Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes

Phylogenetic profiling is a computational method to predict genes involved in the same biological process by identifying protein families which tend to be jointly lost or retained across the tree of life. Phylogenetic profiling has customarily been more widely used with prokaryotes than eukaryotes, because the method is thought to require many diverse genomes. There are now many eukaryotic genomes available, but these are considerably larger, and typical phylogenetic profiling methods require at least quadratic time as a function of the number of genes. We introduce a fast, scalable phylogenetic profiling approach entitled HogProf, which leverages hierarchical orthologous groups for the construction of large profiles and locality-sensitive hashing for efficient retrieval of similar profiles. We show that the approach outperforms Enhanced Phylogenetic Tree, a phylogeny-based method, and use the tool to reconstruct networks and query for interactors of the kinetochore complex as well as conserved proteins involved in sexual reproduction: Hap2, Spo11 and Gex1. HogProf enables large-scale phylogenetic profiling across the three domains of life, and will be useful to predict biological pathways among the hundreds of thousands of eukaryotic species that will become available in the coming few years. HogProf is available at https://github.com/DessimozLab/HogProf

Citrullination Was Introduced into Animals by Horizontal Gene Transfer from Cyanobacteria

Protein posttranslational modifications add great sophistication to biological systems. Citrullination, a key regulatory mechanism in human physiology and pathophysiology, is enigmatic from an evolutionary perspective. Although the citrullinating enzymes peptidylarginine deiminases (PADIs) are ubiquitous across vertebrates, they are absent from yeast, worms, and flies. Based on this distribution PADIs were proposed to have been horizontally transferred, but this has been contested. Here, we map the evolutionary trajectory of PADIs into the animal lineage. We present strong phylogenetic support for a clade encompassing animal and cyanobacterial PADIs that excludes fungal and other bacterial homologs. The animal and cyanobacterial PADI proteins share functionally relevant primary and tertiary synapomorphic sequences that are distinct from a second PADI type present in fungi and actinobacteria. Molecular clock calculations and sequence divergence analyses using the fossil record estimate the last common ancestor of the cyanobacterial and animal PADIs to be less than 1 billion years old. Additionally, under an assumption of vertical descent, PADI sequence change during this evolutionary time frame is anachronistically low, even when compared with products of likely endosymbiont gene transfer, mitochondrial proteins, and some of the most highly conserved sequences in life. The consilience of evidence indicates that PADIs were introduced from cyanobacteria into animals by horizontal gene transfer (HGT). The ancestral cyanobacterial PADI is enzymatically active and can citrullinate eukaryotic proteins, suggesting that the PADI HGT event introduced a new catalytic capability into the regulatory repertoire of animals. This study reveals the unusual evolution of a pleiotropic protein modification

A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers

This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cross-platform mobile framework which enables the deployment of mobile apps to multiple platforms using a single TypeScript code base. A deep convolutional neural network was deployed to a cloud-based platform where the mobile app could send photographs of patient's feet for inference to detect the presence of diabetic foot ulcers. The functionality and usability of the system were tested in two clinical settings: Salford Royal NHS Foundation Trust and Lancashire Teaching Hospitals NHS Foundation Trust. The benefits of the system, such as the potential use of the app by patients to identify and monitor their condition are discussed

Description and validation of the LocoWhisk system: Quantifying rodent exploratory, sensory and motor behaviours

Previous studies have demonstrated that analysing whisker movements and locomotion allows us to quantify the behavioural consequences of sensory, motor and cognitive deficits in rodents. Independent whisker and feet trackers exist but there is no fully-automated, open-source software and hardware solution, that measures both whisker movements and gait. New method We present the LocoWhisk arena and new accompanying software (ARTv2) that allows the automatic detection and measurement of both whisker and gait information from high-speed video footage. Results We demonstrate the new whisker and foot detector algorithms on high-speed video footage of freely moving small mammals, and show that whisker movement and gait measurements collected in the LocoWhisk arena are similar to previously reported values in the literature. Comparison with existing method(s) We demonstrate that the whisker and foot detector algorithms, are comparable in accuracy, and in some cases significantly better, than readily available software and manual trackers. Conclusion The LocoWhisk system enables the collection of quantitative data from whisker movements and locomotion in freely behaving rodents. The software automatically records both whisker and gait information and provides added statistical tools to analyse the data. We hope the LocoWhisk system and software will serve as a solid foundation from which to support future research in whisker and gait analysis

Multiparametric flow cytometry to characterize vaccine-induced polyfunctional T cell responses and T cell/NK cell exhaustion and memory phenotypes in mouse immuno-oncology models

