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The genus Neisseria includes two pathogenic species, N. gonorrhoeae and N. meningitidis, and numerous commensal species. Neisseria species frequently exchange DNA with one other, primarily via transformation and homologous recombination, and via multiple types of mobile genetic elements (MGEs). Few Neisseria bacteriophages (phages) have been identified and their impact on bacterial physiology is poorly understood. Furthermore, little is known about the range of species that Neisseria phages can infect. In this study, we used three virus prediction tools to scan 248 genomes of 21 different Neisseria species and identified 1302 unique predicted prophages. Using comparative genomics, we found that many predictions are dissimilar from other prophages and MGEs previously described to infect Neisseria species. We also identified similar predicted prophages in genomes of different Neisseria species. Additionally, we examined CRISPR-Cas targeting of each Neisseria genome and predicted prophage. While CRISPR targeting of chromosomal DNA appears to be common among several Neisseria species, we found that 20% of the prophages we predicted are targeted significantly more than the rest of the bacterial genome in which they were identified (i.e., backbone). Furthermore, many predicted prophages are targeted by CRISPR spacers encoded by other species. We then used these results to infer additional host species of known Neisseria prophages and predictions that are highly targeted relative to the backbone. Together, our results suggest that we have identified novel Neisseria prophages, several of which may infect multiple Neisseria species. These findings have important implications for understanding horizontal gene transfer between members of this genus.IMPORTANCEDrug-resistant Neisseria gonorrhoeae is a major threat to human health. Commensal Neisseria species are thought to serve as reservoirs of antibiotic resistance and virulence genes for the pathogenic species N. gonorrhoeae and N. meningitidis. Therefore, it is important to understand both the diversity of mobile genetic elements (MGEs) that can mediate horizontal gene transfer within this genus, and the breadth of species these MGEs can infect. In particular, few bacteriophages (phages) have been identified and characterized in Neisseria species. In this study, we identified a large number of candidate phages integrated within the genomes of commensal and pathogenic Neisseria species, many of which appear to be novel phages. Importantly, we discovered extensive interspecies targeting of predicted phages by Neisseria CRISPR-Cas systems, which may reflect their movement between different species. Uncovering the diversity and host range of phages is essential for understanding how they influence the evolution of their microbial hosts.

CRISPR-based diagnostics enable specific sensing of DNA and RNA biomarkers associated with human diseases. This is achieved through the binding of guide RNAs to a complementary sequence which activates Cas enzymes to cleave reporter molecules. Currently, most CRISPRbased diagnostics rely on target preamplification to reach sufficient sensitivity for clinical applications. This limits quantification capability and adds complexity to the reaction chemistry. Here, we show the combination of a CRISPR/Cas-based reaction with a Nanozyme-Linked ImmunoSorbent Assay which allows for the quantitative and colorimetric readout of Cas13- mediated RNA detection through catalytic metallic nanoparticles at room temperature (CrisprZyme). We demonstrate CrisprZyme is easily adaptable to a lateral-flow-based readout and different Cas enzymes, and enables the sensing of non-coding RNAs including microRNAs, long non-coding RNAs and circular RNAs. We utilise this platform to identify patients with acute myocardial infarction and to monitor cellular differentiation in vitro and in tissue biopsies from prostate cancer patients. We anticipate that CrisprZyme has significant potential as a universally applicable signal catalyst for CRISPR-based diagnostics which will expand the spectrum of targets for preamplification-free, quantitative detection.

