A natural bacterial pathogen of C. elegans uses a small RNA to induce transgenerational inheritance of learned avoidance.

C. elegans can learn to avoid pathogenic bacteria through several mechanisms, including bacterial small RNA-induced learned avoidance behavior, which can be inherited transgenerationally. Previously, we discovered that a small RNA from a clinical isolate of Pseudomonas aeruginosa, PA14, induces learned avoidance and transgenerational inheritance of that avoidance in C. elegans. Pseudomonas aeruginosa is an important human pathogen, and there are other Pseudomonads in C. elegans' natural habitat, but it is unclear whether C. elegans ever encounters PA14-like bacteria in the wild. Thus, it is not known if small RNAs from bacteria found in C. elegans' natural habitat can also regulate host behavior and produce heritable behavioral effects. Here we screened a set of wild habitat bacteria, and found that a pathogenic Pseudomonas vranovensis strain isolated from the C. elegans microbiota, GRb0427, regulates worm behavior: worms learn to avoid this pathogenic bacterium following exposure, and this learned avoidance is inherited for four generations. The learned response is entirely mediated by bacterially-produced small RNAs, which induce avoidance and transgenerational inheritance, providing further support that such mechanisms of learning and inheritance exist in the wild. We identified Pv1, a small RNA expressed in P. vranovensis, that has a 16-nucleotide match to an exon of the C. elegans gene maco-1. Pv1 is both necessary and sufficient to induce learned avoidance of Grb0427. However, Pv1 also results in avoidance of a beneficial microbiome strain, P. mendocina. Our findings suggest that bacterial small RNA-mediated regulation of host behavior and its transgenerational inheritance may be functional in C. elegans' natural environment, and that this potentially maladaptive response may favor reversal of the transgenerational memory after a few generations. Our data also suggest that different bacterial small RNA-mediated regulation systems evolved independently, but define shared molecular features of bacterial small RNAs that produce transgenerationally-inherited effects.

P. aeruginosa controls both C. elegans attraction and pathogenesis by regulating nitrogen assimilation.

Detecting chemical signals is important for identifying food sources and avoiding harmful agents. Like most animals, C. elegans use olfaction to chemotax towards their main food source, bacteria. However, little is known about the bacterial compounds governing C. elegans attraction to bacteria and the physiological importance of these compounds to bacteria. Here, we address these questions by investigating the function of a small RNA, P11, in the pathogen, Pseudomonas aeruginosa, that was previously shown to mediate learned pathogen avoidance. We discovered that this RNA also affects the attraction of untrained C. elegans to P. aeruginosa and does so by controlling production of ammonia, a volatile odorant produced during nitrogen assimilation. We untangle the complex regulation of P. aeruginosa nitrogen assimilation, which is mediated by a partner-switching mechanism involving environmental nitrates, sensor proteins, and P11. In addition to mediating C. elegans attraction, nitrogen assimilation is important for bacterial fitness and pathogenesis during C. elegans infection by P. aeruginosa . These studies define ammonia as a major mediator of trans-kingdom signaling, reveal the physiological importance of nitrogen assimilation for both bacteria and host organisms, and highlight how a bacterial metabolic pathway can either benefit or harm a host in different contexts.

Cas13-based amplification-free quantification of aberrant RNAs during influenza virus infection.

Influenza A virus RNA synthesis produces full-length and aberrant RNA molecules, which include defective viral genomes (DVG) and mini viral RNAs (mvRNA). Sequencing approaches have shown that several hundred unique aberrant RNA species may be present during infection, and that they can vary in size, segment origin, and sequence. Moreover, a subset of aberrant RNA molecules can bind and activate host pathogen receptor retinoic acid-inducible gene I (RIG-I), leading to innate immune signaling and the expression of type I and III interferons. Understanding the kinetics and distribution of these immunostimulatory aberrant RNA sequences is important for modeling the outcomes of IAV infection. We here first show that reverse transcription and PCR steps can yield imperfect aberrant RNA quantification data in a sequence-dependent manner. Next, we developed an amplification-free LbuCas13a-based detection method to quantify mvRNA amplification kinetics and subcellular distributions. We show that our assay can quantify the copy numbers of 10 specific mvRNA sequences in total RNA from cell culture, animal tissue or clinical nasopharyngeal swab extracts. In addition, we find kinetic and distribution differences between immunostimulatory and non-immunostimulatory mvRNAs, as well as mvRNAs derived from different segments, during infection. Overall, our results reveal a hitherto hidden diversity in the behavior of IAV mvRNAs and they suggest that their production is linked to replication of the individual viral segments. Cas13 is therefore a valuable new tool in our repertoire for investigating the impact of aberrant RNAs on RNA virus infection.

