Showing papers by "James J. Collins published in 2020"

Cell-free biosensors for rapid detection of water contaminants

Abstract: Lack of access to safe drinking water is a global problem, and methods to reliably and easily detect contaminants could be transformative We report the development of a cell-free in vitro transcription system that uses RNA Output Sensors Activated by Ligand Induction (ROSALIND) to detect contaminants in water A combination of highly processive RNA polymerases, allosteric protein transcription factors and synthetic DNA transcription templates regulates the synthesis of a fluorescence-activating RNA aptamer The presence of a target contaminant induces the transcription of the aptamer, and a fluorescent signal is produced We apply ROSALIND to detect a range of water contaminants, including antibiotics, small molecules and metals We also show that adding RNA circuitry can invert responses, reduce crosstalk and improve sensitivity without protein engineering The ROSALIND system can be freeze-dried for easy storage and distribution, and we apply it in the field to test municipal water supplies, demonstrating its potential use for monitoring water quality

Ultrasensitive CRISPR-based diagnostic for field-applicable detection of Plasmodium species in symptomatic and asymptomatic malaria.

Abstract: Asymptomatic carriers of Plasmodium parasites hamper malaria control and eradication. Achieving malaria eradication requires ultrasensitive diagnostics for low parasite density infections (<100 parasites per microliter blood) that work in resource-limited settings (RLS). Sensitive point-of-care diagnostics are also lacking for nonfalciparum malaria, which is characterized by lower density infections and may require additional therapy for radical cure. Molecular methods, such as PCR, have high sensitivity and specificity, but remain high-complexity technologies impractical for RLS. Here we describe a CRISPR-based diagnostic for ultrasensitive detection and differentiation of Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, and Plasmodium malariae, using the nucleic acid detection platform SHERLOCK (specific high-sensitivity enzymatic reporter unlocking). We present a streamlined, field-applicable, diagnostic comprised of a 10-min SHERLOCK parasite rapid extraction protocol, followed by SHERLOCK for 60 min for Plasmodium species-specific detection via fluorescent or lateral flow strip readout. We optimized one-pot, lyophilized, isothermal assays with a simplified sample preparation method independent of nucleic acid extraction, and showed that these assays are capable of detection below two parasites per microliter blood, a limit of detection suggested by the World Health Organization. Our P. falciparum and P. vivax assays exhibited 100% sensitivity and specificity on clinical samples (5 P. falciparum and 10 P. vivax samples). This work establishes a field-applicable diagnostic for ultrasensitive detection of asymptomatic carriers as well as a rapid point-of-care clinical diagnostic for nonfalciparum malaria species and low parasite density P. falciparum infections.

Evidence that coronavirus superspreading is fat-tailed.

Abstract: Superspreaders, infected individuals who result in an outsized number of secondary cases, are believed to underlie a significant fraction of total SARS-CoV-2 transmission. Here, we combine empirical observations of SARS-CoV and SARS-CoV-2 transmission and extreme value statistics to show that the distribution of secondary cases is consistent with being fat-tailed, implying that large superspreading events are extremal, yet probable, occurrences. We integrate these results with interaction-based network models of disease transmission and show that superspreading, when it is fat-tailed, leads to pronounced transmission by increasing dispersion. Our findings indicate that large superspreading events should be the targets of interventions that minimize tail exposure.

A single-cell RNA-seq atlas of Schistosoma mansoni identifies a key regulator of blood feeding.

Abstract: Schistosomiasis is a neglected tropical disease that infects 240 million people. With no vaccines and only one drug available, new therapeutic targets are needed. The causative agents, schistosomes, are intravascular flatworm parasites that feed on blood and lay eggs, resulting in pathology. The function of the parasite's various tissues in successful parasitism are poorly understood, hindering identification of therapeutic targets. Using single-cell RNA sequencing (RNA-seq), we characterize 43,642 cells from the adult schistosome and identify 68 distinct cell populations, including specialized stem cells that maintain the parasite's blood-digesting gut. These stem cells express the gene hnf4, which is required for gut maintenance, blood feeding, and pathology in vivo. Together, these data provide molecular insights into the organ systems of this important pathogen and identify potential therapeutic targets.

