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225 results found. For more information, click each entry to expand.
47 tweets microbiology
Simon Roux, Mart Krupovic, Rebecca A Daly, Adair L Borges, Stephen Nayfach, Frederik Schulz, Jan-Fang Cheng, Natalia N Ivanova, Joseph Bondy-Denomy, Kelly C Wrighton, Tanja Woyke, Axel Visel, Nikos Kyrpides, Emiley A Eloe-Fadrosh
Bacteriophages from the Inoviridae family (inoviruses) are characterized by their unique morphology, genome content, and infection cycle. To date, a relatively small number of inovirus isolates have been extensively studied, either for biotechnological applications such as phage display, or because of their impact on the toxicity of known bacterial pathogens including Vibrio cholerae and Neisseria meningitidis. Here we show that the current 56 members of the Inoviridae family represent a minute fraction of a highly diverse group of inoviruses. Using a new machine learning approach leveraging a combination of marker gene and genome features, we identified 10,295 inovirus-like genomes from microbial genomes and metagenomes. Collectively, these represent six distinct proposed inovirus families infecting nearly all bacterial phyla across virtually every ecosystem. Putative inoviruses were also detected in several archaeal genomes, suggesting that these viruses may have occasionally transferred from bacterial to archaeal hosts. Finally, we identified an expansive diversity of inovirus-encoded toxin-antitoxin and gene expression modulation systems, alongside evidence of both synergistic (CRISPR evasion) and antagonistic (superinfection exclusion) interactions with co-infecting viruses which we experimentally validated in a Pseudomonas model. Capturing this previously obscured component of the global virosphere sparks new avenues for microbial manipulation approaches and innovative biotechnological applications.
42 tweets genomics
Abigail Lind, Yvonne Y.Y. Lai, Yulia Mostovoy, Alisha K. Holloway, Alessio Iannucci, Angel CY Mak, Marco Fondi, Valerio Orlandini, Walter L Eckalbar, Massimo Milan, Michail Rovatsos, Ilya G. Kichigin, Alex I Makunin, Vladimir Trifonov, Elio Schijlen, Lukas Kratochvil, Renato Fani, Tim S Jessop, Tomaso Patarnello, James W Hicks, Oliver A. Ryder, Joseph R. Mendelson, Claudio Ciofi, Pui-Yan A. Kwok, Katherine S Pollard, Benoit Bruneau
Monitor lizards are unique among ectothermic reptiles in that they have a high aerobic capacity and distinctive cardiovascular physiology which resembles that of endothermic mammals. We have sequenced the genome of the Komodo dragon (Varanus komodoensis), the largest extant monitor lizard, and present a high resolution de novo chromosome-assigned genome assembly for V. komodoensis, generated with a hybrid approach of long-range sequencing and single molecule physical mapping. Comparing the genome of V. komodoensis with those of related species showed evidence of positive selection in pathways related to muscle energy metabolism, cardiovascular homeostasis, and thrombosis. We also found species-specific expansions of a chemoreceptor gene family related to pheromone and kairomone sensing in V. komodoensis and several other lizard lineages. Together, these evolutionary signatures of adaptation reveal genetic underpinnings of the unique Komodo sensory, cardiovascular, and muscular systems, and suggest that selective pressure altered thrombosis genes to help Komodo dragons evade the anticoagulant effects of their own saliva. As the only sequenced monitor lizard genome, the Komodo dragon genome is an important resource for understanding the biology of this lineage and of reptiles worldwide.
