Rapid expansion and extinction of antibiotic resistance mutations during treatment of acute bacterial respiratory infections.

Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5-12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.

Joint single-cell measurements of nuclear proteins and RNA in vivo.

Identifying gene-regulatory targets of nuclear proteins in tissues is a challenge. Here we describe intranuclear cellular indexing of transcriptomes and epitopes (inCITE-seq), a scalable method that measures multiplexed intranuclear protein levels and the transcriptome in parallel across thousands of nuclei, enabling joint analysis of transcription factor (TF) levels and gene expression in vivo. We apply inCITE-seq to characterize cell state-related changes upon pharmacological induction of neuronal activity in the mouse brain. Modeling gene expression as a linear combination of quantitative protein levels revealed genome-wide associations of each TF and recovered known gene targets. TF-associated genes were coexpressed as distinct modules that each reflected positive or negative TF levels, showing that our approach can disentangle relative putative contributions of TFs to gene expression and add interpretability to inferred gene networks. inCITE-seq can illuminate how combinations of nuclear proteins shape gene expression in native tissue contexts, with direct applications to solid or frozen tissues and clinical specimens.

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics.

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

The microbiota regulate neuronal function and fear extinction learning.

Multicellular organisms have co-evolved with complex consortia of viruses, bacteria, fungi and parasites, collectively referred to as the microbiota1. In mammals, changes in the composition of the microbiota can influence many physiologic processes (including development, metabolism and immune cell function) and are associated with susceptibility to multiple diseases2. Alterations in the microbiota can also modulate host behaviours-such as social activity, stress, and anxiety-related responses-that are linked to diverse neuropsychiatric disorders3. However, the mechanisms by which the microbiota influence neuronal activity and host behaviour remain poorly defined. Here we show that manipulation of the microbiota in antibiotic-treated or germ-free adult mice results in significant deficits in fear extinction learning. Single-nucleus RNA sequencing of the medial prefrontal cortex of the brain revealed significant alterations in gene expression in excitatory neurons, glia and other cell types. Transcranial two-photon imaging showed that deficits in extinction learning after manipulation of the microbiota in adult mice were associated with defective learning-related remodelling of postsynaptic dendritic spines and reduced activity in cue-encoding neurons in the medial prefrontal cortex. In addition, selective re-establishment of the microbiota revealed a limited neonatal developmental window in which microbiota-derived signals can restore normal extinction learning in adulthood. Finally, unbiased metabolomic analysis identified four metabolites that were significantly downregulated in germ-free mice and have been reported to be related to neuropsychiatric disorders in humans and mouse models, suggesting that microbiota-derived compounds may directly affect brain function and behaviour. Together, these data indicate that fear extinction learning requires microbiota-derived signals both during early postnatal neurodevelopment and in adult mice, with implications for our understanding of how diet, infection, and lifestyle influence brain health and subsequent susceptibility to neuropsychiatric disorders.

Global and local selection acting on the pathogen Stenotrophomonas maltophilia in the human lung.

Bacterial populations diversify during infection into distinct subpopulations that coexist within the human body. Yet, it is unknown to what extent subpopulations adapt to location-specific selective pressures as they migrate and evolve across space. Here we identify bacterial genes under local and global selection by testing for spatial co-occurrence of adaptive mutations. We sequence 552 genomes of the pathogen Stenotrophomonas maltophilia across 23 sites of the lungs from a patient with cystic fibrosis. We show that although genetically close isolates colocalize in space, distant lineages with distinct phenotypes separated by adaptive mutations spread throughout the lung, suggesting global selective pressures. Yet, for one gene (a distant homologue of the merC gene implicated in metal resistance), mutations arising independently in two lineages colocalize in space, providing evidence for location-specific selection. Our work presents a general framework for understanding how selection acts upon a pathogen that colonizes and evolves across the complex environment of the human body.

RNA Structural Determinants of Optimal Codons Revealed by MAGE-Seq.

Synonymous codon choices at the beginning of genes optimize 5' RNA structures for enhanced translation initiation, but less is known about mechanisms that drive codon optimization downstream within the gene. To understand what determines codon choices across a gene, we generated 12,726 in situ codon mutants in the Escherichia coli essential gene infA and measured their fitness by combining multiplex automated genome engineering mutagenesis with amplicon deep sequencing (MAGE-seq). Correlating predicted 5' RNA structure with fitness revealed that codons even far from the start of the gene are deleterious if they disrupt the native 5' RNA conformation. These long-range structural interactions generate context-dependent rules that constrain codon choices beyond intrinsic codon preferences. Genome-wide RNA folding predictions confirm that natural codon choices far from the start codon are optimized in part to prevent disruption of native structures near the 5' UTR. Our results shed light on natural codon distributions and should improve engineering of gene expression for synthetic biology applications.

Isocost Lines Describe the Cellular Economy of Genetic Circuits.

Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.

Inexpensive multiplexed library preparation for megabase-sized genomes.

Whole-genome sequencing has become an indispensible tool of modern biology. However, the cost of sample preparation relative to the cost of sequencing remains high, especially for small genomes where the former is dominant. Here we present a protocol for rapid and inexpensive preparation of hundreds of multiplexed genomic libraries for Illumina sequencing. By carrying out the Nextera tagmentation reaction in small volumes, replacing costly reagents with cheaper equivalents, and omitting unnecessary steps, we achieve a cost of library preparation of $8 per sample, approximately 6 times cheaper than the standard Nextera XT protocol. Furthermore, our procedure takes less than 5 hours for 96 samples. Several hundred samples can then be pooled on the same HiSeq lane via custom barcodes. Our method will be useful for re-sequencing of microbial or viral genomes, including those from evolution experiments, genetic screens, and environmental samples, as well as for other sequencing applications including large amplicon, open chromosome, artificial chromosomes, and RNA sequencing.

Lipid-derived nanoparticles for immunostimulatory RNA adjuvant delivery.

The specific activation of Toll-like receptors (TLRs) has potential utility for a variety of therapeutic indications including antiviral immunotherapy and as vaccine adjuvants. TLR7 and TLR 8 may be activated by their native ligands, single-stranded RNA, or by small molecules of the imidazoquinoline family. However the use of TLR7/8 agonists for in vivo therapy is limited by instability, in the case of RNA, or systemic biodistribution and toxicity in the case of small molecule agonists. We hypothesized that unique lipid-like materials, termed "lipidoids," could be designed to efficiently deliver immunostimulatory RNA (isRNA) to TLR-expressing cells to drive innate and adaptive immune responses. A library of lipidoids was synthesized and screened for the ability to induce type I IFN activation in human peripheral blood mononuclear cells when combined with isRNA oligonucleotides. Effective lipidoid-isRNA nanoparticles, when tested in mice, stimulated strong IFN-α responses following subcutaneous injection, had robust antiviral activity that suppressed influenza virus replication, and enhanced antiovalbumin humoral and cell-mediated responses when used as a vaccine adjuvant. Further, we demonstrate that whereas all immunological activity was MyD88-dependent, certain materials were found to engage both TLR7-dependent and TLR7-independent activity in the mouse suggestive of cell-specific delivery. These lipidoid formulations, which are materials designed specifically for delivery of isRNA to Toll-like receptors, were superior to the commonly used N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium methylsulfate-RNA delivery system and may provide new tools for the manipulation of TLR responses in vitro and in vivo.