A deep learning approach to programmable RNA switches.

Abstract: Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology. RNA can be used as a programmable tool for detection of biological analytes. Here the authors use deep neural networks to predict toehold switch functionality in synthetic biology applications.

Predictive biology: modelling, understanding and harnessing microbial complexity.

Abstract: Predictive biology is the next great chapter in synthetic and systems biology, particularly for microorganisms. Tasks that once seemed infeasible are increasingly being realized such as designing and implementing intricate synthetic gene circuits that perform complex sensing and actuation functions, and assembling multi-species bacterial communities with specific, predefined compositions. These achievements have been made possible by the integration of diverse expertise across biology, physics and engineering, resulting in an emerging, quantitative understanding of biological design. As ever-expanding multi-omic data sets become available, their potential utility in transforming theory into practice remains firmly rooted in the underlying quantitative principles that govern biological systems. In this Review, we discuss key areas of predictive biology that are of growing interest to microbiology, the challenges associated with the innate complexity of microorganisms and the value of quantitative methods in making microbiology more predictable. In this Review, Lopatkin and Collins discuss key areas of predictive biology that are of growing interest to microbiology, the challenges associated with the innate complexity of microorganisms and the value of quantitative methods in making microbiology more predictable.

A CRISPR-based assay for the detection of opportunistic infections post-transplantation and for the monitoring of transplant rejection

Abstract: In organ transplantation, infection and rejection are major causes of graft loss. They are linked by the net state of immunosuppression. To diagnose and treat these conditions earlier, and to improve long-term patient outcomes, refined strategies for the monitoring of patients after graft transplantation are needed. Here, we show that a fast and inexpensive assay based on CRISPR–Cas13 accurately detects BK polyomavirus DNA and cytomegalovirus DNA from patient-derived blood and urine samples, as well as CXCL9 messenger RNA (a marker of graft rejection) at elevated levels in urine samples from patients experiencing acute kidney transplant rejection. The assay, which we adapted for lateral-flow readout, enables—via simple visualization—the post-transplantation monitoring of common opportunistic viral infections and of graft rejection, and should facilitate point-of-care post-transplantation monitoring. A fast and inexpensive point-of-care assay based on CRISPR–Cas13 accurately detects the DNA of opportunistic viruses in blood and urine samples as well as an mRNA marker of renal transplant rejection in urine samples.

ImmGen at 15

Abstract: 700 comment | SERIES ImmGen at 15 Nature Immunology's 20 th anniversary is a good opportunity to reminisce about the ImmGen collective endeavor-its goals, successes and horror stories-and the group's exploration of various modes of scientific publishing The Immunological Genome Project T he Immunological Genome Project (ImmGen) is a collaborative group of immunology and computational biology laboratories that perform a thorough dissection of gene expression and its regulation in the immune system of the mouse This activity first centered on mRNA expression and then expanded to microRNA (miRNA), chromatin structure, nuclear organization and protein-RNA relationships Shared protocols, data generation and QC pipelines have yielded data that can be directly compared from >250 stem, lymphoid and myeloid cell types, at baseline or under challenge The group develops and applies computational tools to decipher regulatory connections and transcriptional control From its inception, data generated by ImmGen were meant to be a public resource, and they can be accessed through dedicated web and smartphone platforms that use interactive graphic displays that make the results intuitive to users

Large-scale RNAi screening uncovers therapeutic targets in the parasite Schistosoma mansoni

Abstract: Schistosome parasites kill 250,000 people every year. Treatment of schistosomiasis relies on the drug praziquantel. Unfortunately, a scarcity of molecular tools has hindered the discovery of new drug targets. Here, we describe a large-scale RNA interference (RNAi) screen in adult Schistosoma mansoni that examined the function of 2216 genes. We identified 261 genes with phenotypes affecting neuromuscular function, tissue integrity, stem cell maintenance, and parasite survival. Leveraging these data, we prioritized compounds with activity against the parasites and uncovered a pair of protein kinases (TAO and STK25) that cooperate to maintain muscle-specific messenger RNA transcription. Loss of either of these kinases results in paralysis and worm death in a mammalian host. These studies may help expedite therapeutic development and invigorate studies of these neglected parasites.