41 tweets neuroscience
Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous studies have focused on the effectiveness of GSR in removing imaging artifacts, as well as its potential biases. Given the growing interest in functional connectivity fingerprinting, here we considered the utilitarian question of whether GSR strengthens or weakens associations between resting-state functional connectivity (RSFC) and multiple behavioral measures across cognition, personality and emotion. By applying the variance component model to the Brain Genomics Superstruct Project (GSP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 47% across 23 behavioral measures after GSR. In the Human Connectome Project (HCP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 40% across 58 behavioral measures, when GSR was applied after ICA-FIX de-noising. To ensure generalizability, we repeated our analyses using kernel regression. GSR improved behavioral prediction accuracies by an average of 64% and 12% in the GSP and HCP datasets respectively. Importantly, the results were consistent across methods. A behavioral measure with greater RSFC-explained variance (using the variance component model) also exhibited greater prediction accuracy (using kernel regression). A behavioral measure with greater improvement in behavioral variance explained after GSR (using the variance component model) also enjoyed greater improvement in prediction accuracy after GSR (using kernel regression). Furthermore, GSR appeared to benefit task performance measures more than self-reported measures. Since GSR was more effective at removing motion-related and respiratory-related artifacts, GSR-related increases in variance explained and prediction accuracies were unlikely the result of motion-related or respiratory-related artifacts. However, it is worth emphasizing that the current study focused on whole-brain RSFC, so it remains unclear whether GSR improves RSFC-behavioral associations for specific connections or networks. Overall, our results suggest that at least in the case for young healthy adults, GSR strengthens the associations between RSFC and most (although not all) behavioral measures. Code for the variance component model and ridge regression can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/preprocessing/Li2019_GSR.
31 tweets bioinformatics
MOTIVATION: Identifying transcription factor binding sites is the first step in pinpointing non-coding mutations that disrupt the regulatory function of transcription factors and promote disease. ChIP-seq is the most common method for identifying binding sites, but performing it on patient samples is hampered by the amount of available biological material and the cost of the experiment. Existing methods for computational prediction of regulatory elements primarily predict binding in genomic regions with sequence similarity to known transcription factor sequence preferences. This has limited efficacy since most binding sites do not resemble known transcription factor sequence motifs, and many transcription factors are not even sequence-specific. RESULTS: We developed Virtual ChIP-seq, which predicts binding of individual transcription factors in new cell types using an artificial neural network that integrates ChIP-seq results from other cell types and chromatin accessibility data in the new cell type. Virtual ChIP-seq also uses learned associations between gene expression and transcription factor binding at specific genomic regions. This approach outperforms methods that predict TF binding solely based on sequence preference, predicting binding for 36 transcription factors (Matthews correlation coefficient} > 0.3). AVAILABILITY: The datasets we used for training and validation are available at https://virchip.hoffmanlab.org. We have deposited in Zenodo the current version of our software (http://doi.org/10.5281/zenodo.1066928), datasets (http://doi.org/10.5281/zenodo.823297), predictions for 36 transcription factors on Roadmap Epigenomics cell types (http://doi.org/10.5281/zenodo.1455759), and predictions in Cistrome as well as ENCODE-DREAM in vivo TF Binding Site Prediction Challenge (http://doi.org/10.5281/zenodo.1209308).
MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualization, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software.
How sensory evidence is transformed across multiple brain regions to influence behavior remains poorly understood. We trained mice in a visual change detection task designed to separate the covert antecedents of choices from activity associated with their execution. Widefield calcium imaging across dorsal cortex revealed fundamentally different dynamics of activity underlying these processes. While signals related to execution of choice were widespread, fluctuations in sensory evidence in the absence of overt motor responses triggered a confined activity cascade, beginning with transient modulation of visual cortex, followed by sustained recruitment of secondary and primary motor cortex. The activation of motor cortex by sensory evidence was selectively gated by animals' expectation of when the stimulus was likely to change. These results identify distinct activation profiles of specific cortical areas during decision-making, and show that the recruitment of motor cortex depends on the interaction of sensory evidence and expectation.
