Despite longstanding appreciation of gene expression heterogeneity in isogenic bacterial populations, affordable and scalable technologies for studying single bacterial cells have been limited. ...Although single-cell RNA sequencing (scRNA-seq) has revolutionized studies of transcriptional heterogeneity in diverse eukaryotic systems
, the application of scRNA-seq to prokaryotes has been hindered by their extremely low mRNA abundance
, lack of mRNA polyadenylation and thick cell walls
. Here, we present prokaryotic expression profiling by tagging RNA in situ and sequencing (PETRI-seq)-a low-cost, high-throughput prokaryotic scRNA-seq pipeline that overcomes these technical obstacles. PETRI-seq uses in situ combinatorial indexing
to barcode transcripts from tens of thousands of cells in a single experiment. PETRI-seq captures single-cell transcriptomes of Gram-negative and Gram-positive bacteria with high purity and low bias, with median capture rates of more than 200 mRNAs per cell for exponentially growing Escherichia coli. These characteristics enable robust discrimination of cell states corresponding to different phases of growth. When applied to wild-type Staphylococcus aureus, PETRI-seq revealed a rare subpopulation of cells undergoing prophage induction. We anticipate that PETRI-seq will have broad utility in defining single-cell states and their dynamics in complex microbial communities.
The yeast Saccharomyces cerevisiae has been the subject of many studies aimed at understanding mechanisms of adaptation to environmental stresses. Most of these studies have focused on adaptation to ...sub-lethal stresses, upon which a stereotypic transcriptional program called the environmental stress response (ESR) is activated. However, the genetic and regulatory factors that underlie the adaptation and survival of yeast cells to stresses that cross the lethality threshold have not been systematically studied. Here, we utilized a combination of gene expression profiling, deletion-library fitness profiling, and experimental evolution to systematically explore adaptation of S. cerevisiae to acute exposure to threshold lethal ethanol concentrations-a stress with important biotechnological implications. We found that yeast cells activate a rapid transcriptional reprogramming process that is likely adaptive in terms of post-stress survival. We also utilized repeated cycles of lethal ethanol exposure to evolve yeast strains with substantially higher ethanol tolerance and survival. Importantly, these strains displayed bulk growth-rates that were indistinguishable from the parental wild-type strain. Remarkably, these hyper-ethanol tolerant strains had reprogrammed their pre-stress gene expression states to match the likely adaptive post-stress response in the wild-type strain. Our studies reveal critical determinants of yeast survival to lethal ethanol stress and highlight potentially general principles that may underlie evolutionary adaptation to lethal stresses in general.
Microorganisms exist almost exclusively in interactive multispecies communities, but genetic determinants of the fitness of interacting bacteria, and accessible adaptive pathways, remain ...uncharacterized. Here, using a two-species system, we studied the antagonism of Pseudomonas aeruginosa against Escherichia coli. Our unbiased genome-scale approach enabled us to identify multiple factors that explained the entire antagonism observed. We discovered both forms of ecological competition-sequestration of iron led to exploitative competition, while phenazine exposure engendered interference competition. We used laboratory evolution to discover adaptive evolutionary trajectories in our system. In the presence of P. aeruginosa toxins, E. coli populations showed parallel molecular evolution and adaptive convergence at the gene-level. The multiple resistance pathways discovered provide novel insights into mechanisms of toxin entry and activity. Our study reveals the molecular complexity of a simple two-species interaction, an important first-step in the application of systems biology to detailed molecular dissection of interactions within native microbiomes.
Here we explore the possibility that a core function of sensory cortex is the generation of an internal simulation of sensory environment in real-time. A logical elaboration of this idea leads to a ...dynamical neural architecture that oscillates between two fundamental network states, one driven by external input, and the other by recurrent synaptic drive in the absence of sensory input. Synaptic strength is modified by a proposed synaptic state matching (SSM) process that ensures equivalence of spike statistics between the two network states. Remarkably, SSM, operating locally at individual synapses, generates accurate and stable network-level predictive internal representations, enabling pattern completion and unsupervised feature detection from noisy sensory input. SSM is a biologically plausible substrate for learning and memory because it brings together sequence learning, feature detection, synaptic homeostasis, and network oscillations under a single unifying computational framework.