RNA structure modulates Cas13 activity and enables mismatch detection.

The RNA-targeting CRISPR nuclease Cas13 has emerged as a powerful tool for applications ranging from nucleic acid detection to transcriptome engineering and RNA imaging1-6. Cas13 is activated by the hybridization of a CRISPR RNA (crRNA) to a complementary single-stranded RNA (ssRNA) protospacer in a target RNA1,7. Though Cas13 is not activated by double-stranded RNA (dsRNA) in vitro, it paradoxically demonstrates robust RNA targeting in environments where the vast majority of RNAs are highly structured2,8. Understanding Cas13's mechanism of binding and activation will be key to improving its ability to detect and perturb RNA; however, the mechanism by which Cas13 binds structured RNAs remains unknown9. Here, we systematically probe the mechanism of LwaCas13a activation in response to RNA structure perturbations using a massively multiplexed screen. We find that there are two distinct sequence-independent modes by which secondary structure affects Cas13 activity: structure in the protospacer region competes with the crRNA and can be disrupted via a strand-displacement mechanism, while structure in the region 3' to the protospacer has an allosteric inhibitory effect. We leverage the kinetic nature of the strand displacement process to improve Cas13-based RNA detection, enhancing mismatch discrimination by up to 50-fold and enabling sequence-agnostic mutation identification at low (<1%) allele frequencies. Our work sets a new standard for CRISPR-based nucleic acid detection and will enable intelligent and secondary-structure-guided target selection while also expanding the range of RNAs available for targeting with Cas13.

Model-directed generation of CRISPR-Cas13a guide RNAs designs artificial sequences that improve nucleic acid detection.

Generating maximally-fit biological sequences has the potential to transform CRISPR guide RNA design as it has other areas of biomedicine. Here, we introduce model-directed exploration algorithms (MEAs) for designing maximally-fit, artificial CRISPR-Cas13a guides-with multiple mismatches to any natural sequence-that are tailored for desired properties around nucleic acid diagnostics. We find that MEA-designed guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared to guides derived directly from natural sequences, and illuminate interpretable design principles that broaden Cas13a targeting.

Highly multiplexed mRNA quantitation with CRISPR-Cas13.

RNA quantitation tools are often either high-throughput or cost-effective, but rarely are they both. Existing methods can profile the transcriptome at great expense or are limited to quantifying a handful of genes by labor constraints. A technique that permits more throughput at a reduced cost could enable multi-gene kinetic studies, gene regulatory network analysis, and combinatorial genetic screens. Here, we introduce quantitative Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (qCARMEN): an RNA quantitation technique which leverages the programmable RNA-targeting capabilities of CRISPR-Cas13 to address this challenge by quantifying over 4,500 gene-sample pairs in a single experiment. Using qCARMEN, we studied the response profiles of interferon-stimulated genes (ISGs) during interferon (IFN) stimulation and flavivirus infection. Additionally, we observed isoform switching kinetics during epithelial-mesenchymal transition. qCARMEN is a simple and inexpensive technique that greatly enhances the scalability of RNA quantitation for novel applications with performance similar to gold-standard methods.

Multiplexed CRISPR-based Methods for Pathogen Nucleic Acid Detection.

Bacterial and viral pathogens are devastating to human health and well-being. In many regions, dozens of pathogen species and variants co-circulate. Thus, it is important to detect many different species and variants of pathogens in a given sample through multiplexed detection methods. CRISPR-based nucleic acid detection has shown to be a promising step towards an easy-to-use sensitive, specific, and high-throughput method to detect nucleic acids from DNA and RNA viruses and bacteria. Here, we review the current state of multiplexed nucleic acid detection methods with a focus on CRISPR-based methods. We also look toward the future of multiplexed point-of-care diagnostics.