Parallel bimodal single-cell sequencing of transcriptome and chromatin accessibility.

Abstract: Joint profiling of transcriptome and chromatin accessibility within single cells allows for the deconstruction of the complex relationship between transcriptional states and upstream regulatory programs determining different cell fates. Here, we developed an automated method with high sensitivity, assay for single-cell transcriptome and accessibility regions (ASTAR-seq), for simultaneous measurement of whole-cell transcriptome and chromatin accessibility within the same single cell. To show the utility of ASTAR-seq, we profiled 384 mESCs under naive and primed pluripotent states as well as a two-cell like state, 424 human cells of various lineage origins (BJ, K562, JK1, and Jurkat), and 480 primary cord blood cells undergoing erythroblast differentiation. With the joint profiles, we configured the transcriptional and chromatin accessibility landscapes of discrete cell states, uncovered linked sets of cis-regulatory elements and target genes unique to each state, and constructed interactome and transcription factor (TF)-centered upstream regulatory networks for various cell states.

Creating CRISPR-responsive smart materials for diagnostics and programmable cargo release.

Abstract: Materials that sense and respond to biological signals in their environment have a broad range of potential applications in drug delivery, medical devices and diagnostics. Nucleic acids are important biological cues that encode information about organismal identity and clinically relevant phenotypes such as drug resistance. We recently developed a strategy to design nucleic acid-responsive materials using the CRISPR-associated nuclease Cas12a as a user-programmable sensor and material actuator. This approach improves on the sensitivity of current DNA-responsive materials while enabling their rapid repurposing toward new sequence targets. Here, we provide a comprehensive resource for the design, synthesis and actuation of CRISPR-responsive hydrogels. First, we provide guidelines for the synthesis of Cas12a guide RNAs (gRNAs) for in vitro applications. We then outline methods for the synthesis of both polyethylene glycol-DNA (PEG-DNA) and polyacrylamide-DNA (PA-DNA) hydrogels, as well as their controlled degradation using Cas12a for the release of cargos, including small molecules, enzymes, nanoparticles and living cells within hours. Finally, we detail the design and assembly of microfluidic paper-based devices that use Cas12a-sensitive hydrogels to convert DNA inputs into a variety of visual and electronic readouts for use in diagnostics. Following the initial validation of the gRNA and Cas12a components (1 d), the synthesis and testing of either PEG-DNA or PA-DNA hydrogels require 3-4 d of laboratory time. Optional extensions, including the release of primary human cells or the design of the paper-based diagnostic, require an additional 2-3 d each.

Diversification of reprogramming trajectories revealed by parallel single-cell transcriptome and chromatin accessibility sequencing

Abstract: Cellular reprogramming suffers from low efficiency especially for the human cells. To deconstruct the heterogeneity and unravel the mechanisms for successful reprogramming, we adopted single-cell RNA sequencing (scRNA-Seq) and single-cell assay for transposase-accessible chromatin (scATAC-Seq) to profile reprogramming cells across various time points. Our analysis revealed that reprogramming cells proceed in an asynchronous trajectory and diversify into heterogeneous subpopulations. We identified fluorescent probes and surface markers to enrich for the early reprogrammed human cells. Furthermore, combinatory usage of the surface markers enabled the fine segregation of the early-intermediate cells with diverse reprogramming propensities. scATAC-Seq analysis further uncovered the genomic partitions and transcription factors responsible for the regulatory phasing of reprogramming process. Binary choice between a FOSL1 and a TEAD4-centric regulatory network determines the outcome of a successful reprogramming. Together, our study illuminates the multitude of diverse routes transversed by individual reprogramming cells and presents an integrative roadmap for identifying the mechanistic part list of the reprogramming machinery.