Wearable devices provide an alternative pathway to clinical diagnostics by exploiting various physical, chemical and biological sensors to mine physiological (biophysical and/or biochemical) information in real time (preferably, continuously) and in a non-invasive or minimally invasive manner. These sensors can be worn in the form of glasses, jewellery, face masks, wristwatches, fitness bands, tattoo-like devices, bandages or other patches, and textiles. Wearables such as smartwatches have already proved their capability for the early detection and monitoring of the progression and treatment of various diseases, such as COVID-19 and Parkinson disease, through biophysical signals. Next-generation wearable sensors that enable the multimodal and/or multiplexed measurement of physical parameters and biochemical markers in real time and continuously could be a transformative technology for diagnostics, allowing for high-resolution and time-resolved historical recording of the health status of an individual. In this Review, we examine the building blocks of such wearable sensors, including the substrate materials, sensing mechanisms, power modules and decision-making units, by reflecting on the recent developments in the materials, engineering and data science of these components. Finally, we synthesize current trends in the field to provide predictions for the future trajectory of wearable sensors.

Efficient identification of drug mechanisms of action remains a challenge. Computational docking approaches have been widely used to predict drug binding targets; yet, such approaches depend on existing protein structures, and accurate structural predictions have only recently become available from AlphaFold2. Here, we combine AlphaFold2 with molecular docking simulations to predict protein-ligand interactions between 296 proteins spanning Escherichia coli's essential proteome, and 218 active antibacterial compounds and 100 inactive compounds, respectively, pointing to widespread compound and protein promiscuity. We benchmark model performance by measuring enzymatic activity for 12 essential proteins treated with each antibacterial compound. We confirm extensive promiscuity, but find that the average area under the receiver operating characteristic curve (auROC) is 0.48, indicating weak model performance. We demonstrate that rescoring of docking poses using machine learning-based approaches improves model performance, resulting in average auROCs as large as 0.63, and that ensembles of rescoring functions improve prediction accuracy and the ratio of true-positive rate to false-positive rate. This work indicates that advances in modeling protein-ligand interactions, particularly using machine learning-based approaches, are needed to better harness AlphaFold2 for drug discovery.

Cases of suicidal hanging are a common death referred for medico-legal autopsy throughout the world. Although some advocate using postmortem computed tomography (PMCT) without traditional invasive autopsy (TIA) to investigate such deaths, others reject this approach. There is currently limited evidence to guide practice. In this context, the TIA reports and PMCT images of 50 cases of suspected suicidal hanging during an 11-month period were reviewed. The reviewers were blinded to the findings of the other modality. A Cohen’s Kappa coefficient (K) was calculated to assess agreement between TIA and PMCT across a range of pertinent findings. This analysis demonstrated perfect agreement for identification of a ligature (K = 1.00) and a strong level of agreement for identification of a ligature suspension point (K = 0.832) but only a minimal level of agreement for overall ligature mark (K = 0.223). PMCT demonstrated a weak level of agreement for fractures of hyoid bone (K = 0.555) and thyroid cartilage (K = 0.538). Three probable fractures not identified at TIA were identified on PMCT. TIA was shown to be superior in the identification of intramuscular and laryngeal fracture–related haemorrhage/bruising whereas PMCT was superior to TIA in identifying body gas deposition. There was overall good correlation between the natural disease and trauma identified elsewhere in the body during the TIA and PMCT. The study demonstrates that PMCT can assist the investigation of suspected suicidal hangings. However, the accuracy of many findings is limited, and if it is used as an alternative to the TIA, potentially pertinent findings, such as fractures of the laryngeal cartilages, could be missed.

The purpose of this paper was to determine whether recommendations made by King & Murphy (Journal of Autism and Developmental Disorders 44:2717–2733, 2014) in their review of the evidence on autistic people in contact with the criminal justice system (CJS) have been addressed. Research published since 2013 was systematically examined and synthesised. The quality of 47 papers was assessed using the Mixed Methods Appraisal Tool. Findings suggest a limited amount of good quality research has been conducted that has focused on improving our understanding of autistic people in contact with the CJS since 2013. Methodological limitations make direct comparisons between autistic and non-autistic offenders difficult. Autistic people commit a range of crimes and appear to have unique characteristics that warrant further exploration (i.e., vulnerabilities, motivations for offending).

