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BackgroundWe previously reported inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity in 1-5% of unvaccinated patients with life-threatening COVID-19, and auto-antibodies against type I IFN in another 15-20% of cases.MethodsWe report here a genome-wide rare variant burden association analysis in 3,269 unvaccinated patients with life-threatening COVID-19 (1,301 previously reported and 1,968 new patients), and 1,373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. A quarter of the patients tested had antibodies against type I IFN (234 of 928) and were excluded from the analysis.ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants wasTLR7, with an OR of 27.68 (95%CI:1.5-528.7,P=1.1×10−4), in analyses restricted to biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70 [95%CI:1.3-8.2],P=2.1×10−4). Adding the recently reportedTYK2COVID-19 locus strengthened this enrichment, particularly under a recessive model (OR=19.65 [95%CI:2.1-2635.4];P=3.4×10−3). When these 14 loci andTLR7were considered, all individuals hemizygous (n=20) or homozygous (n=5) for pLOF or bLOF variants were patients (OR=39.19 [95%CI:5.2-5037.0],P=4.7×10−7), who also showed an enrichment in heterozygous variants (OR=2.36 [95%CI:1.0-5.9],P=0.02). Finally, the patients with pLOF or bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years;P=1.68×10−5).ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

MotivationWhole-genome sequencing has revolutionized biosciences by providing tools for constructing complete DNA sequences of individuals. With entire genomes at hand, scientists can pinpoint DNA fragments responsible for different cancers and predict patient responses to cancer treatments. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for machine learning algorithms.ResultsWe present three feature extraction methods that facilitate classifier learning from distributions of genomic variants. The proposed approaches use binning, clustering, and kernel density estimation to produce features that discriminate between two groups of patients. Experiments on genomes of 219 ovarian, 61 lung, and 929 breast cancer patients show that the proposed approaches automatically identify genomic biomarkers associated with cancer subtypes and clinical response to oncological treatment. Finally, we show that the extracted features can be used alongside unsupervised learning methods to analyze genomic samples.AvailabilityThe source code of the presented algorithms and reproducible experimental scripts are available on Github at https://github.com/MNMdiagnostics/dbfeContactmaciej.piernik@cs.put.poznan.pl

This paper aims to explore popular CNN architectures for the generation of patient-specific dose distributions for Volumetric Modulated Arc Therapy (VMAT) radiotherapy satisfying clinical dose-volume constraints. Only organs at risk (OARs) and planning target volume (PTV) segmentations are required as input. The outcome of the research is selecting the optimal network architecture and assessing training parameters. The U-net, $\mathbf{ResNet}+\mathbf{U-net},\mathbf{ResNet}+\mathbf{PSPNet}$ networks are analyzed. The $\mathbf{Resnet}+\mathbf{U-net}$ model was chosen as the most suited to the task. The similarity measures such as mIoU and mDice coefficient as well as the dose-volume constraints in PTV and selected OARs are evaluated. The results confirm that the $\mathbf{Reset}+\boldsymbol{U}$ -net network is capable of generating patient-specific dose distribution and can be used as a valuable assistance during clinical radiotherapy planning procedures.

Although Slavic populations account for over 3.5% of world inhabitants, no centralized, open source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for either biomedical research and genetic counseling and are essential for archeological and historical studies. Polish population, homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a good genetic reference for middle European Slavic nations.The aim of the present study was to describe first results of analyses of a newly created national database of Polish genomic variant allele frequencies. Never before has any study on the whole genomes of Polish population been conducted on such a large number of individuals (1,079).A wide spectrum of genomic variation was identified and genotyped, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups and Mendelian inconsistencies. The allele frequencies were calculated for 943 unrelated individuals and released publicly as The Thousand Polish Genomes database. A precise detection and characterisation of rare variants enriched in the Polish population allowed to confirm the allele frequencies for known pathogenic variants in diseases, such as Smith-Lemli-Opitz syndrome (SLOS) or Nijmegen breakage syndrome (NBS). Additionally, the analysis of OMIM AR genes led to the identification of 22 genes with significantly different cumulative allele frequencies in the Polish (POL) vs European NFE population. We hope that The Thousand Polish Genomes database will contribute to the worldwide genomic data resources for researchers and clinicians.

