Scarless Gene Tagging with One-Step Transformation and Two-Step Selection in Saccharomyces cerevisiae and Schizosaccharomyces pombe

Gene tagging with fluorescent proteins is commonly applied to investigate the localization and dynamics of proteins in their cellular environment. Ideally, a fluorescent tag is genetically inserted at the endogenous locus at the N- or C- terminus of the gene of interest without disrupting regulatory sequences including the 5’ and 3’ untranslated region (UTR) and without introducing any extraneous unwanted “scar” sequences, which may create unpredictable transcriptional or translational effects. We present a reliable, low-cost, and highly efficient method for the construction of such scarless C-terminal and N-terminal fusions with fluorescent proteins in yeast. The method relies on sequential positive and negative selection and uses an integration cassette with long flanking regions, which is assembled by two-step PCR, to increase the homologous recombination frequency. The method also enables scarless tagging of essential genes with no need for a complementing plasmid. To further ease high-throughput strain construction, we have computationally automated design of the primers, applied the primer design code to all open reading frames (ORFs) of the budding yeast Saccharomyces cerevisiae (S. cerevisiae) and the fission yeast Schizosaccharomyces pombe (S. pombe), and provide here the computed sequences. To illustrate the scarless N- and C-terminal gene tagging methods in S. cerevisiae, we tagged various genes including the E3 ubiquitin ligase RSP5, the proteasome subunit PRE1, and the eleven Rab GTPases with yeast codon-optimized mNeonGreen or mCherry; several of these represent essential genes. We also implemented the scarless C-terminal gene tagging method in the distantly related organism S. pombe using kanMX6 and HSV1tk as positive and negative selection markers, respectively, as well as ura4. The scarless gene tagging methods presented here are widely applicable to visualize and investigate the functional roles of proteins in living cells.United States. National Institutes of Health (NS087557)American Parkinson Disease Association, Inc

Segregation of molecules at cell division reveals native protein localization

We introduce a non-intrusive method exploiting post-division single-cell variability to validate protein localization. The results show that Clp proteases, widely reported to form biologically relevant foci, are in fact uniformly distributed inside Escherichia coli cells, and that many commonly used fluorescent proteins (FPs) cause severe mislocalization when fused to homo-oligomers. Re-tagging five other reportedly foci-forming proteins with the most monomeric FP tested suggests the foci were caused by the FPs

Quantifying Localizations and Dynamics in Single Bacterial Cells

Levels of macromolecules fluctuate both spatially and temporally in individual cells. Such heterogeneity could be exploited for bet hedging in uncertain environments, or be suppressed by negative feedback if perturbations are deleterious. For the master stress-response regulator in Escherichia coli, RpoS, both of these scenarios have been suggested. RpoS levels are also exceedingly low and controlled by the ClpXP protease, which reportedly displays extreme spatial heterogeneity. However, little is known quantitatively about RpoS dynamics. This is partly because no functional protein fusions exist, but also because the quantitative tools for studying fluctuations and localizations are limited, particularly ones that can be independently validated. Here I develop such methods and begin applying them to RpoS. Protein localization measurements increasingly rely on fluorescent protein fusions and are difficult to verify independently. I designed a non-intrusive method for validating localization patterns in live bacterial cells by exploiting post-division heterogeneity in downstream processes. Applying this assay to the ClpXP protease, widely reported to form biologically relevant foci, revealed in fact that the protease molecules are not specifically localized inside cells, as confirmed by four independent methods. I further evaluated 20+ commonly used fluorescent reporters and found that many cause severe mislocalization when fused to homo-oligomers, likely due to avidity effects. Further reinvestigating other foci-forming proteins strongly suggests that the previously reported foci were all caused by the fluorescent proteins used. For mRNAs – which are often present in low numbers per cell and major sources of non-genetic heterogeneity – existing single-cell assays have unknown accuracy: the experimental counting errors could completely over-shadow the natural variation. I therefore optimized and cross-evaluated two single-molecule mRNA detection methods. Several problems were identified and solutions discussed. I succeeded in building a functional RpoS protein fusion, and used bulk methods to show that the RpoS feedback loop is effectively not operating during exponential- phase growth. Mathematical analyses and initial experiments in a microfluidic device further suggest that the RpoS system has several unusual properties contributing towards extremely fast stress response. A stochastic analysis further suggests that the RpoS feedback loop cannot suppress spontaneous fluctuations, and preliminary experiments indicate that large deviations might indeed play important roles