Continuous bioactivity-dependent evolution of an antibiotic biosynthetic pathway.

Abstract: Antibiotic biosynthetic gene clusters (BGCs) produce bioactive metabolites that impart a fitness advantage to their producer, providing a mechanism for natural selection. This selection drives antibiotic evolution and adapts BGCs for expression in different organisms, potentially providing clues to improve heterologous expression of antibiotics. Here, we use phage-assisted continuous evolution (PACE) to achieve bioactivity-dependent adaptation of the BGC for the antibiotic bicyclomycin (BCM), facilitating improved production in a heterologous host. This proof-of-principle study demonstrates that features of natural bioactivity-dependent evolution can be engineered to access unforeseen routes of improving metabolic pathways and product yields.

Point-of-Care Devices to Detect Zika and Other Emerging Viruses.

Abstract: Rapid diagnostic tests (point-of-care devices) are critical components of informed patient care and public health monitoring (surveillance applications). We propose that among the many rapid diagnostics platforms that have been tested or are in development, lateral flow immunoassays and synthetic biology-based diagnostics (including CRISPR-based diagnostics) represent the best overall options given their ease of use, scalability for manufacturing, sensitivity, and specificity. This review describes the identification of lateral flow immunoassay monoclonal antibody pairs that detect and distinguish between closely related pathogens and that are used in combination with functionalized multicolored nanoparticles and computational methods to deconvolute data. We also highlight the promise of synthetic biology-based diagnostic tests, which use synthetic genetic circuits that activate upon recognition of a pathogen-associated nucleic acid sequence, and discuss how the combined or parallel use of lateral flow immunoassays and synthetic biology tools may represent the future of scalable rapid diagnostics.

Using Natural Language Processing to Learn the Grammar of Glycans

Abstract: While nucleic acids and proteins receive ample attention, progress on understanding the structural and functional roles of carbohydrates has lagged behind. Here, we develop a language model for glycans, SweetTalk, taking into account glycan connectivity and composition. We use this model to investigate motifs in glycan substructures, classify them according to their O-/N-linkage, and predict their immunogenicity with an accuracy of ∼92%, opening up the potential for rational glycoengineering.

Racial disparities in COVID-19 mortality across Michigan, United States

Abstract: Black populations in the US are disproportionately affected by the COVID-19 pandemic, but the increased mortality burden after accounting for health and demographic characteristics is not well understood. We evaluated COVID-19 mortality in Michigan using individual-level death certificate and surveillance data from the Michigan Department of Health and Human Services from March 16 to October 26, 2020. Among the 6,065 COVID-19-related deaths, Black individuals experienced 3.6 times the mortality rate as White individuals. Black individuals under 65 years without comorbidities had a mortality rate 12.6 times that of their White counterparts. After accounting for age, sex, and comorbidities, we found that Black individuals in all strata are at higher risk of COVID-19 mortality than their White peers. We demonstrate that inequities in mortality are driven by ongoing systemic racism, as opposed to comorbidity burden or older age, and further highlight how underlying disparities across the race are compounded in crises.

Identification of Simplified Microbial Communities That Inhibit Clostridioides difficile Infection through Dilution/Extinction.