Whole genome sequencing (WGS) becomes increasingly important for advancing personalized cancer care, driving not only basic science studies but also entering into clinical applications. Translating raw WGS data into the right clinical decision requires high accuracy of somatic variant detection, therefore novel data analysis methods have to be carefully evaluated.In this work we tested the performance of well-established somatic variant detection workflows: GATK, CPG-WGS, DRAGEN and Strelka2. By utilizing both real data, with well-defined mutations, and synthetic mutations spiked-in into real data, we were able to assess sensitivity and precision of each workflow, for various coverage and tumor purity levels.Individual tools excelled in different evaluation approaches, however the results demonstrated that DRAGEN has the highest overall performance when sensitivity is preferred over precision, and the opposite is true for CGP-WGS. The differences in results obtained using synthetic and real datasets, indicate that benchmarks based only on a single reference set may provide an incomplete picture.

Detection of microorganisms is of particular importance to human health and life, and for the industry in general. For this reason, we want this process to be as fast and precise as possible. We also expect that the automation of this activity (detection of microorganisms) can be widely used in various industries. This article is another attempt to the classification of microorganisms (a small group of selected species listed in ISO 17516:2014-11) that uses a deep learning approach with popular deep neural network (DNN) models. Before classification, the microorganisms were stained by two methods: Congo Red and the modified Gram stain. The classification results for the two staining methods are similar, but greater accuracy was obtained for Congo Red stain. The final results show that the popular DNN models (Xception, ResNet-50) perform well with this challenge and also show that it is not always beneficial to use the pre-trained weights of DNN models.

SARS-CoV-2 infection displays immense inter-individual clinical variability, ranging from silent infection to lethal disease. The role of human genetics in determining clinical response to the virus remains unclear. Studies of outliers—individuals remaining uninfected despite viral exposure and healthy young patients with life-threatening disease—present a unique opportunity to reveal human genetic determinants of infection and disease.

The modern professional medical devices for gait analysis are very advanced but are not portable and available everywhere. However, the current information about our gait (“permanent” monitoring) might be helpful to improve our health condition. This paper describes the idea of gait anomalies detection by algorithms of deep learning. These algorithms analyze data collected by a prototype measuring device managed by a mobile application. Sensors collect foot pressure values as data for deep learning. The problem of collecting real data (from real patients) is discussed. The potential use of the device described is also discussed. Finally, assumptions and expectations regarding the results were compared with several related projects of deep learning and gait analysis. Our analysis of related studies shows that the use of deep neural networks (convolutional and recurrent) can have a satisfactory probability of detecting gait anomalies.

The Escherichia coli SMC complex, MukBEF, acts in chromosome segregation. MukBEF shares the distinctive architecture of other SMC complexes, with one prominent difference; unlike other kleisins, MukF forms dimers through its N-terminal domain. We show that a 4-helix bundle adjacent to the MukF dimerisation domain interacts functionally with the MukB coiled-coiled ‘neck’ adjacent to the ATPase head. We propose that this interaction leads to an asymmetric tripartite complex, as in other SMC complexes. Since MukF dimerisation is preserved during this interaction, MukF directs the formation of dimer of dimer MukBEF complexes, observed previously in vivo. The MukF N- and C-terminal domains stimulate MukB ATPase independently and additively. We demonstrate that impairment of the MukF interaction with MukB in vivo leads to ATP hydrolysis-dependent release of MukBEF complexes from chromosomes., eLife digest Most DNA in a cell is arranged in structures called chromosomes. From bacteria to humans, chromosomes have to be compacted and highly organized to allow the cells to maintain and use their genetic information. In all organisms, large ring-shaped protein complexes play a crucial role in managing chromosomes. They transport and organize DNA thanks to reactions whose precise mechanism remains unknown. In bacteria, MukB and a type of kleisin called MukF are two examples of molecules involved in chromosome management. Two MukBs join at one end to form a hinge; at the other end, each MukB protein has a neck and a head. The two heads are linked by the kleisin to form a large protein ring, which can open to capture DNA. The MukB heads can trigger a biochemical reaction that creates the energy essential to trap and release DNA during DNA transport. Here, Zawadzka et al. study how the different components of the MukB-kleisin complex interact with each other to undergo the biochemical reactions that lead to DNA transport. The experiments show that the kleisin joins two MukB heads by attaching the base of one to the neck of the other, asymmetrically closing the ring. The separate interactions of different regions of the kleisin to the head and neck of MukB independently activate the two MukB heads, thereby controlling essential steps in the reactions with DNA. Two MukB-kleisin ring complexes are joined to each other because of a tight interaction between the two kleisin molecules. This leads Zawadzka et al. to suggest that DNA is sequentially grabbed and released from these two rings during DNA transport, similar to how a climbing rope is attached and released through carabiners. Cells cannot survive or be healthy without their chromosomes being accurately managed. It is still unclear how molecules such as MukBs and kleinsins drive this process. A better picture of their structure and interactions is an essential first step to understand these mechanisms.

