Exploring in-plane interactions beside an adsorbed molecule with lateral force microscopy.

Atomic force microscopy with a CO-functionalized tip can be used to directly image the internal structure of a planar molecule and to characterize chemical bonds. However, hydrogen atoms usually cannot be directly observed due to their small size. At the same time, these atoms are highly important, since they can direct on-surface chemical reactions. Measuring in-plane interactions at the sides of PTCDA (3,4,9,10-perylenetetracarboxylic dianhydride) molecules with lateral force microscopy allowed us to directly identify hydrogen atoms via their repulsive signature, which we confirmed with a model incorporating radially symmetric atomic interactions. Additional features were observed in the force data and could not be explained by H-bonding of the CO tip with the PTCDA sides. Instead, they are caused by electrostatic interaction of the large dipole of the metal apex, which we verified with density functional theory. This calculation allowed us to estimate the strength of the dipole at the metal tip apex. To further confirm that this dipole generally affects measurements on weakly polarized systems, we investigated the archetypical surface adsorbate of a single CO molecule. We determined the radially symmetric atomic interaction to be valid over a large solid angle of 5.4 sr, corresponding to 82°. We therefore find that in both the PTCDA and CO systems, the underlying interaction preventing direct observations of H-bonding and causing a collapse of the radially symmetric model is the dipole at the metal apex, which plays a significant role when approaching closer than standard imaging heights.

Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare.

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.

An atlas of combinatorial transcriptional regulation in mouse and man.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

Scaling national and international improvement in virtual gene panel curation via a collaborative approach to discordance resolution.

Clinical validity assessments of gene-disease associations underpin analysis and reporting in diagnostic genomics, and yet wide variability exists in practice, particularly in use of these assessments for virtual gene panel design and maintenance. Harmonization efforts are hampered by the lack of agreed terminology, agreed gene curation standards, and platforms that can be used to identify and resolve discrepancies at scale. We undertook a systematic comparison of the content of 80 virtual gene panels used in two healthcare systems by multiple diagnostic providers in the United Kingdom and Australia. The process was enabled by a shared curation platform, PanelApp, and resulted in the identification and review of 2,144 discordant gene ratings, demonstrating the utility of sharing structured gene-disease validity assessments and collaborative discordance resolution in establishing national and international consensus.

Autonomous Single-Molecule Manipulation Based on Reinforcement Learning.

Building nanostructures one-by-one requires precise control of single molecules over many manipulation steps. The ideal scenario for machine learning algorithms is complex, repetitive, and time-consuming. Here, we show a reinforcement learning algorithm that learns how to control a single dipolar molecule in the electric field of a scanning tunneling microscope. Using about 2250 iterations to train, the algorithm learned to manipulate the molecule toward specific positions on the surface. Simultaneously, it generates physical insights into the movement as well as orientation of the molecule, based on the position where the electric field is applied relative to the molecule. This reveals that molecular movement is strongly inhibited in some directions, and the torque is not symmetric around the dipole moment.

Sensor Fusion for the Robust Detection of Facial Regions of Neonates Using Neural Networks.

The monitoring of vital signs and increasing patient comfort are cornerstones of modern neonatal intensive care. Commonly used monitoring methods are based on skin contact which can cause irritations and discomfort in preterm neonates. Therefore, non-contact approaches are the subject of current research aiming to resolve this dichotomy. Robust neonatal face detection is essential for the reliable detection of heart rate, respiratory rate and body temperature. While solutions for adult face detection are established, the unique neonatal proportions require a tailored approach. Additionally, sufficient open-source data of neonates on the NICU is lacking. We set out to train neural networks with the thermal-RGB-fusion data of neonates. We propose a novel indirect fusion approach including the sensor fusion of a thermal and RGB camera based on a 3D time-of-flight (ToF) camera. Unlike other approaches, this method is tailored for close distances encountered in neonatal incubators. Two neural networks were used with the fusion data and compared to RGB and thermal networks. For the class "head" we reached average precision values of 0.9958 (RetinaNet) and 0.9455 (YOLOv3) for the fusion data. Compared with the literature, similar precision was achieved, but we are the first to train a neural network with fusion data of neonates. The advantage of this approach is in calculating the detection area directly from the fusion image for the RGB and thermal modality. This increases data efficiency by 66%. Our results will facilitate the future development of non-contact monitoring to further improve the standard of care for preterm neonates.