Background:\ud The Adapted Firesetting Assessment Scale was developed for use with adults with developmental disabilities targeting fire-related factors thought to be associated with deliberate firesetting behaviour (i.e. attitudes towards fire, fire interest, fire normalisation, identification with fire and fire safety awareness). However, the psychometric properties of the scale are yet to be evaluated.\ud \ud Method:\ud The reliability, validity, comprehensibility, relevance and comprehensiveness of the Adapted Firesetting Assessment Scale were evaluated. Fifty-nine adults with developmental disabilities, some of whom had a history of firesetting, completed the Adapted Firesetting Assessment Scale on two occasions. Feedback about the questionnaire was sought from both participants and professionals.\ud \ud Results:\ud The AFAS has acceptable internal consistency and excellent test–retest reliability. The attitudes towards fire, fire normalisation, poor fire safety subscales and total scores discriminated firesetters from non-firesetters. Content analysis of feedback indicated items of the AFAS were understood, relevant, accessible and comprehensible.\ud \ud Conclusion:\ud A larger study is needed to examine the factor structure of the AFAS.

Antibiotic tolerance, or the ability of bacteria to survive antibiotic treatment in the absence of genetic resistance, has been linked to chronic and recurrent infections. Tolerant cells are often characterized by a low metabolic state, against which most clinically used antibiotics are ineffective. Here, we show that tolerance readily evolves against antibiotics that are strongly dependent on bacterial metabolism, but does not arise against antibiotics whose efficacy is only minimally affected by metabolic state. We identify a mechanism of tolerance evolution in E. coli involving deletion of the sodium-proton antiporter gene nhaA, which results in downregulated metabolism and upregulated stress responses. Additionally, we find that cycling of antibiotics with different metabolic dependencies interrupts evolution of tolerance in vitro, increasing the lifetime of treatment efficacy. Our work highlights the potential for limiting the occurrence and extent of tolerance by accounting for antibiotic dependencies on bacterial metabolism.

To elucidate principles operating in native biological systems and to develop novel biotechnologies, synthetic biology aims to build and integrate synthetic gene circuits within native transcriptional networks. The utility of synthetic gene circuits for cell engineering relies on the ability to control the expression of all constituent transgene components. Transgene silencing, defined as the loss of expression over time, persists as an obstacle for engineering primary cells and stem cells with transgenic cargos. In this review, we highlight the challenge that transgene silencing poses to the robust engineering of mammalian cells, outline potential molecular mechanisms of silencing, and present approaches for preventing transgene silencing. We conclude with a perspective identifying future research directions for improving the performance of synthetic gene circuits.

Fibrosis-driven solid organ failure is a major global health burden. Spiny mice (genus: Acomys ) are terrestrial mammals that regenerate severe skin wounds without scars to avoid predation. To test whether spiny mice can also regenerate internal organ injuries, we performed acute obstructive or ischemic surgeries on adult kidneys of Acomys cahirinus compared to Mus musculus. Despite equivalent acute tissue damage, Acomys fully regenerate nephron structure, vascular & lymphatic networks, and organ function without fibrosis by 14d while Mus (CD1 or C57BL/6) develop extensive interstitial fibrosis and progress to organ failure and death. Comparative transcriptomic, epigenetic, and single-cell assays revealed that the Acomys genome appears poised to initiate a regenerative response at the time of injury. In addition, we found the Hippo pathway effector protein YAP localized to the nucleus in renal tubular epithelial cells (RTEs) undergoing scarless wound healing in Acomys while it was either cytoplasmic or not detectable in Mus RTEs. Experiments in vitro revealed an accelerated PP2A-dependent YAP phosphatase activity that maintained nuclear YAP in Acomys RTEs and was not detected in Mus or human cells. Treatment of Acomys in vivo with the nuclear YAP-TEAD inhibitor verteporfin converted tissue regeneration to fibrosis in the dermis and similar experiments for the kidney are in progress. These results suggest that the spiny mouse genome evolved both transcriptional and post-translational adaptations important for scar-free regenerative wound healing in vivo .