2019 Klein et al., Understanding the plasticity of genomes has been greatly aided by assays for recombination, repair and mutagenesis. These assays have been developed in microbial systems that provide the advantages of genetic and molecular reporters that can readily be manipulated. Cellular assays comprise genetic, molecular, and cytological reporters. The assays are powerful tools but each comes with its particular advantages and limitations. Here the most commonly used assays are reviewed, discussed, and presented as the guidelines for future studies., HLK was supported by NIH grant R01-CA146940. AA was supported by the European research Council (ERC2014- ADG669898 TARLOOP), the Spanish Ministry of Economy and Competitiveness (BFU2016-75058-P), and the Junta de Andalucía (BIO1238). JLA was supported by NIH grant R35G-GM119788. CHF was supported by NIH grants P01- GM105473 and R01-GM122880. SMG was supported by the Swiss national Science Foundation and the Novartis Research Foundation. DAG was supported by National Institutes of Health (Intramural Research Program Project Z1AES103266. JEH was supported by NIH grants R35- GM127029 and P01-GM105473. GI was supported by NIH grants R01-GM125650 and R01-GM080600. SJ-R was supported by NIH grant R35-GM118077. MCK was supported by National Science Foundation Graduate Research Fellowship DGE-1122492, NIH training grant T32-GM007223 and NIH grant DP20D008429. RDK and CDP were supported by NIH grants R01-GM26017 and R01-GM50006. AK was supported by NIH grant R01-GM073115. SAEL was supported by grants from Agence Nationale de la Recherche ANR-14- CE10-0010-01 and the Foundation pour la Recherche Médicale Equipe FRM DEQ20160334889. SEL was supported by NIH grant R01-GM071011. SMM was supported by NIH grants R01-GM60987 and P01-GM105473. TDP was supported by NIH grant R35-GM118020. SMR was supported by a gift from WM Keck Foundation, NIH Director’s Pioneer Award DP1-CA174424 and NIH grant R35-GM122598. DMF was supported by the Cancer Prevention and Research Institute of Texas, Baylor College of Medicine Comprehensive Cancer Training Program Postdoctoral Fellowship RP160283. RR was supported by NIH grant R35-GM118180 and JM-H was supported by a Marie Curie International Outgoing Fellowship and the ANR-12-PDOC-0035-01. LSS was supported by NIH grant R35-GM126997. PZ was supported by National Science Centre Poland 2015/19/103859 and FNP First TEAM/2016-1/9. NK was supported by NIH grant R01-GM116007 and the Welch Foundation (AU1875). ML was supported by grants from the Danish Agency for Science, Technology and Innovation, the Villum Foundation and the Danish National Research Foundation (DNRF115). AM was supported by NIH grants R35-GM127006 and R03- ES029306.

Development of alternative thin film photovoltaic technologies is an important research topic because of the potential of low-cost, high-efficiency solar cells to produce terawatt levels of clean power. However, this development of unexplored yet promising absorbers can be hindered by complications that arise during solar cell fabrication. Here, a high-throughput combinatorial method is applied to accelerate development of photovoltaic devices, in this case, using the novel CuSbS2 absorber via a newly developed three-stage self-regulated growth process to control absorber purity and orientation. Photovoltaic performance of the absorber, using the typical substrate CuInxGa1 − xSe2 (CIGS) device architecture, is explored as a function of absorber quality and thickness using a variety of back contacts. This study yields CuSbS2 device prototypes with ~1% conversion efficiency, suggesting that the optimal CuSbS2 device fabrication parameters and contact selection criteria are quite different than for CIGS, despite the similarity of these two absorbers. The CuSbS2 device efficiency is at present limited by low short-circuit current because of bulk recombination related to defects, and a small open-circuit voltage because of a theoretically predicted cliff-type conduction band offset between CuSbS2 and CdS. Overall, these results illustrate both the potential and limits of combinatorial methods to accelerate the development of thin film photovoltaic devices using novel absorbers. Copyright © 2016 John Wiley & Sons, Ltd.

