Massively multiplexed nucleic acid detection with Cas13.

The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples1-3 while simultaneously testing for many pathogens4-6. Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents7 self-organize in a microwell array8 to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of more than 4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health9-11.

Benchmarking Metagenomics Tools for Taxonomic Classification.

Metagenomic sequencing is revolutionizing the detection and characterization of microbial species, and a wide variety of software tools are available to perform taxonomic classification of these data. The fast pace of development of these tools and the complexity of metagenomic data make it important that researchers are able to benchmark their performance. Here, we review current approaches for metagenomic analysis and evaluate the performance of 20 metagenomic classifiers using simulated and experimental datasets. We describe the key metrics used to assess performance, offer a framework for the comparison of additional classifiers, and discuss the future of metagenomic data analysis.

Zika virus evolution and spread in the Americas.

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests.

Reversible, opto-mechanically induced spin-switching in a nanoribbon-spiropyran hybrid material.

It has recently been shown that electronic transport in zigzag graphene nanoribbons becomes spin-polarized upon application of an electric field across the nanoribbon width. However, the electric fields required to experimentally induce this magnetic state are typically large and difficult to apply in practice. Here, using both first-principles density functional theory (DFT) and time-dependent DFT, we show that a new spiropyran-based, mechanochromic polymer noncovalently deposited on a nanoribbon can collectively function as a dual opto-mechanical switch for modulating its own spin-polarization. These calculations demonstrate that upon mechanical stress or photoabsorption, the spiropyran chromophore isomerizes from a closed-configuration ground-state to a zwitterionic excited-state, resulting in a large change in dipole moment that alters the electrostatic environment of the nanoribbon. We show that the electronic spin-distribution in the nanoribbon-spiropyran hybrid material can be reversibly modulated via noninvasive optical and mechanical stimuli without the need for large external electric fields. Our results suggest that the reversible spintronic properties inherent to the nanoribbon-spiropyran material allow the possibility of using this hybrid structure as a resettable, molecular-logic quantum sensor where opto-mechanical stimuli are used as inputs and the spin-polarized current induced in the nanoribbon substrate is the measured output.