosome structure from a single experiment. Although sequencing-based methods like chromosome conformation capture provide high genomic coverage, they can only be done in bulk, providing an averaged static view of the chromosome structure. In this study, we address these limitations and investigate the bacterial chromosome organization by imaging fluorescently labeled loci in a library of Escherichia coli strains, following the 3D locations of 68 different loci in live cells in a single experiment. The resulting location distributions along the cell's longitudinal and radial axes are used to inform a dynamic polymer model of the chromosome over the cell cycle. We show a global reorganization of the E. coli chromosome, at both the longitudinal and radial axes. Our model reproduces the known chromosomal architecture of four macrodomains and demonstrates how these domains form dynamically over the cell cycle. ### Competing Interest Statement The authors have declared no competing interest.

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 -DV T. 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 -DV T (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 (beta = -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.

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.

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.