Bacterial DNA gyrase introduces negative supercoils into chromosomal DNA and relaxes positive supercoils introduced by replication and transiently by transcription. Removal of these positive supercoils is essential for replication fork progression and for the overall unlinking of the two duplex DNA strands, as well as for ongoing transcription. To address how gyrase copes with these topological challenges, we used high-speed single-molecule fluorescence imaging in liveEscherichia colicells. We demonstrate that at least 300 gyrase molecules are stably bound to the chromosome at any time, with ∼12 enzymes enriched near each replication fork. Trapping of reaction intermediates with ciprofloxacin revealed complexes undergoing catalysis. Dwell times of ∼2 s were observed for the dispersed gyrase molecules, which we propose maintain steady-state levels of negative supercoiling of the chromosome. In contrast, the dwell time of replisome-proximal molecules was ∼8 s, consistent with these catalyzing processive positive supercoil relaxation in front of the progressing replisome.

Smoking is a major risk factor for peripheral artery disease (PAD), which correlates with progression of the disease, the prevalence of chronic wounds, amputation incidence and mortality. On the other hand, abstinence from smoking has a beneficial effect on the bypass grafts patency after surgical revascularization. Poland fits in the steady decline in the percentage of smokers, but there is a lack of current data, whether those changes are observed also in patients with PAD and whether they lead to the improvement of health condition.This study evaluated the impact of smoking and other known risk factors for cardiovascular disease on the occurrence of PAD, the risk of adverse outcomes (death, amputation, tissue necrosis), development of chronic wounds and their healing after arterial revascularization.The study was conducted in groups of 208 patients with PAD scheduled for surgical treatment (28.4% of patients with adverse outcomes of PAD, 38.5% of patients with ischemic wounds) and 190 control subjects. The study groups were interviewed concerning smoking, characterized by known risk factors for cardiovascular disease, and in the incidence of amputation, and deaths within 30 days after surgery. In the group of 48 patients with ischemic wounds a prospective assessment of the progress of wound healing in terms of changes in the wound advancement and changes in pain severity associated with wounds was performed.Over 90% of patients with PAD were smokers: 53.8% former and 36.5% past in relation to 27.4% and 14.7%, respectively, in the control group (p0.0001). Among patients, a higher proportion of former smokers was found in those with poorer health condition: with adverse outcomes of PAD (48.0% vs 64.1%, p0.05), and with ischemic wounds (70.7% vs 65.1%, p = 0.056). Advanced age, female sex, and the presence of diabetes were associated with both, the presence of PAD adverse outcomes, as well as the development of ischemic wounds. In the prospective study, major factors prolonging the process of wound healing were advanced age, diabetes and smoking (evaluated as peaks years of smoking).Smoking is still the most common risk factor for PAD, and smoking cessation is the result of the deterioration of health condition. Simultaneously this factor, in addition to diabetes, advanced age and female sex, affects both the risk of unfavorable course of PAD and decrease the progress of wound healing. Control of risk factors for cardiovascular disease should be especially careful in women in whom, despite the lower PAD incidence, further prognosis of disease progression seem worse.

Single-particle tracking (SPT) combined with Photoactivated Localization Microscopy (sptPALM) provides an opportunity to perform complex molecular biology experiments inside living cells. By tracking the motion of DNA repair proteins in vivo, information can be extracted not only about their diffusion, but also about the kinetics and spatial distribution of DNA binding1–3. From a methodological point of view, a Total Internal Reflection Microscope equipped with a sensitive detector (usually an EM-CCD camera4) is commonly used, allowing detection of individual fluorophores. The signal from individual emitters can be analysed and the position of a given fluorophore established with high accuracy (up to a single nm) by Gaussian fitting. To determine the mobility of each fluorophore, the positions of individual molecules are linked into trajectories over multiple frames using a tracking algorithm5.

