Investigating the dynamics of surface-immobilized DNA nanomachines

Surface-immobilization of molecules can have a profound influence on their structure, function and dynamics. Toehold-mediated strand displacement is often used in solution to drive synthetic nanomachines made from DNA, but the effects of surface-immobilization on the mechanism and kinetics of this reaction have not yet been fully elucidated. Here we show that the kinetics of strand displacement in surface-immobilized nanomachines are significantly different to those of the solution phase reaction, and we attribute this to the effects of intermolecular interactions within the DNA layer. We demonstrate that the dynamics of strand displacement can be manipulated by changing strand length, concentration and G/C content. By inserting mismatched bases it is also possible to tune the rates of the constituent displacement processes (toehold-binding and branch migration) independently, and information can be encoded in the time-dependence of the overall reaction. Our findings will facilitate the rational design of surface-immobilized dynamic DNA nanomachines, including computing devices and track-based motors

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit

Interrogating domain-domain interactions with parsimony based approaches

<p>Abstract</p> <p>Background</p> <p>The identification and characterization of interacting domain pairs is an important step towards understanding protein interactions. In the last few years, several methods to predict domain interactions have been proposed. Understanding the power and the limitations of these methods is key to the development of improved approaches and better understanding of the nature of these interactions.</p> <p>Results</p> <p>Building on the previously published Parsimonious Explanation method (PE) to predict domain-domain interactions, we introduced a new Generalized Parsimonious Explanation (GPE) method, which (i) adjusts the granularity of the domain definition to the granularity of the input data set and (ii) permits domain interactions to have different costs. This allowed for preferential selection of the so-called "co-occurring domains" as possible mediators of interactions between proteins. The performance of both variants of the parsimony method are competitive to the performance of the top algorithms for this problem even though parsimony methods use less information than some of the other methods. We also examined possible enrichment of co-occurring domains and homo-domains among domain interactions mediating the interaction of proteins in the network. The corresponding study was performed by surveying domain interactions predicted by the GPE method as well as by using a combinatorial counting approach independent of any prediction method. Our findings indicate that, while there is a considerable propensity towards these special domain pairs among predicted domain interactions, this overrepresentation is significantly lower than in the iPfam dataset.</p> <p>Conclusion</p> <p>The Generalized Parsimonious Explanation approach provides a new means to predict and study domain-domain interactions. We showed that, under the assumption that all protein interactions in the network are mediated by domain interactions, there exists a significant deviation of the properties of domain interactions mediating interactions in the network from that of iPfam data.</p

Single cell derived mRNA signals across human kidney tumors.

Tumor cells may share some patterns of gene expression with their cell of origin, providing clues into the differentiation state and origin of cancer. Here, we study the differentiation state and cellular origin of 1300 childhood and adult kidney tumors. Using single cell mRNA reference maps of normal tissues, we quantify reference "cellular signals" in each tumor. Quantifying global differentiation, we find that childhood tumors exhibit fetal cellular signals, replacing the presumption of "fetalness" with a quantitative measure of immaturity. By contrast, in adult cancers our assessment refutes the suggestion of dedifferentiation towards a fetal state in most cases. We find an intimate connection between developmental mesenchymal populations and childhood renal tumors. We demonstrate the diagnostic potential of our approach with a case study of a cryptic renal tumor. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer

Protein Design Using Continuous Rotamers

Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code

The local and systemic response to SARS-CoV-2 infection in children and adults

While a substantial proportion of adults infected with SARS-CoV-2 progress to develop severe disease, children rarely manifest respiratory complications. Therefore, understanding differences in the local and systemic response to SARS-CoV-2 infection between children and adults may provide important clues about the pathogenesis of SARS-CoV-2 infection. To address this, we first generated a healthy reference multi-omics single cell data set from children (n=30) in whom we have profiled triple matched samples: nasal and tracheal brushings and PBMCs, where we track the developmental changes for 42 airway and 31 blood cell populations from infancy, through childhood to adolescence. This has revealed the presence of naive B and T lymphocytes in neonates and infants with a unique gene expression signature bearing hallmarks of innate immunity. We then contrast the healthy reference with equivalent data from severe paediatric and adult COVID-19 patients (total n=27), from the same three types of samples: upper and lower airways and blood. We found striking differences: children with COVID-19 as opposed to adults had a higher proportion of innate lymphoid and non-clonally expanded naive T cells in peripheral blood, and a limited interferon-response signature. In the airway epithelium, we found the highest viral load in goblet and ciliated cells and describe a novel inflammatory epithelial cell population. These cells represent a transitional regenerative state between secretory and ciliated cells; they were found in healthy children and were enriched in paediatric and adult COVID-19 patients. Epithelial cells display an antiviral and neutrophil-recruiting gene signature that is weaker in severe paediatric versus adult COVID-19. Our matched blood and airway samples allowed us to study the spatial dynamics of infection. Lastly, we provide a user-friendly interface for this data1 as a highly granular reference for the study of immune responses in airways and blood in children

Local and systemic responses to SARS-CoV-2 infection in children and adults

It is not fully understood why COVID-19 is typically milder in children1–3. To examine differences in response to SARS-CoV-2 infection in children and adults, we analysed paediatric and adult COVID-19 patients and healthy controls (total n=93) using single-cell multi-omic profiling of matched nasal, tracheal, bronchial and blood samples. In healthy paediatric airways, we observed cells already in an interferon-activated state, that upon SARS-CoV-2 infection was further induced especially in airway immune cells. We postulate that higher paediatric innate interferon-responses restrict viral replication and disease progression. The systemic response in children was characterised by increases in naive lymphocytes and a depletion of natural killer cells, while in adults cytotoxic T cells and interferon-stimulated subpopulations were significantly increased. We provide evidence that dendritic cells initiate interferon signaling in early infection, and identify novel epithelial cell states that associate with COVID-19 and age. Our matching nasal and blood data showed a strong interferon response in the airways with the induction of systemic interferon-stimulated populations, which were massively reduced in paediatric patients. Together, we provide several mechanisms that explain the milder clinical syndrome observed in children

Inflammatory Rheumatic Disorders and Bone

Inflammatory joint diseases such as rheumatoid arthritis, as well as other rheumatic conditions, such as systemic lupus erythematosus (SLE) and ankylosing spondylitis, comprise a heterogeneous group of joint disorders that are all associated with extra-articular side effects, including bone loss and fractures. The concept of osteoimmunology is based on growing insights into the links between the immune system and bone. The pathogenesis of osteoporosis in these patients is multifactorial. We have, more or less as an example, described this extensively for patients with SLE. High disease activity (inflammation) and immobility are common factors that substantially increase fracture risk in these patients, on top of the background fracture risk based on, among other factors, age, body mass index, and gender. Although no fracture reduction has been shown in intervention studies in patients with inflammatory rheumatic diseases, we present treatment options that might be useful for clinicians who are treating these patients

Single-cell multi-omics analysis of the immune response in COVID-19

Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy

Cholera- and Anthrax-Like Toxins Are among Several New ADP-Ribosyltransferases

Chelt, a cholera-like toxin from Vibrio cholerae, and Certhrax, an anthrax-like toxin from Bacillus cereus, are among six new bacterial protein toxins we identified and characterized using in silico and cell-based techniques. We also uncovered medically relevant toxins from Mycobacterium avium and Enterococcus faecalis. We found agriculturally relevant toxins in Photorhabdus luminescens and Vibrio splendidus. These toxins belong to the ADP-ribosyltransferase family that has conserved structure despite low sequence identity. Therefore, our search for new toxins combined fold recognition with rules for filtering sequences – including a primary sequence pattern – to reduce reliance on sequence identity and identify toxins using structure. We used computers to build models and analyzed each new toxin to understand features including: structure, secretion, cell entry, activation, NAD+ substrate binding, intracellular target binding and the reaction mechanism. We confirmed activity using a yeast growth test. In this era where an expanding protein structure library complements abundant protein sequence data – and we need high-throughput validation – our approach provides insight into the newest toxin ADP-ribosyltransferases