Crypt4GH: a file format standard enabling native access to encrypted data.

MOTIVATION: The majority of genome analysis tools and pipelines require data to be decrypted for access. This potentially leaves sensitive genetic data exposed, either because the unencrypted data is not removed after analysis, or because the data leaves traces on the permanent storage medium. RESULTS: : We defined a file container specification enabling direct byte-level compatible random access to encrypted genetic data stored in community standards such as SAM/BAM/CRAM/VCF/BCF. By standardizing this format, we show how it can be added as a native file format to genomic libraries, enabling direct analysis of encrypted data without the need to create a decrypted copy. AVAILABILITY AND IMPLEMENTATION: The Crypt4GH specification can be found at: http://samtools.github.io/hts-specs/crypt4gh.pdf. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Refget: standardized access to reference sequences.

MOTIVATION: Reference sequences are essential in creating a baseline of knowledge for many common bioinformatics methods, especially those using genomic sequencing. RESULTS: We have created refget, a Global Alliance for Genomics and Health API specification to access reference sequences and sub-sequences using an identifier derived from the sequence itself. We present four reference implementations across in-house and cloud infrastructure, a compliance suite and a web report used to ensure specification conformity across implementations. AVAILABILITY AND IMPLEMENTATION: The refget specification can be found at: https://w3id.org/ga4gh/refget. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Note: Reproducibility of potential energy surfaces of organic/metal interfaces on the example of PTCDA on Ag(111).

We recently published a benchmark study of common local, semi-local, and non-local exchange correlation functionals in combination with various van der Waals (vdW) corrections, where we investigated the reproducibility of the potential energy surface of perylenetetracarboxylic dianhydride on Ag(111). This Note presents an additional benchmark of the recently developed non-local many body dispersion (MBD-NL) vdW correction, coupled with the Perdew-Burke-Ernzerhof (PBE) functional. We find that this computation method shows similar performance as the established approaches. Notably, it yields very similar results as PBE + MBD.

Cancer Predisposition Sequencing Reporter (CPSR): A flexible variant report engine for high-throughput germline screening in cancer.

The value of high-throughput germline genetic testing is increasingly recognized in clinical cancer care. Disease-associated germline variants in cancer patients are important for risk management and surveillance, surgical decisions and can also have major implications for treatment strategies since many are in DNA repair genes. With the increasing availability of high-throughput DNA sequencing in cancer clinics and research, there is thus a need to provide clinically oriented sequencing reports for germline variants and their potential therapeutic relevance on a per-patient basis. To meet this need, we have developed the Cancer Predisposition Sequencing Reporter (CPSR), an open-source computational workflow that generates a structured report of germline variants identified in known cancer predisposition genes, highlighting markers of therapeutic, prognostic and diagnostic relevance. A fully automated variant classification procedure based on more than 30 refined American College of Medical Genetics and Genomics (ACMG) criteria represents an integral part of the workflow. Importantly, the set of cancer predisposition genes profiled in the report can be flexibly chosen from more than 40 virtual gene panels established by scientific experts, enabling customization of the report for different screening purposes and clinical contexts. The report can be configured to also list actionable secondary variant findings, as recommended by ACMG. CPSR demonstrates comparable sensitivity and specificity for the detection of pathogenic variants when compared to other algorithms in the field. Technically, the tool is implemented in Python/R, and is freely available through Docker technology. Source code, documentation, example reports and installation instructions are accessible via the project GitHub page: https://github.com/sigven/cpsr.

First-principles calculations of hybrid inorganic-organic interfaces: from state-of-the-art to best practice.