The Escherichia coli SMC complex, MukBEF, acts in chromosome segregation. MukBEF shares the distinctive architecture of other SMC complexes, with one prominent difference; unlike other kleisins, MukF forms dimers through its N-terminal domain. We show that a 4-helix bundle adjacent to the MukF dimerization domain interacts functionally with the MukB coiled-coiled ‘neck’ adjacent to the ATPase head, forming an asymmetric tripartite complex, as in other SMC complexes. Since MukF dimerization is preserved during this interaction, MukF directs the formation of dimer of dimers MukBEF complexes, observed previously in vivo. The MukF N- and C-terminal domains stimulate ATPase independently and additively, consistent with them each targeting only one of the two MukB ATPase active sites in the asymmetric complex. We demonstrate that MukF interaction with the MukB neck turns over during cycles of ATP binding and hydrolysis in vivo and that impairment of this interaction leads to MukBEF release from chromosomes.

In multinary compound semiconductors, cation disorder can decisively alter the electronic properties and impact potential applications. $\mathrm{ZnSn}{\mathrm{N}}_{2}$ is a ternary nitride of interest for photovoltaics, which forms in a wurtzite-derived crystal structure. In the ground state, every N anion is coordinated by two Zn and two Sn cations, thereby observing the octet rule locally. Using a motif-based model Hamiltonian, we performed Monte Carlo simulations that provide atomistic representations of $\mathrm{ZnSn}{\mathrm{N}}_{2}$ with varying degrees of cation disorder. Subsequent electronic structure calculations describe the evolution of band gaps, optical properties, and carrier localization effects as a function of the disorder. We find that octet-rule conserving disorder is practically impossible to avoid but perfectly benign, with hardly any effects on the electronic structure. In contrast, a fully random cation distribution would be very detrimental, but fortunately it is energetically highly unfavorable. A degree of disorder that can realistically be expected for nonequilibrium thin-film deposition leads to a moderate band-gap reduction and to moderate carrier localization effects. Comparing the simulated structures with experimental samples grown by sputtering, we find evidence that these samples indeed incorporate a certain degree of octet-rule violating disorder, which is reflected in the x-ray diffraction and in the optical absorption spectra. This study demonstrates that the electronic properties of $\mathrm{ZnSn}{\mathrm{N}}_{2}$ are dominated by changes of the local coordination environments rather than long-range ordering effects.

As the world’s demand for energy grows, the search for cost competitive and earth abundant thin film photovoltaic absorbers is becoming increasingly important. A promising approach to tackle this challenge is through thin film photovoltaics made of elements that are abundant in the Earth’s crust. In this work, we focus on Cu2SnS3, a promising earth abundant absorber material. Recent publications have presented 3% and 6% device efficiencies using Cu2SnS3-based absorber materials and alloys, respectively. However, little is understood about the fundamental defect and doping physics of this material, which is needed for further improvements in device performance. Here, we identify the origins of the changes in doping in sputtered cubic Cu2SnS3 thin films using combinatorial experiments and first-principles theory. Experimentally, we find that the cubic Cu2SnS3 has a large phase width and that the electrical conductivity increases with increasing Cu and S content in the films, which cannot be fully explained ...

Background Among cancer therapies relying on the defects in DNA repair mechanisms, the platinum agents (e.g. cisplatin or carboplatin) are most widely used. Despite being effective in majority of patients, the tumor often relapses, and these originally sensitive cancers acquire resistance towards platinum-based drugs. The mechanism of resistance development is not well understood and there is no clinical approach to prevent or diagnose it. Therefore, there is an urgent need for better understanding of DNA repair pathway interactions affecting cell response and resistance to these drugs. Methods The main aim of this study was to identify DNA repair pathways involved in drug sensitivity and resistance by RNAi knockdown and CRISPR/Cas9 knockout screenings. We tested a library of genes involved in different DNA repair pathways in the hTERT RPE-1 cell line. Silencing by RNAi and CRISPR-based knockout of the target genes were followed with drug treatments to identify repair pathway crosstalks. Results We found that silencing of ERCC1 and FANCD2 genes drastically increase cell sensitivity to cisplatin as well as towards PARP inhibitor Olaparib. By performing CRISPR screen, we have found that MSH2 (Mismatch Repair (MMR) gene) inactivation in ERCC1KO/KO cells alleviate cisplatin sensitivity of these cells but not the sensitivity towards Olaparib. These results suggest that in clinical settings, inactivation of MMR might provide a mechanism of the resistance development towards cisplatin but not towards PARP inhibitors. Therefore, knowledge about the activity of DNA repair pathways could be used to select appropriate treatments for patients. Conclusions We suggest that the comprehensive analysis of DNA repair pathway efficiencies, preferably achieved by cancer whole-genome sequencing could provide a diagnostic tool for treatment selection and could be applied in day-to-day cancer diagnostics. Legal entity responsible for the study Adam Mickiewicz University, Poznan, Poland. Funding Foundation for Polish Science. Disclosure All authors have declared no conflicts of interest.