The homeostatic framework has dominated our understanding of cellular physiology. We question whether homeostasis alone adequately explains microbial responses to environmental stimuli, and explore ...the capacity of intracellular networks for predictive behavior in a fashion similar to metazoan nervous systems. We show that in silico biochemical networks, evolving randomly under precisely defined complex habitats, capture the dynamical, multidimensional structure of diverse environments by forming internal representations that allow prediction of environmental change. We provide evidence for such anticipatory behavior by revealing striking correlations of Escherichia coli transcriptional responses to temperature and oxygen perturbations--precisely mirroring the covariation of these parameters upon transitions between the outside world and the mammalian gastrointestinal tract. We further show that these internal correlations reflect a true associative learning paradigm, because they show rapid decoupling upon exposure to novel environments.
Antibiotic persistence, the noninherited tolerance of a subpopulation of bacteria to high levels of antibiotics, is a bet-hedging phenomenon with broad clinical implications. Indeed, the isolation of ...bacteria with substantially increased persistence rates from chronic infections suggests that evolution of hyperpersistence is a significant factor in clinical therapy resistance. However, the pathways that lead to hyperpersistence and the underlying cellular states have yet to be systematically studied. Here, we show that laboratory evolution can lead to increase in persistence rates by orders of magnitude for multiple independently evolved populations of
and that the driving mutations are highly enriched in translation-related genes. Furthermore, two distinct adaptive mutations converge on concordant transcriptional changes, including increased population heterogeneity in the expression of several genes. Cells with extreme expression of these genes showed dramatic differences in persistence rates, enabling isolation of subpopulations in which a substantial fraction of cells are persisters. Expression analysis reveals coherent regulation of specific pathways that may be critical to establishing the hyperpersistence state. Hyperpersister mutants can thus enable the systematic molecular characterization of this unique physiological state, a critical prerequisite for developing antipersistence strategies.
Bacterial persistence is a fascinating phenomenon in which a small subpopulation of bacteria becomes phenotypically tolerant to lethal antibiotic exposure. There is growing evidence that populations of bacteria in chronic clinical infections develop a hyperpersistent phenotype, enabling a substantially larger subpopulation to survive repeated antibiotic treatment. The mechanisms of persistence and modes of increasing persistence rates remain largely unknown. Here, we utilized experimental evolution to select for
mutants that have more than a thousandfold increase in persistence rates. We discovered that a variety of individual mutations to translation-related processes are causally involved. Furthermore, we found that these mutations lead to population heterogeneity in the expression of specific genes. We show that this can be used to isolate populations in which the majority of bacteria are persisters, thereby enabling systems-level characterization of this fascinating and clinically significant microbial phenomenon.
Deciphering the noncoding regulatory genome has proved a formidable challenge. Despite the wealth of available gene expression data, there currently exists no broadly applicable method for ...characterizing the regulatory elements that shape the rich underlying dynamics. We present a general framework for detecting such regulatory DNA and RNA motifs that relies on directly assessing the mutual information between sequence and gene expression measurements. Our approach makes minimal assumptions about the background sequence model and the mechanisms by which elements affect gene expression. This provides a versatile motif discovery framework, across all data types and genomes, with exceptional sensitivity and near-zero false-positive rates. Applications from yeast to human uncover putative and established transcription-factor binding and miRNA target sites, revealing rich diversity in their spatial configurations, pervasive co-occurrences of DNA and RNA motifs, context-dependent selection for motif avoidance, and the strong impact of posttranscriptional processes on eukaryotic transcriptomes.