The computational characterization of inorganic-organic hybrid interfaces is arguably one of the technically most challenging applications of density functional theory. Due to the fundamentally different electronic properties of the inorganic and the organic components of a hybrid interface, the proper choice of the electronic structure method, of the algorithms to solve these methods, and of the parameters that enter these algorithms is highly non-trivial. In fact, computational choices that work well for one of the components often perform poorly for the other. As a consequence, default settings for one materials class are typically inadequate for the hybrid system, which makes calculations employing such settings inefficient and sometimes even prone to erroneous results. To address this issue, we discuss how to choose appropriate atomistic representations for the system under investigation, we highlight the role of the exchange-correlation functional and the van der Waals correction employed in the calculation and we provide tips and tricks how to efficiently converge the self-consistent field cycle and to obtain accurate geometries. We particularly focus on potentially unexpected pitfalls and the errors they incur. As a summary, we provide a list of best practice rules for interface simulations that should especially serve as a useful starting point for less experienced users and newcomers to the field.

Whole-genome sequencing reveals new Alzheimer's disease-associated rare variants in loci related to synaptic function and neuronal development.

INTRODUCTION: Genome-wide association studies have led to numerous genetic loci associated with Alzheimer's disease (AD). Whole-genome sequencing (WGS) now permits genome-wide analyses to identify rare variants contributing to AD risk. METHODS: We performed single-variant and spatial clustering-based testing on rare variants (minor allele frequency [MAF] ≤1%) in a family-based WGS-based association study of 2247 subjects from 605 multiplex AD families, followed by replication in 1669 unrelated individuals. RESULTS: We identified 13 new AD candidate loci that yielded consistent rare-variant signals in discovery and replication cohorts (4 from single-variant, 9 from spatial-clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, and CLSTN2. DISCUSSION: Downstream analyses of these novel loci highlight synaptic function, in contrast to common AD-associated variants, which implicate innate immunity and amyloid processing. These loci have not been associated previously with AD, emphasizing the ability of WGS to identify AD-associated rare variants, particularly outside of the exome.

RAF1 rearrangements are common in pancreatic acinar cell carcinomas.

There is now evidence that gene fusions activating the MAPK pathway are relatively common in pancreatic acinar cell carcinoma with potentially actionable BRAF or RET fusions being found in ~30%. We sought to investigate the incidence of RAF1 fusions in pancreatic malignancies with acinar cell differentiation. FISH testing for RAF1 was undertaken on 30 tumors comprising 25 'pure' acinar cell carcinomas, 2 mixed pancreatic acinar-neuroendocrine carcinomas, 1 mixed acinar cell-low grade neuroendocrine tumor and 2 pancreatoblastomas. RAF1 rearrangements were identified in 5 cases and confirmed by DNA and RNA sequencing to represent oncogenic fusions (GATM-RAF1, GOLGA4-RAF1, PDZRN3-RAF1, HERPUD1-RAF1 and TRIM33-RAF1) and to be mutually exclusive with BRAF and RET fusions, as well as KRAS mutations. Large genome-wide copy number changes were common and included 1q gain and/or 1p loss in all five RAF1 FISH-positive acinar cell carcinomas. RAF1 expression by immunohistochemistry was found in 3 of 5 (60%) of fusion-positive cases and no FISH-negative cases. Phospho-ERK1/2 expression was found in 4 of 5 RAF1-fusion-positive cases. Expression of both RAF1 and phospho-ERK1/2 was heterogeneous and often only detected at the tumor-stroma interface, thus limiting their clinical utility. We conclude that RAF1 gene rearrangements are relatively common in pancreatic acinar cell carcinomas (14.3% to 18.5% of cases) and can be effectively identified by FISH with follow up molecular testing. The combined results of several studies now indicate that BRAF, RET or RAF1 fusions occur in between one third and one-half of these tumors but are extremely rare in other pancreatic malignancies. As these fusions are potentially actionable with currently available therapies, a strong argument can be made to perform FISH or molecular testing on all pancreatic acinar cell carcinomas.

Clonal dynamics of native haematopoiesis.