Abstract: The gastrointestinal microbiome plays an important role in limiting susceptibility to infection with Clostridioides difficile. To better understand the ecology of bacteria important for C. difficile colonization resistance, we developed an experimental platform to simplify complex communities of fecal bacteria through dilution and rapidly screen for their ability to resist C. difficile colonization after challenge, as measured by >100-fold reduction in levels of C. difficile in challenged communities. We screened 76 simplified communities diluted from cultures of six fecal donors and identified 24 simplified communities that inhibited C. difficile colonization in vitro. Sequencing revealed that simplified communities were composed of 19 to 67 operational taxonomic units (OTUs) and could be partitioned into four distinct community types. One simplified community could be further simplified from 56 to 28 OTUs through dilution and retain the ability to inhibit C. difficile. We tested the efficacy of seven simplified communities in a humanized microbiota mouse model. We found that four communities were able to significantly reduce the severity of the initial C. difficile infection and limit susceptibility to disease relapse. Analysis of fecal microbiomes from treated mice demonstrated that simplified communities accelerated recovery of indigenous bacteria and led to stable engraftment of 19 to 22 OTUs from simplified communities. Overall, the insights gained through the identification and characterization of these simplified communities increase our understanding of the microbial dynamics of C. difficile infection and recovery. IMPORTANCEClostridioides difficile is the leading cause of antibiotic-associated diarrhea and a significant health care burden. Fecal microbiota transplantation is highly effective at treating recurrent C. difficile disease; however, uncertainties about the undefined composition of fecal material and potential long-term unintended health consequences remain. These concerns have motivated studies to identify new communities of microbes with a simpler composition that will be effective at treating disease. This work describes a platform for rapidly identifying and screening new simplified communities for efficacy in treating C. difficile infection. Four new simplified communities of microbes with potential for development of new therapies to treat C. difficile disease are identified. While this platform was developed and validated to model infection with C. difficile, the underlying principles described in the paper could be easily modified to develop therapeutics to treat other gastrointestinal diseases.

A single-cell RNAseq atlas of the pathogenic stage of Schistosoma mansoni identifies a key regulator of blood feeding

Abstract: Schistosomiasis is an ancient and chronic neglected tropical disease that infects over 240 million people and kills over 200,000 of the world’s poorest people every year1, 2. There are no vaccines and because there is only one drug available, the need for new therapeutics is great. The causative agents of this disease are flatworm parasites that dwell inside the host’s circulation, often for decades, where they feed on blood and lay eggs which are primarily responsible for disease pathology. As metazoans comprised of multiple tissue types, understanding the schistosome’s tissues on a molecular level and their functions during what can be decades of successful parasitism could suggest novel therapeutic strategies. Here, we employ single-cell RNAseq to characterize 43,642 cells from the pathogenic (adult) stage of the schistosome lifecycle. From these data, we characterize 68 molecularly distinct cell populations that comprise nearly all tissues described morphologically, including the nervous and reproductive systems. We further uncover a lineage of somatic stem cells responsible for producing and maintaining the parasite’s gut – the primary tissue responsible for digestion of host blood. Finally, we show that a homologue of hepatocyte nuclear factor 4 (hnf4) is expressed in this gut lineage and required for gut maintenance, blood feeding and inducing egg-associated pathology in vivo. Together, the data highlight the utility of this single-cell RNAseq atlas to understand schistosome biology and identify potential therapeutic interventions.

Identification of simplified microbial communities that inhibit Clostridioides difficile infection through dilution/extinction

Abstract: The gastrointestinal microbiome plays an important role in limiting susceptibility to infection with Clostridioides difficile. To better understand the ecology of bacteria important for C. difficile colonization resistance, we developed an experimental platform to simplify complex communities of fecal bacteria through dilution and rapidly screen for their ability to inhibit C. difficile. We simplified complex communities from six fecal donors and found that 17% of simplified communities inhibited C. difficile growth when initially isolated and when re-cultured from frozen stocks. Composition varied between simplified communities based upon fecal donor used for dilution; complexity ranged from 19-67 OTUs. One simplified community could be further simplified through dilution and retain the ability to inhibit C. difficile. We tested efficacy of seven simplified communities in a humanized microbiota mouse model and found that four communities were able to significantly reduce the severity of the initial C. difficile infection and limit susceptibility to disease relapse. Analysis of fecal microbiomes from treated mice demonstrated that simplified communities accelerated recovery of endogenous bacteria and led to stable engraftment of at least 20% of bacteria from simplified communities. Overall, the insights gained through the identification and characterization of these simplified communities increase our understanding of the microbial dynamics of C. difficile infection and recovery.