Charge transport to surface reactive sites is a crucial step in any photocatalytic process. In the most popular photocatalyst—the anatase TiO2–this step is complicated by the fact that photogenerated carriers can trap. Studies of charge trapping and transfer in anatase often employ transient absorption spectroscopy (TAS), but the understanding of the optical absorption due to trapped carriers in TiO2 is incomplete. On the basis of the generalized Δ self-consistent field density functional theory (Δ-SCF DFT) calculations, we attribute the experimentally observed absorption band at 430–550 nm to the interpolaron transitions of the stable surface and subsurface O– centers and associate the blue shift of the spectra after the photoexcitation with holes migration to surfaces. We also suggest that subsurface hole trapping may contribute to generally lower photocatalytic performance of the anatase (101) surface compared to the (001) surface.

Significance Insight into the mechanisms that underlie the process of faithful chromosome segregation is of importance for understanding the place of humans in the living world. Bacteria are the most abundant free-living organisms and have important roles in human health and disease. Nevertheless, molecular understanding of bacterial chromosome segregation is in its infancy. In this paper, the action of one conserved molecular machine that acts to coordinate the late steps of chromosome segregation with cell division is analyzed molecule by molecule in real time, using three complementary single-molecule techniques simultaneously. By using normal and mutated proteins, the complete reaction pathway is revealed from assembly of the initial nucleoprotein complex, to its activation by a DNA motor, and to the subsequent steps that lead to chromosome unlinking.

Band-edge effects — including grading, electrostatic fluctuations, bandgap fluctuations, and band tails — affect chalcogenide device efficiency. These effects now require more careful consideration as efficiencies increase beyond 20%. Several aspects of the relationships between band-edge phenomena and device performance for NREL absorbers are examined. For Cu(In, Ga)Se2 devices, recent increases in diffusion length imply changes to the optimum bandgap profile. The origin, impact, and modification of electrostatic and bandgap fluctuations are also discussed. The application of the same principles to devices based on CdTe, kesterites, and emerging absorbers (Cu 2 SnS 3 , CuSbS 2 ), considering differences in materials properties, is examined.

We study electronic hole localization in rutile and anatase titanium dioxide by means of Δ-Self-Consistent Field Density Functional Theory. In order to compare stabilities of the localized and the delocalized hole states we introduce a simple correction to the wrong description of the localization processes within DFT. The correction removes the non-linearity of energy for fractional excitations. We show that the self-trapped and the delocalized hole states have comparable stability in rutile TiO 2 whereas in anatase the former is favoured. The theoretical prediction of the adiabatic Potential Energy Surfaces for the hole localization compares well with published photoluminescence measurements.

Typically point defects are modeled by adding, removing, or exchanging at most few atoms around a given lattice site. We demonstrate the possibility of formation of extended antisite defects that involve complex, nonlocal atomic rearrangements, which cannot be captured within a simple point defect model. We illustrate the formation of extended antisite defects in ${\mathrm{Cu}}_{2}{\mathrm{SnS}}_{3}$ and ${\mathrm{Cu}}_{2}{\mathrm{SnZnS}}_{4}$ solar absorbers where they lower the formation energy by up to about 1 eV per defect. These extended antisite configurations can dramatically change the stoichiometries and doping properties of multinary semiconductors that have a propensity towards disorder.

Cu${}_{2}$SnS${}_{3}$ is a promising, earth-abundant photovoltaic material, but disorder in the positions of Cu and Sn cations in its crystal lattice complicate its electronic transport. The authors find that even after substantially increasing its cation ordering via annealing, minority-carrier transport is still dominated by disorder effects, as revealed by spectroscopy plus Monte Carlo simulations. These results identify important challenges to the implementation of Cu${}_{2}$SnS${}_{3}$ in solar cells, and carry implications for other semiconductors of this type, such as Cu${}_{2}$ZnSn(S,Se)${}_{4}$ (CZTS).