Phenotypic heterogeneity displayed by a clonal bacterial population permits a small fraction of cells to survive prolonged exposure to antibiotics. Although first described over 60 y ago, the ...molecular mechanisms underlying this behavior, termed persistence, remain largely unknown. To systematically explore the genetic basis of persistence, we selected a library of transposon-mutagenized Escherichia coli cells for survival to multiple rounds of lethal ampicillin exposure. Application of microarray-based genetic footprinting revealed a large number of loci that drastically elevate persistence frequency through null mutations and domain disruptions. In one case, the C-terminal disruption of methionyl-tRNA synthetase (MetG) results in a 10,000-fold higher persistence frequency than wild type. We discovered a mechanism by which null mutations in transketolase A (tktA) and glycerol-3-phosphate (G3P) dehydrogenase (glpD) increase persistence through metabolic flux alterations that increase intracellular levels of the growth-inhibitory metabolite methylglyoxal. Systematic double-mutant analyses revealed the genetic network context in which such persistent mutants function. Our findings reveal a large mutational target size for increasing persistence frequency, which has fundamental implications for the emergence of antibiotic tolerance in the clinical setting.
Thymidine starvation causes rapid cell death. This enigmatic process known as thymineless death (TLD) is the underlying killing mechanism of diverse antimicrobial and antineoplastic drugs. Despite ...decades of investigation, we still lack a mechanistic understanding of the causal sequence of events that culminate in TLD. Here, we used a diverse set of unbiased approaches to systematically determine the genetic and regulatory underpinnings of TLD in Escherichia coli. In addition to discovering novel genes in previously implicated pathways, our studies revealed a critical and previously unknown role for intracellular acidification in TLD. We observed that a decrease in cytoplasmic pH is a robust early event in TLD across different genetic backgrounds. Furthermore, we show that acidification is a causal event in the death process, as chemical and genetic perturbations that increase intracellular pH substantially reduce killing. We also observe a decrease in intracellular pH in response to exposure to the antibiotic gentamicin, suggesting that intracellular acidification may be a common mechanistic step in the bactericidal effects of other antibiotics.
Microglia are resident immune cells of the CNS that are activated by infection, neuronal injury, and inflammation. Here, we utilize flow cytometry and deep RNA sequencing of acutely isolated spinal ...cord microglia to define their activation in vivo. Analysis of resting microglia identified 29 genes that distinguish microglia from other CNS cells and peripheral macrophages/monocytes. We then analyzed molecular changes in microglia during neurodegenerative disease activation using the SOD1G93A mouse model of amyotrophic lateral sclerosis (ALS). We found that SOD1G93A microglia are not derived from infiltrating monocytes, and that both potentially neuroprotective and toxic factors, including Alzheimer’s disease genes, are concurrently upregulated. Mutant microglia differed from SOD1WT, lipopolysaccharide-activated microglia, and M1/M2 macrophages, defining an ALS-specific phenotype. Concurrent messenger RNA/fluorescence-activated cell sorting analysis revealed posttranscriptional regulation of microglia surface receptors and T cell-associated changes in the transcriptome. These results provide insights into microglia biology and establish a resource for future studies of neuroinflammation.
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•Identification of specific marker genes for acutely isolated microglia•Progressive resident microglia transcriptome changes reveal in vivo activation phenotype•Microglial ALS disease activation signature distinct from M1/M2 macrophages•Parallel transcriptome and FACS analyses reveal T cell/microglia crosstalk
Microglia are resident immune cells of the brain that are activated by infection or tissue damage. In this study, Maniatis and colleagues report the acute isolation, transcriptional profiling, and immunological analysis of microglia during disease activation in an ALS mouse model. A neurodegeneration-specific gene-expression signature is identified that includes induction of both neuroprotective and toxic factors and is distinct from that associated with M1/M2 macrophages. The data also provide a resource for future studies of microglia activation in neurodegenerative diseases.
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