It is currently thought that life-long blood cell production is driven by the action of a small number of multipotent haematopoietic stem cells. Evidence supporting this view has been largely acquired through the use of functional assays involving transplantation. However, whether these mechanisms also govern native non-transplant haematopoiesis is entirely unclear. Here we have established a novel experimental model in mice where cells can be uniquely and genetically labelled in situ to address this question. Using this approach, we have performed longitudinal analyses of clonal dynamics in adult mice that reveal unprecedented features of native haematopoiesis. In contrast to what occurs following transplantation, steady-state blood production is maintained by the successive recruitment of thousands of clones, each with a minimal contribution to mature progeny. Our results demonstrate that a large number of long-lived progenitors, rather than classically defined haematopoietic stem cells, are the main drivers of steady-state haematopoiesis during most of adulthood. Our results also have implications for understanding the cellular origin of haematopoietic disease.

Reproducibility of potential energy surfaces of organic/metal interfaces on the example of PTCDA on Ag(111).

Molecular adsorption at organic/metal interfaces depends on a range of mechanisms: covalent bonds, charge transfer, Pauli repulsion, and van der Waals (vdW) interactions shape the potential energy surface (PES), making it key to understanding organic/metal interfaces. Describing such interfaces with density functional theory requires carefully selecting the exchange correlation (XC) functional and vdW correction scheme. To explore the reproducibility of the PES with respect to the choice of method, we present a benchmark of common local, semi-local, and non-local XC functionals in combination with various vdW corrections. We benchmark these methods using perylene-tetracarboxylic dianhydride on Ag(111), one of the most frequently studied organic/metal interfaces. For each method, we determine the PES using a Gaussian process regression algorithm, which requires only about 50 density functional theory calculations as input. This allows a detailed analysis of the PESs' features, such as the positions and energies of minima and saddle points. Comparing the results from different combinations of XC functionals and vdW corrections enables us to identify trends and differences between the approaches. PESs for different computation methods are in qualitative agreement but also display significant quantitative differences. In particular, the lateral positions of adsorption geometries agree well with experiment, while adsorption heights, energies, and barriers show larger discrepancies.

Silencing of the Drosophila ortholog of SOX5 leads to abnormal neuronal development and behavioral impairment.

SOX5 encodes a transcription factor that is expressed in multiple tissues including heart, lung and brain. Mutations in SOX5 have been previously found in patients with amyotrophic lateral sclerosis (ALS) and developmental delay, intellectual disability and dysmorphic features. To characterize the neuronal role of SOX5, we silenced the Drosophila ortholog of SOX5, Sox102F, by RNAi in various neuronal subtypes in Drosophila. Silencing of Sox102F led to misorientated and disorganized michrochaetes, neurons with shorter dendritic arborization (DA) and reduced complexity, diminished larval peristaltic contractions, loss of neuromuscular junction bouton structures, impaired olfactory perception, and severe neurodegeneration in brain. Silencing of SOX5 in human SH-SY5Y neuroblastoma cells resulted in a significant repression of WNT signaling activity and altered expression of WNT-related genes. Genetic association and meta-analyses of the results in several large family-based and case-control late-onset familial Alzheimer's disease (LOAD) samples of SOX5 variants revealed several variants that show significant association with AD disease status. In addition, analysis for rare and highly penetrate functional variants revealed four novel variants/mutations in SOX5, which taken together with functional prediction analysis, suggests a strong role of SOX5 causing AD in the carrier families. Collectively, these findings indicate that SOX5 is a novel candidate gene for LOAD with an important role in neuronal function. The genetic findings warrant further studies to identify and characterize SOX5 variants that confer risk for AD, ALS and intellectual disability.

NIR Phosphorescent Intramolecularly Bridged Benzoporphyrins and Their Application in Oxygen-Compensated Glucose Optode.

A glucose optode measuring the internal oxygen gradient is presented. The multilayer biosensor is composed of (i) analyte-impermeable transparent support, (ii) first oxygen-sensing layer combined with an enzymatic layer, (iii) diffusion barrier, and (iv) second oxygen-sensing layer. To make this design suitable for measurement in subcutaneous tissue, a pair of NIR phosphorescent indicators with very different spectral properties is chosen. Combination of a conventional Pt(II) tetrabenzoporphyrin dye (absorption and emission maxima at 617 and 772 nm, respectively) used in the first layer and a new intramolecularly bridged Pt(II) complex (absorption and emission maxima at 673 and 872 nm, respectively) in the second layer enables efficient separation of both emission signals. This specially designed dye class is accessible via Scholl-reaction from tetraphenyltetrabenzoporphyrin complexes. For the first time, the new optode allows simultaneous glucose and oxygen measurement in a single spot and therefore accurate compensation of oxygen heterogeneities resulting from fluctuations in the tissue. The presented material covers the dynamic ranges from 0 to 150 hPa O2 and from 0 to 360 mg/dL (20 mM) glucose (at 37 °C).