Significance This study develops and exploits an expanded single-molecule fluorescence technique to understand the molecular mechanism of assembly, translocation, and disassembly of a hexameric DNA motor, FtsK, which functions ubiquitously in bacterial chromosome segregation. Assembly of single hexamers on DNA and their subsequent rapid translocation were directly assayed. FtsK hexamers dissociated soon after encountering and activating XerCD- dif recombination complexes. This work contrasts with previously published reports, which suggested that FtsK can reverse spontaneously during translocation, or upon encountering XerCD- dif . Furthermore, in some previous assays, the readout was DNA looping; here, we show that looping does not occur with single hexamer translocation. The technique used provides a blueprint for mechanistic real-time studies of individual protein–nucleic acid complexes.

Despite the fundamental importance of transcription, a comprehensive analysis of RNA polymerase (RNAP) behavior and its role in the nucleoid organization in vivo is lacking. Here, we used superresolution microscopy to study the localization and dynamics of the transcription machinery and DNA in live bacterial cells, at both the single-molecule and the population level. We used photoactivated single-molecule tracking to discriminate between mobile RNAPs and RNAPs specifically bound to DNA, either on promoters or transcribed genes. Mobile RNAPs can explore the whole nucleoid while searching for promoters, and spend 85% of their search time in nonspecific interactions with DNA. On the other hand, the distribution of specifically bound RNAPs shows that low levels of transcription can occur throughout the nucleoid. Further, clustering analysis and 3D structured illumination microscopy (SIM) show that dense clusters of transcribing RNAPs form almost exclusively at the nucleoid periphery. Treatment with rifampicin shows that active transcription is necessary for maintaining this spatial organization. In faster growth conditions, the fraction of transcribing RNAPs increases, as well as their clustering. Under these conditions, we observed dramatic phase separation between the densest clusters of RNAPs and the densest regions of the nucleoid. These findings show that transcription can cause spatial reorganization of the nucleoid, with movement of gene loci out of the bulk of DNA as levels of transcription increase. This work provides a global view of the organization of RNA polymerase and transcription in living cells.

Clustering of certain structural motifs leads to fluctuations of the electrostatic potential in an entire class of materials that are of interest as solar absorbers, and controlling such fluctuations is important for photovoltaic applications. The authors show that this clustering is driven by entropy and leads to narrowing of the band gap, and may occur even under low-temperature growth conditions. They also note that this cluster formation could actually be advantageous for thermoelectric applications.

Protein-DNA interactions are critical to many important biological functions, from transcription and chromosome organization, to DNA replication and repair. To fully understand these processes we need to look at molecular details, such as the stoichiometries and binding kinetics of these proteins. However, focusing on the molecular level can miss the bigger picture; we also need to understand how protein-DNA interactions shape the global organisation of chromosomes and cause phenotypical changes over the whole cell.Using photoactivated single-molecule tracking in live bacteria allows proteins specifically bound to DNA to be distinguished from mobile proteins, offering a new perspective on protein-DNA interactions, from the molecular level to the length scale of whole bacterial cells. We demonstrate how we have applied this technique to answer key questions in transcription, chromosome organisation, and DNA repair in Escherichia coli.Discriminating transcribing RNA polymerase molecules from the rest of the population showed that low levels of transcription can occur throughout the nucleoid, but clustering analysis and 3D Structured Illumination Microscopy (SIM) showed that dense clusters of transcribing RNAPs form at the nucleoid periphery, indicating a movement of gene loci out of the bulk of DNA as levels of transcription increase [1].We further demonstrate how this technique can be used to study the formation and DNA binding of multienzyme complexes shedding light on the damage recognition mechanism of the UvrAB complex. Finally we highlight an assay to characterise the search process and non-specific DNA interactions of DNA-binding proteins by degrading the entire chromosome.1. Stracy, M. et al. Live-cell superresolution microscopy reveals the organization of RNA polymerase in the bacterial nucleoid. Proc. Natl. Acad. Sci. 112, 201507592 (2015).