20 tweets evolutionary biology
Maternally transmitted Wolbachia infect about half of insect species, yet the predominant mode(s) of Wolbachia acquisition remains uncertain. Species-specific associations could be old, with Wolbachia and hosts co-diversifying (i.e., cladogenic acquisition), or relatively young and acquired by horizontal transfer or introgression. The three Drosophila yakuba-clade species ((D. santomea, D. yakuba), D. teissieri) diverged about three million years ago and currently hybridize on Bioko and Sao Tome, west African islands. Each species is polymorphic for very similar Wolbachia that cause weak cytoplasmic incompatibility (CI)-reduced egg hatch when uninfected females mate with infected males. D. yakuba-clade Wolbachia are closely related to wMel, globally polymorphic in D. melanogaster. We use draft Wolbachia and mitochondria genomes to demonstrate that D. yakuba-clade Wolbachia and mitochondrial phylogenies tend to follow host nuclear phylogenies; however, roughly half of D. santomea individuals, sampled both inside and outside of the Sao Tome hybrid zone, have introgressed D. yakuba mitochondria. Both mitochondria and Wolbachia possess more recent common ancestors than the bulk of the host nuclear genomes, precluding cladogenic Wolbachia acquisition. A single discordance between mitochondrial and Wolbachia phylogenies indicates rare horizontal or paternal transmission across close relatives. General concordance of Wolbachia and mitochondrial phylogenies suggest that horizontal transmission is rare, but statistical tests are complicated by varying relative rates of molecular divergence. WO prophage loci associated with CI in wMel are disrupted in the D. yakuba-clade Wolbachia, but these A-group Wolbachia contain a second set of CI loci, horizontally transferred from distantly related B-group Wolbachia via transposable elements.
19 tweets bioengineering
Johan M.S. van der Schoot, Felix L. Fennemann, Michael Valente, Yusuf Dolen, Iris M. Hagemans, Anouk M.D. Becker, Camille M. Le Gall, Duco van Dalen, Alper Cevirgel, J. Armando C. van Bruggen, Melanie Engelfriet, Marieke F. Fransen, Tomislav Caval, Arthur E.H. Bentlage, Maaike Nederend, Jeanette H.W. Leusen, Albert J.R. Heck, Gestur Vidarsson, Carl G Figdor, Martijn Verdoes, Ferenc A Scheeren
Hybridoma technology is instrumental for the development of novel antibody therapeutics and diagnostics. Recent preclinical and clinical studies highlight the importance of antibody isotype for therapeutic efficacy. However, since the sequence encoding the constant domains is fixed, tuning antibody function in hybridomas has been restricted. Here, we demonstrate a versatile CRISPR/HDR platform to rapidly engineer the constant immunoglobulin domains to obtain recombinant hybridomas which secrete antibodies in the preferred format, species and isotype. Using this platform, we obtained recombinant hybridomas secreting Fab fragments, isotype switched chimeric antibodies, and Fc-silent mutants. These antibody products are stable, retain their antigen specificity, and display their intrinsic Fc-effector functions in vitro and in vivo. Furthermore, we can site-specifically attach cargo to these antibody products via chemo-enzymatic modification. We believe this versatile platform facilitates antibody engineering for the entire scientific community, empowering preclinical antibody research.
17 tweets bioinformatics
Microbial genomes are often mosaic: different regions can possess different evolutionary origins due to genetic recombination. The recent feasibility to assemble microbial genomes completely and the availability of sequencing data for complete microbial populations, means that researchers can now investigate the potentially rich evolutionary history of a microbe at a much higher resolution. Here, we present Alpaca: a method to investigate mosaicism in microbial genomes based on kmer similarity of large sequencing datasets. Alpaca partitions a given assembly into various sub-regions and compares their similarity across a population of genomes. The result is a high-resolution map of an entire genome and the most similar scoring clades across the given population.
17 tweets genetics
Abdel Abdellaoui, David Hugh-Jones, Kathryn E. Kemper, Yan Holtz, Michel G. Nivard, Laura Veul, Loic Yengo, Brendan P. Zietsch, Timothy M Frayling, Naomi Wray, Jian Yang, Karin J.H. Verweij, Peter M. Visscher
Human DNA varies across geographic regions, with most variation observed so far reflecting distant ancestry differences. Here, we investigate the geographic clustering of genetic variants that influence complex traits and disease risk in a sample of ~450,000 individuals from Great Britain. Out of 30 traits analyzed, 16 show significant geographic clustering at the genetic level after controlling for ancestry, likely reflecting recent migration driven by socio-economic status (SES). Alleles associated with educational attainment (EA) show most clustering, with EA-decreasing alleles clustering in lower SES areas such as coal mining areas. Individuals that leave coal mining areas carry more EA-increasing alleles on average than the rest of Great Britain. In addition, we leveraged the geographic clustering of complex trait variation to further disentangle regional differences in socio-economic and cultural outcomes through genome-wide association studies on publicly available regional measures, namely coal mining, religiousness, 1970/2015 general election outcomes, and Brexit referendum results.