SweetOrigins: Extracting Evolutionary Information from Glycans

Abstract: Glycans, the most diverse biopolymer and crucial for many biological processes, are shaped by evolutionary pressures stemming in particular from host-pathogen interactions. While this positions glycans as being essential for understanding and targeting host-pathogen interactions, their considerable diversity and a lack of methods has hitherto stymied progress in leveraging their predictive potential. Here, we utilize a curated dataset of 12,674 glycans from 1,726 species to develop and apply machine learning methods to extract evolutionary information from glycans. Our deep learning-based language model SweetOrigins provides evolution-informed glycan representations that we utilize to discover and investigate motifs used for molecular mimicry-mediated immune evasion by commensals and pathogens. Novel glycan alignment methods enable us to identify and contextualize virulence-determining motifs in the capsular polysaccharide of Staphylococcus aureus and Acinetobacter baumannii. Further, we show that glycan-based phylogenetic trees contain most of the information present in traditional 16S rRNA-based phylogenies and improve on the differentiation of genetically closely related but phenotypically divergent species, such as Bacillus cereus and Bacillus anthracis. Leveraging the evolutionary information inherent in glycans with machine learning methodology is poised to provide further - critically needed - insights into host-pathogen interactions, sequence-to-function relationships, and the major influence of glycans on phenotypic plasticity.

Recombinant human insulin-like growth factor-1 therapy for 6 months improves growth but not motor function in boys with Duchenne muscular dystrophy.

Abstract: INTRODUCTION Recombinant human insulin-like growth factor-1 (rhIGF-1) is a growth factor and has anabolic effects on muscle. We investigated whether rhIGF-1 therapy: 1) improves or preserves muscle function; and 2) improves growth in boys with Duchenne muscular dystrophy (DMD). METHODS In this study we compared prepubescent, ambulatory, glucocorticoid-treated boys with DMD (n = 17) vs controls (glucocorticoid therapy only, n = 21) in a 6-month-long, prospective, randomized, controlled trial of subcutaneous rhIGF-1 therapy. The primary outcome was 6-minute walk distance (6MWD). Secondary outcomes included height velocity (HV), change in height standard deviation score (ΔHtSDS), motor function, cardiopulmonary function, body composition, insulin sensitivity, quality of life, and safety. RESULTS Change in 6MWD was similar between groups (rhIGF-1 vs controls [mean ± SD]: 3.4 ± 32.4 vs -5.1 ± 50.2 meters, P = .53). Treated subjects grew more than controls (HV: 6.5 ± 1.7 vs 3.3 ± 1.3 cm/year, P < .0001; 6-month ΔHtSDS: 0.25, P < .0001). Lean mass and insulin sensitivity increased in treated subjects. DISCUSSION In boys with DMD, 6 months of rhIGF-1 therapy did not change motor function, but it improved linear growth.

Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni

Abstract: Schistosomes kill 250,000 people every year and are responsible for serious morbidity in 240 million of the world9s poorest people. Despite their profound global impact, only a single drug (praziquantel) is available to treat schistosomiasis, highlighting the need to better understand schistosome biology to drive the development of a new generation of therapeutics. A major barrier to this goal is the paucity of large-scale datasets exploring schistosome gene function. Here, we describe the first large-scale RNA interference screen in adult Schistosoma mansoni examining the function of over 2000 genes representing approximately 20 percent of the protein coding genome. More than 250 genes were found to have phenotypes affecting neuromuscular function, tissue integrity, stem cell maintenance, and parasite survival. Leveraging these data, we bioinformatically prioritized several compounds with in vitro activity against parasites and validated p97, a component of the ubiquitin proteasome system, as a drug target in the worm. We further reveal a potentially druggable protein kinase-signaling module involving the TAO and STK25 kinases that are essential for maintaining the transcription of muscle-specific mRNAs. Importantly, loss of either of these kinases results in paralysis and death of schistosomes following surgical transplantation into a mammalian host. We anticipate this work will invigorate studies into the biology of these poorly studied organisms and expedite the development of new therapeutics to treat an important neglected tropical disease.