A natural bacterial pathogen of C. elegans uses a small RNA to induce transgenerational inheritance of learned avoidance.

Previously, we discovered that a small RNA from a clinical isolate of Pseudomonas aeruginosa, PA14, induces learned avoidance and its transgenerational inheritance in C. elegans. Pseudomonas aeruginosa is an important human pathogen, and there are other Pseudomonads in C. elegans' natural habitat, but it is unclear whether C. elegans ever encounters PA14-like bacteria in the wild. Thus, it is not known if small RNAs from bacteria found in C. elegans' natural habitat can also regulate host behavior and produce heritable behavioral effects. Here we found that a pathogenic Pseudomonas vranovensis strain isolated from the C. elegans microbiota, GRb0427, like PA14, regulates worm behavior: worms learn to avoid this pathogenic bacterium following exposure to GRb0427, and this learned avoidance is inherited for four generations. The learned response is entirely mediated by bacterially-produced small RNAs, which induce avoidance and transgenerational inheritance, providing further support that such mechanisms of learning and inheritance exist in the wild. Using bacterial small RNA sequencing, we identified Pv1, a small RNA from GRb0427, that matches the sequence of C. elegans maco-1. We find that Pv1 is both necessary and sufficient to induce learned avoidance of Grb0427. However, Pv1 also results in avoidance of a beneficial microbiome strain, P. mendocina; this potentially maladaptive response may favor reversal of the transgenerational memory after a few generations. Our findings suggest that bacterial small RNA-mediated regulation of host behavior and its transgenerational inheritance are functional in C. elegans' natural environment, and that different bacterial small RNA-mediated regulation systems evolved independently but define shared molecular features of bacterial small RNAs that produce transgenerationally-inherited effects.

Optimizing the Cas13 antiviral train: cargo and delivery.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in 2020 highlighted the need for rapid, widespread responses against infectious disease. One such innovation uses CRISPR-Cas13 technology to directly target and cleave viral RNA, thereby inhibiting replication. Due to their programmability, Cas13-based antiviral therapies can be rapidly deployed to target emerging viruses, in comparison with traditional therapeutic development that takes at least 12-18 months, and often many years. Moreover, similar to the programmability of mRNA vaccines, Cas13 antivirals can be developed to target mutations as the virus evolves.

Simplified Cas13-based assays for the fast identification of SARS-CoV-2 and its variants.

The widespread transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for rapid nucleic acid diagnostics that are easy to use outside of centralized clinical laboratories. Here we report the development and performance benchmarking of Cas13-based nucleic acid assays leveraging lyophilised reagents and fast sample inactivation at ambient temperature. The assays, which we named SHINEv.2 (for 'streamlined highlighting of infections to navigate epidemics, version 2'), simplify the previously reported RNA-extraction-free SHINEv.1 technology by eliminating heating steps and the need for cold storage of the reagents. SHINEv.2 detected SARS-CoV-2 in nasopharyngeal samples with 90.5% sensitivity and 100% specificity (benchmarked against the reverse transcription quantitative polymerase chain reaction) in less than 90 min, using lateral-flow technology and incubation in a heat block at 37 °C. SHINEv.2 also allows for the visual discrimination of the Alpha, Beta, Gamma, Delta and Omicron SARS-CoV-2 variants, and can be run without performance losses by using body heat. Accurate, easy-to-use and equipment-free nucleic acid assays could facilitate wider testing for SARS-CoV-2 and other pathogens in point-of-care and at-home settings.

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays.

Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel preamplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a simple proof of principle workflow using stabilized reagents and cell phone camera optical readout, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.

Designing sensitive viral diagnostics with machine learning.

Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome's conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic-target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus's genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT's designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus's variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.

Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants.