Social networks predict the life and death of honey bees

In complex societies, individuals' roles are reflected by interactions with other conspecifics. Honey bees (Apis mellifera) generally change tasks as they age, but developmental trajectories of individuals can vary drastically due to physiological and environmental factors. We introduce a succinct descriptor of an individual's social network that can be obtained without interfering with the colony. This 'network age' accurately predicts task allocation, survival, activity patterns, and future behavior. We analyze developmental trajectories of multiple cohorts of individuals in a natural setting and identify distinct developmental pathways and critical life changes. Our findings suggest a high stability in task allocation on an individual level. We show that our method is versatile and can extract different properties from social networks, opening up a broad range of future studies. Our approach highlights the relationship of social interactions and individual traits, and provides a scalable technique for understanding how complex social systems function. Honey bee workers take on different tasks for the colony as they age. Here, the authors develop a method to extract a descriptor of the individuals' social networks and show that interaction patterns predict task allocation and distinguish different developmental trajectories

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Effectiveness of an intensive care telehealth programme to improve process quality (ERIC): a multicentre stepped wedge cluster randomised controlled trial

Purpose!#!Supporting the provision of intensive care medicine through telehealth potentially improves process quality. This may improve patient recovery and long-term outcomes. We investigated the effectiveness of a multifaceted telemedical programme on the adherence to German quality indicators (QIs) in a regional network of intensive care units (ICUs) in Germany.!##!Methods!#!We conducted an investigator-initiated, large-scale, open-label, stepped-wedge cluster randomised controlled trial enrolling adult ICU patients with an expected ICU stay of ≥ 24 h. Twelve ICU clusters in Berlin and Brandenburg were randomly assigned to three sequence groups to transition from control (standard care) to the intervention condition (telemedicine). The quality improvement intervention consisted of daily telemedical rounds guided by eight German acute ICU care QIs and expert consultations. Co-primary effectiveness outcomes were patient-specific daily adherence (fulfilled yes/no) to QIs, assessed by a central end point adjudication committee. Analyses used mixed-effects logistic modelling adjusted for time. This study is completed and registered with ClinicalTrials.gov (NCT03671447).!##!Results!#!Between September 4, 2018, and March 31, 2020, 1463 patients (414 treated on control, 1049 on intervention condition) were enrolled at ten clusters, resulting in 14,783 evaluated days. Two randomised clusters recruited no patients (one withdrew informed consent; one dropped out). The intervention, as implemented, significantly increased QI performance for 'sedation, analgesia and delirium' (adjusted odds ratio (99.375% confidence interval [CI]) 5.328, 3.395-8.358), 'ventilation' (OR 2.248, 1.198-4.217), 'weaning from ventilation' (OR 9.049, 2.707-30.247), 'infection management' (OR 4.397, 1.482-13.037), 'enteral nutrition' (OR 1.579, 1.032-2.416), 'patient and family communication' (OR 6.787, 3.976-11.589), and 'early mobilisation' (OR 3.161, 2.160-4.624). No evidence for a difference in adherence to 'daily multi-professional and interdisciplinary clinical visits' between both conditions was found (OR 1.606, 0.780-3.309). Temporal trends related and unrelated to the intervention were detected. 149 patients died during their index ICU stay (45 treated on control, 104 on intervention condition).!##!Conclusion!#!A telemedical quality improvement program increased adherence to seven evidence-based German performance indicators in acute ICU care. These results need further confirmation in a broader setting of regional, non-academic community hospitals and other healthcare systems

Pre-Micro RNA Signatures Delineate Stages of Endothelial Cell Transformation in Kaposi Sarcoma

MicroRNAs (miRNA) have emerged as key regulators of cell lineage differentiation and cancer. We used precursor miRNA profiling by a novel real-time QPCR method (i) to define progressive stages of endothelial cell transformation cumulating in Kaposi sarcoma (KS) and (ii) to identify specific miRNAs that serve as biomarkers for tumor progression. We were able to compare primary patient biopsies to well-established culture and mouse tumor models. Loss of mir-221 and gain of mir-15 expression demarked the transition from merely immortalized to fully tumorigenic endothelial cells. Mir-140 and Kaposi sarcoma–associated herpesvirus viral miRNAs increased linearly with the degree of transformation. Mir-24 emerged as a biomarker specific for KS