Suitable methods to assess in vivo immunogenicity and therapeutic efficacy of cancer vaccines in preclinical cancer models are critical to overcome current limitations of cancer vaccines and enhance the clinical applicability of this promising immunotherapeutic strategy. In particular, availability of methods allowing the characterization of T cell responses to endogenous tumor antigens is required to assess vaccine potency and improve the antigen formulation. Moreover, multiparametric assays to deeply characterize tumor-induced and therapy-induced immune modulation are relevant to design mechanism-based combination immunotherapies. Here we describe a versatile multiparametric flow cytometry method to assess the polyfunctionality of tumor antigen-specific CD4+ and CD8+ T cell responses based on their production of multiple cytokines after short-term ex vivo restimulation with relevant tumor epitopes of the most common mouse strains. We also report the development and application of two 21-color flow cytometry panels allowing a comprehensive characterization of T cell and natural killer cell exhaustion and memory phenotypes in mice with a particular focus on preclinical cancer models

The contributions of fibre atrophy, fibre loss, in situ specific force and voluntary activation to weakness in sarcopenia

The contributions of fibre atrophy, fibre loss, in situ specific force and voluntary activation to weakness in sarcopenia remain unclear. To investigate, forty older (20 women; age 72±4yrs) and 31 younger adults (15 women, age 22±3yrs) completed measurements. The knee extensor maximal voluntary torque (MVC) was measured as well as voluntary activation, patella tendon moment arm length, muscle volume and fascicle architecture to estimate in situ specific force. Fibre cross-sectional area (FCSA), fibre numbers and connective tissue contents were also estimated from vastus lateralis biopsies. The MVC, quadriceps volume and specific force were 39%, 28% and 17% lower, respectively, in old compared with young, but voluntary activation was not different. The difference in muscle size was due in almost equal proportions to lower type II FCSA and fewer fibres. Five years later (n=23) the MVC, muscle volume and voluntary activation in old decreased an additional 12%, 6% and 4%, respectively, but there was no further change in specific force. Conclusions: in situ specific force declines relatively early in older age and reduced voluntary activation occurs later, but the overall weakness in sarcopenia is mainly related to loss of both type I and II fibres and type II fibre atrophy

Development of a combined heart-cut and comprehensive two-dimensional gas chromatography system to extend the carbon range of volatile organic compounds analysis in a single instrument

The majority of atmospheric measurements of volatile organic compounds (VOCs) are usually limited to a small range, either in volatility or time resolution. A combined heart-cut gas chromatography (GC) with comprehensive two-dimensional GC (GC×GC) instrument was developed, specifically to increase the number of VOCs analysed using a single instrument. The system uses valve based modulation and was fully automated, making it suitable for use in the field. A laboratory comparison to an existing dual-channel GC (DC-GC) instrument demonstrated that this new GC-GC×GC can accurately measure atmospheric mixing ratios of C -C VOC species with a wide range of functionalities. Approximately hourly field measurements were conducted at a remote marine atmospheric research station in Bachok, Malaysia. This region was shown to be influenced by clean marine air masses, local anthropogenic and biogenic emission sources and aged emissions transported from highly polluted South East Asian regions. A dramatic shift in air mass direction was observed each day associated with the development of a sea breeze, which influenced the diurnal profiles of species measured at the Bachok site. A proton-transfer-reaction mass spectrometer (PTR-MS) was also deployed at Bachok and compared to the new GC-GC×GC instrument. Overall, the GC-GC×GC instrument has been shown to perform well in lab comparisons and during field observations. This represents a good compromise between volatility and high complexity measurements of VOCs

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation

There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detection frameworks applied to this problem. DFUC2020 provided participants with a comprehensive dataset consisting of 2,000 images for training and 2,000 images for testing. This paper summarizes the results of DFUC2020 by comparing the deep learning-based algorithms proposed by the winning teams: Faster R–CNN, three variants of Faster R–CNN and an ensemble method; YOLOv3; YOLOv5; EfficientDet; and a new Cascade Attention Network. For each deep learning method, we provide a detailed description of model architecture, parameter settings for training and additional stages including pre-processing, data augmentation and post-processing. We provide a comprehensive evaluation for each method. All the methods required a data augmentation stage to increase the number of images available for training and a post-processing stage to remove false positives. The best performance was obtained from Deformable Convolution, a variant of Faster R–CNN, with a mean average precision (mAP) of 0.6940 and an F1-Score of 0.7434. Finally, we demonstrate that the ensemble method based on different deep learning methods can enhance the F1-Score but not the mAP