Current newborn screening programs for Pompe disease (PD) and mucopolysaccharidosis type I (MPS I) suffer from a high false positive rate and long turnaround time for clinical follow up. This study aimed to develop a novel proteomics-based assay for rapid and accurate second-tier screening of PD and MPS I. A fast turnaround assay would enable the identification of severe cases who need immediate clinical follow up and treatment.We developed an immunocapture coupled with mass spectrometry-based proteomics (Immuno-SRM) assay to quantify GAA and IDUA proteins in dried blood spots (DBS) and buccal swabs. Sensitivity, linearity, reproducibility, and protein concentration range in healthy control samples were determined. Clinical performance was evaluated in known PD and MPS I patients as well as pseudodeficiency and carrier cases.Using three 3.2 mm punches (~13.1 μL of blood) of DBS, the assay showed reproducible and sensitive quantification of GAA and IDUA. Both proteins can also be quantified in buccal swabs with high reproducibility and sensitivity. Infantile onset Pompe disease (IOPD) and severe MPS I cases are readily identifiable due to the absence of GAA and IDUA, respectively. In addition, late onset Pompe disease (LOPD) and attenuated MPS I patients showed much reduced levels of the target protein. By contrast, pseudodeficiency and carrier cases exhibited significant higher target protein levels compared to true patients.Direct quantification of endogenous GAA and IDUA peptides in DBS by Immuno-SRM can be used for second-tier screening to rapidly identify severe PD and MPS I patients with a turnaround time of1 week. Such patients could benefit from immediate clinical follow up and possibly earlier treatment.

Intercellular communication is important for tissue development and homeostasis, and when dysregulated contributes to a multitude of pathobiological processes. Cells communicate with each other by several mechanisms, including direct cell-cell contacts between membrane-tethered ligands and receptors on the cell surface, through secreted molecules that bind their cognate receptor on the receiving cell, or alternative modalities such as exosomes. The study of cell-cell communication networks using single-cell genomic approaches is now under intensive investigation, and innovative algorithms to interpret the data, infer how cells interact and identify the downstream effectors of a putative binding of a ligand to its cognate receptor are critically needed. Here, we describe a protocol to run CellComm, a data-driven systems biology algorithm that integrates single-cell RNA-sequencing, protein interaction networks, and gene regulatory networks to infer which cells within a heterogeneous tissue are actively communicating, as well as their downstream transcriptional programs. When spatial transcriptomics data is available, CellComm additionally identifies spatially-resolved cell-cell interactions within the tissue. This protocol is associated with our Nature Cell Biology paper describing our algorithm: CellComm infers cellular crosstalk that drives hematopoietic stem and progenitor cell development.

RADxSM Tech's mission is to rapidly accelerate deployment of SARS-CoV-2 tests and could not utilize typical grant application and review processes that can run 4 to 6 months. Instead, RADx Tech leveraged methodologies developed by CIMIT and utilized by POCTRN as described further in this special issue. RADx Tech uses a multi-stage review with two review panels, a Viability Panel and a Steering Panel, that are supported by subject matter experts and a Deep Dive team. Members of the panels have extensive commercialization and business experience in addition to scientific and technical knowledge. The Viability Panel is responsible for assessing whether the proposal is a good fit with the RADx Tech Program and whether it should be recommended to move into a Deep Dive. Less detailed information is requested in the application than a typical SBIR application since the application is refined and details added during the Deep Dive. The Steering Panel reviews the results from the Deep Dive and decides whether to recommend further funding. Everyone on the Viability Panel and Steering Panel reviews every application, thereby providing consistency and context for the reviewers. Utilization of an “assess, improve, and then select” process with review panels comprised of highly experienced review panel members has resulted in improved timing, efficiency, and effectiveness of reviews and has the potential to be extensible beyond RADx Tech.

Schistosomes cause untold disease and disability in the developing world. Here, we introduce SchistoCyte Atlas, a web-based platform to explore gene expression at single-cell resolution in adult Schistosoma mansoni. Similar resources accessible by the non-specialists across the globe will expedite our ability to understand the biology of these devastating parasites.