16 tweets cell biology
Three-dimensional electron microscopy techniques like electron tomography provide valuable insights into cellular structures, and present significant challenges for data storage and dissemination. Here we explored a novel method to publicly release more than 11,000 such datasets, more than 30 TB in total, collected by our group. Our method, based on a peer-to-peer file sharing network built around a blockchain ledger, offers a distributed solution to data storage. In addition, we offer a user-friendly browser-based interface, https://etdb.caltech.edu, for anyone interested to explore and download our data. We discuss the relative advantages and disadvantages of this system and provide tools for other groups to mine our data and/or use the same approach to share their own imaging datasets.
16 tweets epidemiology
Antibiotic exposure can perturb the human gut microbiome and cause changes in the within-host abundance of the genetic determinants of drug-resistance in bacteria. Such within-host dynamics are expected to play an important role in mediating the relationship between antibiotic use and persistence of drug-resistance within a host and its prevalence within a population. Developing a quantitative representation of these within-host dynamics is an important step towards a detailed mechanistic understanding of the population-level processes by which antibiotics select for resistance. Here we study extended-spectrum beta-lactamase (ESBL) producing organisms of the Enterobacteriaceae bacterial family. These have been identified as a global public health priority and are resistant to most first-line antibiotics for treatment of Enterobacteriaceae infections. We analyse data from 833 rectal swabs from a prospective longitudinal study in three European countries including 133 ESBL-positive hospitalised patients. Quantitative polymerase chain reaction was used to quantify the abundance of the CTX-M gene family - the most wide-spread ESBL gene family - and the 16S rRNA gene as a proxy for bacterial load. We find strong dynamic heterogeneity in CTX-M abundance that is largely explained by the variable nature of the swab sampling. Using information on time-varying antibiotic treatments, we develop a dynamic Bayesian model to decompose the serial data into observational variation and ecological signal and to quantify the potentially causal antibiotic effects. We find an association of treatment with cefuroxime or ceftriaxone with increased CTX-M abundance (approximately 21% and 10% daily increase, respectively), while treatment with meropenem or piperacillin-tazobactam is associated with decreased CTX-M (approximately 8% daily decrease for both). Despite a potential risk for indirect selection, oral ciprofloxacin is also associated with decreasing CTX-M (approximately 8% decrease per day). Using our dynamic model to make forward stochastic simulations of CTX-M dynamics, we generate testable predictions about antibiotic impacts on duration of carriage. We find that a typical course of cefuroxime or ceftriaxone is expected to more than double a patient's carriage duration of CTX-M. A typical course of piperacillin-tazobactam or of meropenem - both options to treat hospital acquired infections (HAI) like pneumonia - would reduce CTX-M carriage time relative to ceftriaxone plus amikacin (also an option to treat HAIs) by about 70%. While most antibiotics showed little association with changes in total bacterial abundance, meropenem and piperacillin-tazobactam were associated with decrease in 16S rRNA abundance (3% and 4% daily decrease, respectively). Our study quantifies antibiotic impacts on within-host resistance abundance and resistance carriage, and informs our understanding of how changes in patterns of antibiotic use will affect the prevalence of resistance. This work also provides an analytical framework that can be used more generally to quantify the antibiotic treatment effects on within-host dynamics of determinants of antibiotic resistance using clinical data.
16 tweets cell biology
To increase our understanding of cells, there is a need for specific markers to identify biomolecules, cellular structures and compartments. One type of markers comprises genetically encoded fluorescent probes that are linked with protein domains, peptides and/or signal sequences. These markers are encoded on a plasmid and they allow straightforward, convenient labeling of cultured mammalian cells by introducing the plasmid into the cells. Ideally, the fluorescent marker combines favorable spectroscopic properties (brightness, photostability) with specific labeling of the structure or compartment of interest. Here, we report on our ongoing efforts to generate robust and bright genetically encoded fluorescent markers for highlighting structures and compartments in living cells.