Phosphoproteomic profiling of mouse primary HSPCs reveals new regulators of HSPC mobilization.

Protein phosphorylation is a central mechanism of signal transduction that both positively and negatively regulates protein function. Large-scale studies of the dynamic phosphorylation states of cell signaling systems have been applied extensively in cell lines and whole tissues to reveal critical regulatory networks, and candidate-based evaluations of phosphorylation in rare cell populations have also been informative. However, application of comprehensive profiling technologies to adult stem cell and progenitor populations has been challenging, due in large part to the scarcity of such cells in adult tissues. Here, we combine multicolor flow cytometry with highly efficient 3-dimensional high performance liquid chromatography/mass spectrometry to enable quantitative phosphoproteomic analysis from 200 000 highly purified primary mouse hematopoietic stem and progenitor cells (HSPCs). Using this platform, we identify ARHGAP25 as a novel regulator of HSPC mobilization and demonstrate that ARHGAP25 phosphorylation at serine 363 is an important modulator of its function. Our approach provides a robust platform for large-scale phosphoproteomic analyses performed with limited numbers of rare progenitor cells. Data from our study comprises a new resource for understanding the molecular signaling networks that underlie hematopoietic stem cell mobilization.

VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research.

Accurate variant calling in next generation sequencing (NGS) is critical to understand cancer genomes better. Here we present VarDict, a novel and versatile variant caller for both DNA- and RNA-sequencing data. VarDict simultaneously calls SNV, MNV, InDels, complex and structural variants, expanding the detected genetic driver landscape of tumors. It performs local realignments on the fly for more accurate allele frequency estimation. VarDict performance scales linearly to sequencing depth, enabling ultra-deep sequencing used to explore tumor evolution or detect tumor DNA circulating in blood. In addition, VarDict performs amplicon aware variant calling for polymerase chain reaction (PCR)-based targeted sequencing often used in diagnostic settings, and is able to detect PCR artifacts. Finally, VarDict also detects differences in somatic and loss of heterozygosity variants between paired samples. VarDict reprocessing of The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma dataset called known driver mutations in KRAS, EGFR, BRAF, PIK3CA and MET in 16% more patients than previously published variant calls. We believe VarDict will greatly facilitate application of NGS in clinical cancer research.

Structure Prediction for Surface-Induced Phases of Organic Monolayers: Overcoming the Combinatorial Bottleneck.

Structure determination and prediction pose a major challenge to computational material science, demanding efficient global structure search techniques tailored to identify promising and relevant candidates. A major bottleneck is the fact that due to the many combinatorial possibilities, there are too many possible geometries to be sampled exhaustively. Here, an innovative computational approach to overcome this problem is presented that explores the potential energy landscape of commensurate organic/inorganic interfaces where the orientation and conformation of the molecules in the tightly packed layer is close to a favorable geometry adopted by isolated molecules on the surface. It is specifically designed to sample the energetically lowest lying structures, including the thermodynamic minimum, in order to survey the particularly rich and intricate polymorphism in such systems. The approach combines a systematic discretization of the configuration space, which leads to a huge reduction of the combinatorial possibilities with an efficient exploration of the potential energy surface inspired by the Basin-Hopping method. Interfacing the algorithm with first-principles calculations, the power and efficiency of this approach is demonstrated for the example of the organic molecule TCNE (tetracyanoethylene) on Au(111). For the pristine metal surface, the global minimum structure is found to be at variance with the geometry found by scanning tunneling microscopy. Rather, our results suggest the presence of surface adatoms or vacancies that are not imaged in the experiment.