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated a clear need for high-throughput, multiplexed and sensitive assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses and their emerging variants. Here, we present a cost-effective virus and variant detection platform, called microfluidic Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (mCARMEN), which combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel to test for up to 21 viruses, including SARS-CoV-2, other coronaviruses and both influenza strains, and demonstrated its diagnostic-grade performance on 525 patient specimens in an academic setting and 166 specimens in a clinical setting. We further developed an mCARMEN panel to enable the identification of 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 2,088 patient specimens with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of SARS-CoV-2 and influenza A viral copies in samples. The mCARMEN platform enables high-throughput surveillance of multiple viruses and variants simultaneously, enabling rapid detection of SARS-CoV-2 variants.

Equipment-free detection of SARS-CoV-2 and Variants of Concern using Cas13.

The COVID-19 pandemic, and the recent rise and widespread transmission of SARS-CoV-2 Variants of Concern (VOCs), have demonstrated the need for ubiquitous nucleic acid testing outside of centralized clinical laboratories. Here, we develop SHINEv2, a Cas13-based nucleic acid diagnostic that combines quick and ambient temperature sample processing and lyophilized reagents to greatly simplify the test procedure and assay distribution. We benchmarked a SHINEv2 assay for SARS-CoV-2 detection against state-of-the-art antigen-capture tests using 96 patient samples, demonstrating 50-fold greater sensitivity and 100% specificity. We designed SHINEv2 assays for discriminating the Alpha, Beta, Gamma and Delta VOCs, which can be read out visually using lateral flow technology. We further demonstrate that our assays can be performed without any equipment in less than 90 minutes. SHINEv2 represents an important advance towards rapid nucleic acid tests that can be performed in any location.

Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events.

Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.

Streamlined inactivation, amplification, and Cas13-based detection of SARS-CoV-2.

The COVID-19 pandemic has highlighted that new diagnostic technologies are essential for controlling disease transmission. Here, we develop SHINE (Streamlined Highlighting of Infections to Navigate Epidemics), a sensitive and specific diagnostic tool that can detect SARS-CoV-2 RNA from unextracted samples. We identify the optimal conditions to allow RPA-based amplification and Cas13-based detection to occur in a single step, simplifying assay preparation and reducing run-time. We improve HUDSON to rapidly inactivate viruses in nasopharyngeal swabs and saliva in 10 min. SHINE's results can be visualized with an in-tube fluorescent readout - reducing contamination risk as amplification reaction tubes remain sealed - and interpreted by a companion smartphone application. We validate SHINE on 50 nasopharyngeal patient samples, demonstrating 90% sensitivity and 100% specificity compared to RT-qPCR with a sample-to-answer time of 50 min. SHINE has the potential to be used outside of hospitals and clinical laboratories, greatly enhancing diagnostic capabilities.

Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events.

SARS-CoV-2 has caused a severe, ongoing outbreak of COVID-19 in Massachusetts with 111,070 confirmed cases and 8,433 deaths as of August 1, 2020. To investigate the introduction, spread, and epidemiology of COVID-19 in the Boston area, we sequenced and analyzed 772 complete SARS-CoV-2 genomes from the region, including nearly all confirmed cases within the first week of the epidemic and hundreds of cases from major outbreaks at a conference, a nursing facility, and among homeless shelter guests and staff. The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission, including outbreaks in homeless populations, and was exported to several other domestic and international sites. The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into MA early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data.

Deployable CRISPR-Cas13a diagnostic tools to detect and report Ebola and Lassa virus cases in real-time.

Recent outbreaks of viral hemorrhagic fevers (VHFs), including Ebola virus disease (EVD) and Lassa fever (LF), highlight the urgent need for sensitive, deployable tests to diagnose these devastating human diseases. Here we develop CRISPR-Cas13a-based (SHERLOCK) diagnostics targeting Ebola virus (EBOV) and Lassa virus (LASV), with both fluorescent and lateral flow readouts. We demonstrate on laboratory and clinical samples the sensitivity of these assays and the capacity of the SHERLOCK platform to handle virus-specific diagnostic challenges. We perform safety testing to demonstrate the efficacy of our HUDSON protocol in heat-inactivating VHF viruses before SHERLOCK testing, eliminating the need for an extraction. We develop a user-friendly protocol and mobile application (HandLens) to report results, facilitating SHERLOCK's use in endemic regions. Finally, we successfully deploy our tests in Sierra Leone and Nigeria in response to recent outbreaks.