15 tweets epidemiology
Background: Large population-based studies of neuropsychological factors that characterize or precede depressive symptoms are rare. Most studies use small case-control or cross-sectional designs, which may cause selection bias and cannot test temporality. In a large UK population-based cohort we investigated cross-sectional and longitudinal associations between executive control of positive and negative information and adolescent depressive symptoms. Methods: Cohort study of 2315 UK adolescents (ALSPAC) who completed an affective go/no-go task at age 18. Depressive symptoms were assessed with the Clinical Interview Schedule Revised (CIS-R) and short Mood and Feeling Questionnaire (sMFQ) at age 18, and with the sMFQ 15 months later. Analyses were linear multilevel regressions (for cross-sectional associations) and traditional linear regressions (for longitudinal associations), before and after adjustment for confounders. Results: Cross-sectionally, at age 18, there was some evidence that adolescents with more depressive symptoms made more errors in executive control (after adjustments, errors increased by 0.17 of a point per 1 SD increase in sMFQ score, 95% CI 0.08 to 0.25). However, this cross-sectional association was not observed for the CIS-R (.03, 95% CI -.06 to .12). There was no evidence of a difference in executive control errors according to valence. Longitudinally, there was no evidence that reduced executive control was associated with future depressive symptoms. Conclusions: Executive control of positive and negative information does not appear to be a marker of current or future depressive symptoms in adolescents and would therefore not be a useful target in interventions to prevent adolescent depression. According to our evidence, the affective go/no-go task is also not a good candidate for future neuroimaging studies of adolescent depression.
15 tweets microbiology
Background: E. faecium is a gut commensal of humans and animals. In addition, it has recently emerged as an important nosocomial pathogen through the acquisition of genetic elements that confer resistance to antibiotics and virulence. We performed a whole-genome sequencing based study on 96 multidrug-resistant E. faecium strains that asymptomatically colonized five patients with the aim to describe the genome dynamics of this species. Results: The patients were hospitalized on multiple occasions and isolates were collected over periods ranging from 15 months to 6.5 years. Ninety-five of the sequenced isolates belonged to E. faecium clade A1, which was previously determined to be responsible for the vast majority of clinical infections. The clade A1 strains clustered into six clonal groups of highly similar isolates, three of which entirely consisted of isolates from a single patient. We also found evidence of concurrent colonization of patients by multiple distinct lineages and transfer of strains between patients during hospitalisation. We estimated the evolutionary rate of two clonal groups that colonized a single patient at 12.6 and 25.2 single nucleotide polymorphisms (SNPs)/genome/year. A detailed analysis of the accessory genome of one of the clonal groups revealed considerable variation due to gene gain and loss events, including the chromosomal acquisition of a 37 kbp prophage and the loss of an element containing carbohydrate metabolism-related genes. We determined the presence and location of twelve different Insertion Sequence (IS) elements, with ISEfa5 showing a unique pattern of location in 24 of the 25 isolates, suggesting widespread ISEfa5 excision and insertion into the genome during gut colonization. Conclusions: Our findings show that the E. faecium genome is highly dynamic during asymptomatic colonization of the patient gut. We observe considerable genomic flexibility due to frequent horizontal gene transfer and recombination, which can contribute to the generation of genetic diversity within the species and, ultimately, can contribute to its success as a nosocomial pathogen.
14 tweets bioinformatics
Using human hepatocellular carcinoma (HCC) tissue samples stained with seven immune markers including one nuclear counterstain, we compared and evaluated the use of a new dimensionality reduction technique called Uniform Manifold Approximation and Projection (UMAP), as an alternative to t-Distributed Stochastic Neighbor Embedding (t-SNE) in analysing multiplex-immunofluorescence (mIF) derived single-cell data. We adopted an unsupervised clustering algorithm called FlowSOM to identify eight major cell types present in human HCC tissues. UMAP and t-SNE were ran independently on the dataset to qualitatively compare the distribution of clustered cell types in both reduced dimensions. Our comparison shows that UMAP is superior in runtime. Both techniques provide similar arrangements of cell clusters, with the key difference being UMAP's extensive characteristic branching. Most interestingly, UMAP's branching was able to highlight biological lineages, especially in identifying potential hybrid tumour cells (HTC). Survival analysis shows patients with higher proportion of HTC have a worse prognosis (p-value = 0.019). We conclude that both techniques are similar in their visualisation capabilities, but UMAP has a clear advantage over t-SNE in runtime, making it highly plausible to employ UMAP as an alternative to t-SNE in mIF data analysis.