Colonization with heterologous bacteria reprograms a Caenorhabditis elegans nutritional phenotype

Abstract: Animals rely on the gut microbiome to process complex food compounds that the host cannot digest and to synthesize nutrients that the host cannot produce. New systems are needed to study how the expanded metabolic capacity provided by the gut microbiome impacts the nutritional status and health of the host. Here we colonized the nematode Caenorhabditis elegans gut with cellulolytic bacteria that enabled C. elegans to utilize cellulose, an otherwise indigestible substrate, as a carbon source. The nutritional benefits of colonization with cellulolytic bacteria were assayed directly, by incorporation of isotopic biomass, and indirectly, as host larval yield resulting from glucose release in the gut. As a community component in the worm gut, cellulolytic bacteria can also support additional bacterial species with specialized roles, which we demonstrate by using Lactobacillus to protect against Salmonella infection. As a model system, C. elegans colonized with cellulolytic bacteria can be used to study microbiome-host interactions. Engineered microbiome communities may provide host organisms with novel functions, such as the ability to use more complex nutrient sources and to fight against pathogen infections. One Sentence Summary Heterologous bacteria colonizing an animal gut help digest complex sugars to provide nutrition for the host in a model system.

The Impact of Vaccination Efforts on the Spatiotemporal Patterns of the Hepatitis A Outbreak in Michigan, 2016-2018.

Abstract: BACKGROUND The United States is currently experiencing the largest hepatitis A virus (HAV) outbreak since the introduction of a vaccine in 1996. More than 31,000 cases have been reported since 2016. Although HAV had largely been considered a foodborne pathogen in recent years, this outbreak has been spread primarily through person-to-person transmission in urban settings and has been associated with homelessness and substance use. Michigan was one of the first states to report an outbreak, with 910 reported cases between August 2016 and December 2018. METHODS We analyzed surveillance and vaccination data from Michigan using a disease transmission model to investigate how vaccine timing and coverage influenced the spatiotemporal patterns of the outbreak, distinguishing between Southeast Michigan, where the outbreak began, and the rest of the state. RESULTS We estimated that vaccination had little impact in Southeast Michigan (3% cases averted [95% confidence interval (CI) = 1%, 8%]) but had a substantial impact in the rest of the state, preventing a larger outbreak (91% cases averted [95% CI = 85%, 97%]) lasting several more years. CONCLUSIONS Our results emphasize the value of targeting populations where local transmission is not yet sustained rather than populations where transmission is already waning. Simulation modeling can aid in proactive rather than reactive decision-making and may help direct the response to outbreaks emerging in other states. See video abstract: http://links.lww.com/EDE/B704.

Labeling of the Schistosoma mansoni Tegument.

Abstract: Schistosomes are deadly pathogens responsible for the neglected tropical disease schistosomiasis. The parasite's virulence is aided by a skin-like tissue called the tegument. The study of the tegument is hampered by a lack of tools suitable for visualizing the tissue. Here we describe a novel methodology employing fluorophore-conjugated dextrans that allows specific fluorescent labeling of the tegument and that is compatible with downstream fluorescence-labeling techniques including phalloidin labeling, RNA FISH, and immunofluorescence.

Compositions and methods for increasing the viability of freeze-dried probiotics

Abstract: The present disclosure relates to compositions, methods, and kits for increasing the viability of bacteria that have been subjected to freeze-drying/lyophilization In particular, the disclosure relates to compositions and methods for increasing the viability of living medicines (eg, probiotics) during lyophilization, oral rehydration, and passage through the gastrointestinal tract

Engineered post-poly a signal rna and uses thereof

Abstract: The present disclosure is related to an engineered nucleic acid encoding a post-poly A signal RNA 3' to a terminator for expression of protein, and/or non-coding RNA. Also provided herein are methods for reducing epigenetic silencing, genetic modification, transcriptional regulation of the engineered nucleic acid described herein.

Dna-responsive hydrogels, methods of altering a property of a hydrogel, and applications thereof

Abstract: Disclosed herein are hydrogels comprising a polynucleotide-based structural component. Methods of altering a property of a hydrogel based on user-defined nucleic acid input sequences are also disclosed. In addition, various applications are described that utilize these hydrogels and methods.