14 tweets genetics
Knowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We developed a method, Relate, scaling to > 10,000 sequences while simultaneously estimating branch lengths, mutational ages, and variable historical population sizes, as well as allowing for data errors. Application to 1000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations. Highly diverged lineages are present in all groups, but most frequent in Africa. Outside Africa, these mainly reflect ancient introgression from groups related to Neanderthals and Denisovans, while African signals instead reflect unknown events, unique to that continent. Our approach allows more powerful inferences of natural selection than previously possible. We identify multiple novel regions under strong positive selection, and multi-allelic traits including hair colour, BMI, and blood pressure, showing strong evidence of directional selection, varying among human groups.
13 tweets bioinformatics
Emerging Linked-Read (aka read-cloud) technologies such as the 10x Genomics Chromium system have great potential for accurate detection and phasing of large-scale human genome structural variations (SVs). By leveraging the long-range information encoded in Linked-Read sequencing, computational techniques are able to detect and characterize complex structural variations that are previously undetectable by short-read methods. However, there is no available Linked-Read method for detection and assembly of novel sequence insertions, DNA sequences present in a given sequenced sample but missing in the reference genome, without requiring whole genome de novo assembly. In this paper, we propose a novel integrated alignment-based and local-assembly-based algorithm, Novel-X, that effectively uses the barcode information encoded in Linked-Read sequencing datasets to improve detection of such events without the need of whole genome de novo assembly. We evaluated our method on two haploid human genomes, CHM1 and CHM13, sequenced on the 10x Genomics Chromium system. These genomes have been also characterized with high coverage PacBio long-reads recently. We also tested our method on NA12878, the well-known HapMap CEPH diploid genome and the child genome in a Yoruba trio (NA19240) which was recently studied on multiple sequencing platforms. Detecting insertion events is very challenging using short reads and the only viable available solution is by long-read sequencing (e.g. PabBio or ONT). Our experiments, however, show that Novel-X finds many insertions that cannot be found by state of the art tools using short-read sequencing data but present in PacBio data. Since Linked-Read sequencing is significantly cheaper than long-read sequencing, our method using Linked-Reads enables routine large-scale screenings of sequenced genomes for novel sequence insertions.
12 tweets bioinformatics
We present KrakenLinked, a metagenomic read classifier for Linked-Reads. We have formulated two algorithms for read classification of metagenomic samples using linked reads: tree pruning and taxa promotion. Tree pruning improves specificity while taxa promotion improves sensitivity. Used together the algorithms improve the taxonomic classification of linked-reads compared to short reads, particularly reducing false identification of taxa. We have implemented these algorithms as functions in KrakenUniq which we make available as KrakenLinked.
12 tweets biophysics
The SNF2h remodeler slides nucleosomes most efficiently as a dimer, yet how the two protomers avoid a tug-of-war is unclear. Furthermore, SNF2h couples histone octamer deformation to nucleosome sliding, but the underlying structural basis remains unknown. Here we present cryo-EM structures of SNF2h-nucleosome complexes with ADP-BeFx that capture two reaction intermediates. In one structure, histone residues near the dyad and in the H2A-H2B acidic patch, distal to the active SNF2h protomer, are disordered. The disordered acidic patch is expected to inhibit the second SNF2h promoter, while disorder near the dyad is expected to promote DNA translocation. The other structure doesn't show octamer deformation, but surprisingly shows a 2bp translocation. FRET studies indicate that ADP-BeFx predisposes SNF2h-nucleosome complexes for an elemental translocation step. We propose a model for allosteric control through the nucleosome, where one SNF2h protomer promotes asymmetric octamer deformation to inhibit the second protomer, while stimulating directional DNA translocation.
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